Vol. 18 No. 1, June 2017 - Balai PATPbpatp.litbang.pertanian.go.id/balaipatp/assets/upload/download/file/Dokumen_378.pdf · Vol. 18 No. 1, June 2017 Indonesian Journal of Agricultural

Vol. 18 No. 1, June 2017Accredited by the Indonesian Institute ofSciences No. 818/E/2015

Editorial TeamEditor-in-ChiefMarkus Anda Mineralogy and Soil Classification (Scopus ID : 23024287000 / h-Index:

6) Indonesian Center for Agricultural Land Resources Research and Development, Indonesia

International Editorial Board

Supriadi Plant Pathology, Indonesian Spice and Medicinal Crops Research Institute, Indonesia

Budi Tangendjaja Animal Feed and Nutrition, (Scopus ID: 6508321607 / h-Index : 6) Indonesian Center for Animal Research and Development, Indonesia

Dewa Ketut Sadra Swastika Socioeconomics, Indonesian Center for Agricultural Socio Economic and Policy Studies, Indonesia

Randy Alan Dahlgren Soil Science and Biogeochemistry, (Scopus ID: 7005899511 / h-Index : 45)University of California, Davis, United States

Bunyamin Tar’an Plant Biotechnology, (Scopus ID: 56181765200 / h-Index : 17) University of Saskatchewan, Canada

Soon-Wook Kwan Plant Breeding and Molecular Breeding, (Scopus ID : 55782595000 / h-Index : 9) Pusan National University, Republic of Korea

Sri Yuliani Postharvest Technology, (Scopus ID : 9844293200 / h-Index : 6) Indonesian Center for Agricultural Postharvest Research and Development, Indonesia

I Made Tasma Plant Breeding and Molecular Biology, (Scopus ID : 6507936762 / h-Index : 6) Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development, Indonesia

Puji Lestari Molecular Biology, (Scopus ID : 6507413576 / h-Index : 6) Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development, Indonesia

Md. Babul Akter Crop Physiology and Molecular Breeding, Bangladesh Institute of Nuclear Agriculture (BINA), Bangladesh

Assistant EditorEndang Setyorini Indonesian Center for Agricultural Library and Technology Dissemination,

IndonesiaKania Tresnawati Indonesian Institute for Agricultural Technology Transfer, IndonesiaSara Purnasihar Indonesian Institute for Agricultural Technology Transfer, IndonesiaSlamet Sutriswanto Indonesian Center for Agricultural Library and Technology Dissemination,

IndonesiaLayout EditorIrwan Arfiansyah Indonesian Institute for Agricultural Technology Transfer, Indonesia

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Indonesian Journal of

AGRICULTURALSCIENCE

ISSN 1411-982XE-ISSN 2354-8509

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Kularb Laosatit Genetic and Molecular Biology, (Scopus ID : 36872678000 / h-Index : 3), Faculty of Agriculture at Kamphaeng Saen, Kasetsart University, Kamphaeng Saen, Nakhon Pathom, 73140, Thailand

Ahmad Kurnain Soil Science, (Scopus ID : 56515310300 / h-Index: -), Lambung Mangkurat University, Banjarmasin, Indonesia

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Ika Mariska Plant Physiology and Biotechnology In Vitro Culture, (Scopus ID : 6507460259 / h Index : 4) Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development, Indonesia

Backki Kim Biochemistry, Genetics and Molecular Biology, (Scopus ID : 56042253700 / h-Index : 3), Texas A&M University, College Station, TX 77843, United States

Sutoro Agronomy, Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development, Indonesia

Indonesian Journal of

AGRICULTURALSCIENCE

ISSN 1411-982XE-ISSN 2354-8509

Vol. 18 No. 1, June 2017

Indonesian Journal of Agricultural Science is previously published as Indonesian Journal of Crop Science (1985 - 1999). This journal is published in one volume of two issues per year on June and December by the Indonesian Agency for Agricultural Research and Development. It is available online at: ejurnal.litbang.perta-nian.go.id/index.php/ijas

The journal publishes primary research articles of current research topics, not simultaneously submitted to nor previously published in other scientific or technical journals. General review articles will not be accepted. The journal maintains strict standards of content, presentation, and reviewing. The official language of the journal is English. The journal will consider papers from any source if they make an original contribution to the experimental or theoretical understanding and application of theories and methodologies of some aspects of agricultural science. The definition of agricultural science is kept as broad as possible to allow the widest coverage in the journal including socio-economic aspects. The focus of the journal is in the following areas: Agronomy, animal science, soil science, climate and environment related to agricultural aspects. Agronomy covers the topics of plant breeding, physiology, production, biotechnology, plant protection (pest and disease) and postharvest. Animal sciences include breeding, nutrition, reproduction, and disease. Soil Sciences cover aspects of mineralogy, classification, land evaluation, chemistry, fertility, fertilizer, conservation, and biology.

Low association of Bph17 allele in landraces and improved varieties of rice resistant to brown planthopperWage Ratna Rohaeni, Untung Susanto and Aida F.V. Yuningsih 1–6

Phenotypic performance of Ciherang sub1 near isogenic line as an adaptive variety for flooding conditionsYudhistira Nugraha, Nurul Hidayatun, Trisnaningsih, Dini Yuliani, Shinta Ardiyanti and Triny Suryani Kadir 7–16

Inhibition of the growth of tolerant yeast Saccharomyces cerevisiae strain I136 by a mixture of synthetic inhibitors Eny Ida Riyanti and Edy Listanto 17–24

Gene action and heritability estimates of quantitative characters among lines derived from varietal crosses of soybeanLukman Hakim and Suyamto 25–32

Complete rumen modifier supplementation in corn cob silage basal diet of lamb reduces methane emissionDwi Yulistiani, Wisri Puastuti, Budi Haryanto, Agung Purnomoadi, M. Kurihara and Amlius Thalib 33–42

CONTENTS

Indonesian Journal of Agricultural Science Vol. 18 No. 1 June 2017: 1–6

DOI: http//dx.doi.org/10.21082/ijas.v.18.n1.2017.p.1–6

LOW ASSOCIATION OF Bph17 ALLELE IN LANDRACES AND IMPROVED VARIETIES OF RICE RESISTANT TO BROWN PLANTHOPPER

Asosiasi Rendah Alel Bph17 pada Varietas Lokal dan Varietas Unggul Padi Tahan Wereng Batang Cokelat

Wage Ratna Rohaeni*, Untung Susanto and Aida F.V. Yuningsih

Indonesian Center for Rice ResearchJalan Raya No. 9 Sukamandi, Subang 41256, West Java, Indonesia

Phone +62 260 520157, Fax. +62 260 520158*Corresponding author: [email protected]

Submitted 28 July 2016; Revised 31 March 2017; Accepted 7 April 2017

ABSTRACT

Resistance traits to brown planthopper on rice varieties are controlled by dominant and recessive genes called Bph/bph. Bph17 is one of dominant genes that control rice resistance to brown planthopper. Marker of Bph17 allele can be used as a tool of marker assisted selection (MAS) in breeding activity. Association of Bph17 allele and resistance to brown planthopper in Indonesian landraces and new-improved varieties of rice is not clearly known. The study aimed to determine the association of Bph17 allele in landraces and new-improved varieties of rice resistant to brown planthopper. Twenty-one rice genotypes were used in the study, consisting of 13 landraces, 5 improved varieties, 3 popular varieties and a check variety Rathu Heenati. Two simple sequence repeat markers linked to Bph17 allele were used, i.e. RM8213 and RM5953. The results showed that association of Bph17 allele in landraces and new-improved varieties of rice resistant to brown planthopper resistance was very low (r = -0.019 and -0.023, respectively). The presence of Bph17 allele did not constantly express resistance to brown planthopper. The study suggests that Bph17 allele cannot be used as a tool of MAS for evaluating resistance of landraces and new-improved varieties of rice to brown planthopper. Further research is needed to obtain a specific gene marker that can be used as a tool of MAS and applicable for Indonesian differential rice varieties.

[Keywords: association, Bph17 allele, plant resistance, brown planthopper, rice varieties]

ABSTRAK

Sifat ketahanan terhadap wereng batang cokelat (WBC) pada varietas padi dikendalikan oleh gen dominan dan gen resesif yang disebut Bph/bph. Bph17 merupakan salah satu gen dominan yang mengendalikan sifat ketahanan tanaman padi terhadap WBC. Marka alel Bph17 dapat menjadi alat bantu seleksi (marker assisted selection, MAS) pada kegiatan pemuliaan. Hubungan antara kehadiran alel Bph17 dan sifat ketahanan terhadap WBC pada varietas padi lokal Indonesia dan beberapa varietas unggul baru (VUB) belum diketahui secara jelas. Penelitian ini bertujuan untuk mengetahui asosiasi antara kehadiran alel Bph17 dan karakter ketahanan terhadap WBC pada padi varietas lokal dan VUB. Sebanyak 21 genotipe digunakan dalam penelitian ini, terdiri atas 13 varietas lokal, 5 VUB, 3 varietas populer, dan Rathu

Heenati. Dua penanda spesifik alel Bph17 digunakan, yaitu RM8213 dan RM5953. Hasil penelitian membuktikan bahwa asosiasi antara keberadaan alel Bph17 dan sifat ketahanan terhadap WBC pada padi lokal dan VUB sangat rendah (r = -0,019 dan -0,023). Kehadiran alel Bph17 tidak mengekspresikan ketahanan terhadap WBC pada varietas lokal dan VUB. Hasil penelitian ini menunjukkan bahwa alel tidak dapat digunakan sebagai alat bantu seleksi untuk mengevaluasi ketahanan padi varietas lokal dan VUB terhadap WBC. Diperlukan penelitian lebih lanjut untuk mendapatkan penanda gen spesifik yang dapat digunakan sebagai alat bantu seleksi untuk varietas padi diferensial Indonesia.

[Kata kunci: hubungan, alel Bph17, sifat ketahanan, wereng cokelat varietas padi]

INTRODUCTION

Brown planthopper (BPH; Nilaparvata lugens) is a major pest of rice crop around the world, including Indonesia. The pest is cosmopolitan, potentially reducing rice production even causing crop failure (Watanabe et al. 2009; Direktorat PTP 2016). Rice plants stricken by BPH show symptoms of leaf yellowing and dry, stunted growth, and eventually die (Baehaki 2012). The 100-140-day old rice plant had higher number of BPHs per hill compared to 80-90-day old crop (Prashant et al. 2012). Current technology that effectively controls BPH is a resistant variety (Baehaki and Mejaya 2014).

Resistance traits to BPH on rice varieties are controlled by major and minor genes called Bph/bph (Brar et al. 2009). The genes were mapped on chromosomes 2, 3, 4, 6, 7 and 9 (Liu et al. 2001; Liu et al, 2009). Bph17 is one of dominant genes that control resistance trait to BPH (Brar et al. 2009). The gene is located on chromosome 4 (Rahman et al. 2009) and derived from BPH donor resistance gene of Rathu Heenati (Sun et al. 2005).

Bph17 gene has been used as a donor in breeding program of BPH-resistant rice varieties (Iswanto et al.

2 Indonesian Journal of Agricultural Science Vol. 18 No. 1 June 2017: 1–6

2015). Sun et al. (2005) and Jena et al. (2006) revealed that RM8213 and RM5953 DNA markers are closely linked to Bph17 gene that controls the expression of resistance trait. These markers can be used as a tool of marker assisted selection (MAS) with marker alleles at 177 bp on RM8213 PCR products and 140 bp on RM5953 PCR products (Sun et al. 2005; Jena et al. 2006). DNA products of RM8213 follow the Mendelian inheritance pattern of 1:2:1 (susceptible: heterozygous segregation: resistant) (Pertiwi et al. 2014; Carsono et al. 2016).

The success of MAS such as Bph17 marker depends on several factors, including genetic base of trait, degree of association between molecular marker and target gene, number of individuals analyzed, and genetic background of the target gene to be transferred (Francia et al. 2005; Wang et al. 2008). DNA markers such as Bph17 need to be evaluated for identifying BPH biotypes. The use of MAS to suspect and avail the selection of simply inherited traits is increasingly important in breeding programs, allowing an acceleration of breeding process, and is not affected by the environment or growing conditions (Guimarães et al. 2007; Bahagiawati 2012). Many of MAS are used as a marker assisted breeding (MAB) for selection of segregated population, but sometimes cannot be used for selection of non-breeding populations as well as landraces or local rice (depending on the marker trait). Carsono et al. (2016) found 63 selected lines from F2 progenies of resistant parent based on the linked marker of Bph17 allele of Rathu Heenati as the check variety.

Landrace is a germplasm containing resistance genes to pests and diseases (Sitaresmi et al. 2013). Some landraces and new-improved varieties of rice have been identified for resistance to BPH (Yunani et al. 2014; Jamil et al. 2015). However, the presence of resistance genes, especially Bph17 in Indonesian landraces and some new-improved varieties has not been intensively studied. To support breeding program based on landrace populations, it is necessary to study the presence of these BPH resistance genes in Indonesian landraces and several new-improved varieties of rice and find out the association of Bph17 allele position on Rathu Heenati.

The study aimed to determine the association between Bph17 allele in landraces and improved varieties of rice and resistance to BPH.

MATERIALS AND METHODS

The study was conducted in 2015 in DNA Laboratory of Plant Breeding Division, Indonesian Center for Rice Research (ICRR) at Subang, West Java.

Plant Materials

The study used 21 rice genotypes, consisted of 13 landraces from various provinces in Indonesia, one positive check variety (Rathu Heenati), five new improved varieties and three popular varieties (Table 1). The rice genotypes belonged to ICRR. Ten to twenty seeds of each accession were germinated in the planting medium then put into the germinator cabinet. The 21 day-old rice seedings were transplanted into polybags containing a mixture of soil and sand growth medium (50:50). The plants were kept in the greenhouse of Plant Breeding Division, ICRR, and maintained according to protocol of The Crop Manager version 1.0 by IRRI (http://webapps.irri.org).

Molecular Analysis

Molecular analysis was done using simple sequence repeat (SSR). The analysis consisted of five major activities, namely DNA isolation, DNA quantity and quality test, polymerase chain reaction (PCR) amplification, electrophoresis of PCR products, and visualization of electrophoresis products.

DNA Isolation and DNA Quantity and Quality Test

Five young leaves of 10-day old rice seedlings of each accession were taken and used for DNA isolation. The DNA was extracted following the method of Murray and Thompson (1980) by small modification on leaf crushing. The leaves were crushed in a mortar without liquid nitrogen and homogenized with 800 µl CTAB buffer. DNA quality and quantity were measured using NanoDrop 2000/UV-Vis Spectrophotometer at 260 and 280 nm.

PCR Amplification

DNA of Bph17 allele in the leaf samples was amplified using SSR markers, i.e. RM8213 and RM5953 (Sun et al. 2005) (Table 2). Extracted DNA was amplified using PCR machine (BIO-RAD T100TM Thermal Cycler) applying the ICRR DNA Laboratory procedure. PCR cocktail was made consisting of 50 ng DNA sample, 0.25 μM forward and reverse primers, 100 μM dNTPs, 1x PCR buffer (consisting of 20 mM Tris pH 8.3, 50 mM KCl, 1.5 mM MgCl2, and 0.01% gelatin), and 0.5 units Taq DNA polymerase. PCR amplification was performed under the following conditions: denaturation at 95ºC for 5 min, 35

3Low association of bph17 allele in landraces … (Wage Ratna Rohaeni et al.)

Table 1. List of accessions and origin of rice varieties used in the study.

No. Lab

No. ac-cession

Accession/variety

Subspecies Origin/pedigreeResistance

to BPHReference

Landraces1 33 Bandang Si Gadis Indica North Sumatra S Yunani et al. (2014)2 144 Padi Kuning Indica Jambi S Yunani et al. (2014)3 268 Si Awak Indica Bengkulu MR Yunani et al. (2014))4 289 Takong Indica East Kalimantan MS Yunani et al. (2014)5 673 Pare Ndele A Javanica East Nusa Tenggara S Yunani et al. (2014)6 1039 Mentik Wangi Indica Central Java S Yunani et al. (2014)7 1240 Cinta Kasih Indica Bengkulu MS Yunani et al. (2014)8 1546 Rethu Heenati Indica Introduction R Yunani et al. (2014)9 2733 Padi Serai Indica East Kalimantan S Yunani et al. (2014)10 2734 Selasih Indica East Kalimantan S Yunani et al. (2014)11 4771 Mayas Indica East Kalimantan S Yunani et al. (2014)12 7787 Marahmay Indica Banten S Yunani et al. (2014)13 7944 Jadul Japonica Central Kalimantan R Yunani et al. (2014)

New Improved Varieties14 Inpari 34 Indica BR41XIR6190-3B-22-2 MS Jamil et al. (2015)15 Inpari 35 Indica IR10206-29-21XSUAKOKO S Jamil et al. (2015)16 Inpari 36 Indica IR58773-35-3-1-2/IR65475-62-3-1-3-1 S Jamil et al. (2015)17 Inpari 37 Indica CT9162-12/SeratushariT36//Membramo/

Cibodas///IR66160-121-4-5-3/MembramoS Jamil et al. (2015)

18 Inpari 38 Indica IR68888/BP68*10/Selegreng/Guarani/Asahan

MS Jamil et al. (2015)

Popular Varieties

19 Ciherang Indica IR18349-53-1-3-1-3/IR9661-131-3-1//IR19661-131-3-1-3///IR64///IR64

R Jamil et al. (2015)

20 Rojolele Javanica Local Delanggu Klaten S Yunani et al. (2014)21 Batanghari Indica Cisadane/IR19661-131-1-3-1-3 MR Suprihatno et al. (2010)

BPH = brown planthopper; Resistance to BPH: S = susceptible, MS = moderately susceptible, MR = moderately resistant, R = resistant.

Table 2. Markers linked for the amplification of Bph17 allele DNA.

Marker Chr Forward (5’-3’) Reverse (5’-3’) Tm Size Reference

RM8213 4 AGCCCAGTGATACAAAGATG GCGAGGAGATACCAAGAAAG 55 177 Sun et al. (2005)

RM5953 12 AAACTTTCTGTGATGGTATC ATCCTTGTCTAGAATTGACA 55 129 Sun et al. (2005), Shabanimofrad (2015)

cycles of 1 min denaturation at 94ºC, 1 min annealing at 55ºC, 1 min extension at 72ºC, and a final extension at 72ºC for 5 min. The amplification was verified by continuous polyacrylamide gel electrophoresis (8%) to ascertain the presence of amplifiable DNA under 100 volts for 60 minutes in 1 x TBE buffer.

Data Analysis

The amplification data were analyzed based on the presence (1) or absence (0) of DNA bands. DNA polymorphism of Rathu Heenati was used as a reference of the Bph17 allele. The presence of Bph17 allele on each accession was ascertained at a distance of 177 bp and 129 bp based on RM5953 and RM8213 markers existing on the check variety Rathu Heenati. Association of the

presence of Bph17 allele bands and plant resistance to BPH was analyzed using correlation analysis by Minitab version 13 software.

RESULTS AND DISCUSSION

BPH Resistance

Resistance levels of rice genotypes to BPH biotype 3 varied (Table 3), ranging from susceptible to resistant. Resistance trait was owned by Rathu Heenati, Jadul and Ciherang, while moderately resistance trait was owned by Si Awak and Batanghari. Takong, Cinta Kasih, Inpari 34 and Inpari 38 were moderately susceptible, while Bandang Si Gadis, Padi Kuning, Pare Ndele A, Mentik Wangi, Padi Serai, Selasih, Mayas, Marahmay, Inpari


Table 3. The presence of Bph17 allele fragments based on two specific primers RM8213 and RM5953 on several landrace, improved and popular rice accessions.

No. ac-cession

Accession/varietyResis-tance*)

RM8213-177bp

RM5953-129bp

Landraces33 Bandang Si Gadis S + +144 Padi Kuning S - +268 Si Awak MR + +289 Takong MS + +673 Pare Ndele A S - -1039 Mentik Wangi S + +1240 Cinta Kasih MS + +1546 Rathu Heenati* R + +2733 Padi Serai S + +2734 Selasih S - +4771 Mayas S + +7787 Marahmay S + +7944 Jadul R - -

Ciherang MR - -Improved varietiesInpari 34 MS - -Inpari 36 S + -Inpari 37 S + -Inpari 38 MS + -Popular varietiesRojolele S - -Inpari 35 S - -

Batanghari MR + -*)Source: Yunani et al .(2014), R = resistant, MR = moderately resistant, MS = moderately susceptible, S = susceptible. + = allele presence, - = allele absence.

Fig. 1. Visualization of polymerase chain reaction products of RM8213 (A) and RM5953 (B).

35, Inpari 36, Inpari 37 and Rojolele were susceptible to BPH. Data on resistance to BPH biotype 3 from ICRR Gene Bank showed that biotype 3 is the most virulent biotype. Therefore, the biotype was selected to investigate the existence of Bph17 allele.

Brown planthopper has a high genetic plasticity, making it easier and faster in forming a new biotype (Baehaki and Widiarta 2009). Therefore, breeding of rice varieties having durable resistance to BPH is needed to compensate the development of BPH biotypes (Baehaki 2012; Baehaki and Mejaya 2014). Resistance trait to BPH has a narrow genetic variability. Nugaliyadde et al. (2016) reported that resistance to BPH was monogenic dominant based on the damage reaction at seedling stage of F1 and F2 generations from crosses between PTB33 and susceptible variety. On the other hand, Sai Harini et al. (2013) stated that resistance trait to BPH had a wide genetic variability based on molecular analysis results.

Bph17 allele could be used for marker assisted selection (Sun et al. 2005). For rapid identification requirements associated with resistance trait to BPH in Indonesian rice landraces, the role of this allele and its presence need to be investigated clearly. Specific markers for Bph17 were mapped at RM8213-177bp and RM-5953-129bp on Rathu Heenati.

Identification of Bph17 Allele

Table 3 shows that RM8213-177 bp was not only present in positive-check variety (Rathu Heenati), but also in eight landraces, three new improved varieties and Batanghari. Meanwhile, based on the results of RM5953 amplification at 129 bp, specific band was present on check variety and 10 landraces, but the band was absent in new improved varieties tested (Figure 1).

RM8213 and RM5953 gave different results regarding the presence of Bph17 allele. The genotypes of Bandang Si Gadis, Si Awak, Takong, Mentik Wangi, Cinta Kasih, Padi Serai, Mayas and Marahmay had both of the markers (RM8213-177bp and RM5953-129bp). Most of the landraces had Bph17 allele. Eight accessions had the two allele markers, including Bandang Si Gadis, Si Awak, Takong, Mentik Wangi, Cinta Kasih, Padi Serai, Mayas and Marahmay. On the other hand, RM8213-177 bp allele only appeared on Inpari 36, Inpari 37, Inpari 38 and Batanghari, while RM5953-129 bp allele was only present on Padi Kuning and Selasih (Table 3).

One landrace (Si Awak) had Bph17 allele and medium resistance to BPH biotype 3. The contradictive results

Table 4. Association between Bph17 allele and BPH resistance traits based on correlation analysis.

Correlation Resistances RM8213-177bp

RM8213-177bp -0.119

Prob. 0.608

RM5953-129bp -0.023 0.430

Prob. 0.921 0.052

Prob. > 0.05 shows no significant correlation.

5Low association of bph17 allele in landraces … (Wage Ratna Rohaeni et al.)

were observed on Rathu Heenati vs Jadul and Ciherang. Rathu Heenati had Bph17 allele and was resistant to BPH, while Jadul which did not have Bph17 allele, was resistant to BPH.

Association Between Bph17 Allele and BPH Resistance

The presence of the bands that indicate Bph17 had a very low relationship with BPH resistance. The analysis result showed that the correlation between the presence of RM8213-177bp and RM5953-129bp and BPH resistance was very low and not significant (r = -0.119 and -0.023, respectively). This means that the presence of Bph17 allele had very low association with resistance traits to BPH in Indonesian landraces and new-improved varieties of rice.

The presence of Bph17 allele mostly contradicted with the resistance information on landraces and new-improved varieties. The data revealed that some Indonesian landraces that had a Bph17 gene were not necessarily resistant to the most virulent BPH and the resistant varieties did not necessarily have a Bph17 gene. Some landraces that have a Bph17 allele (the same allele with Rathu Heenati, positive check variety) based on SSR analysis were susceptible to BPH. It is allegedly because although the size of DNA bands are the same, the DNA sequences are completely different.

The same result was observed by Damayanti (2014) on bph4 alelle. The allele was absent in resistant genotypes, but it was present in susceptible genotypes. The Bph1 allele also had a low association with resistance to BPH in promising lines. Rahmini et al. (2012) reported that IR42 has a bph2 allele, but the feeding activity of BPH of biotype 3 on this variety is very high.

Sun et al. (2006) reported the great progress in MAS development in recent years, but relatively few varieties or lines successfully developed by this method due to low association of specific marker and resistance. The presence of one kind of Bph/bph allele was not enough information to guest plant resistance to BPH. Satoto et al. (2008) reported that pyramiding analysis is needed as resistance to BPH is controlled by many genes. Su et al. (2006) said that not all Bph/bph allele markers can be used as MAS. Bogadhi et al. (2015) found more than one BPH resistance genes in each resistant genotype.

Microarray analysis showed that BPH resistance in Rathu Heenati (donor of Bph17 gene) may be controlled by a series of resistance-related genes (Wang et al. 2012).Based on this research result, the presence of Bph17 allele in Indonesian landraces and new-improved varieties does not merely show plant resistance to BPH. Association of Bph17 alleles in landraces and new-improved varieties

of rice does not constantly express resistance to BPH. Landraces and varieties resistant to BPH in this study had different resistance genes to those of Rathu Heenati. So that, RM5953-129bp and RM8213-177bp cannot be used for analyzing rice varieties resistant to BPH of biotype 3. The presence of these markers had no correlation with resistance trait on new-improved rice varieties, i.e. Inpari 34, Inpari 35, Inpari 36, Inpari 37 and Inpari 38. Therefore, it is necessary to search for new genes that control the resistance trait to BPH in landraces or varieties originated from Indonesia.

CONCLUSION

The association of Bph17 alleles in landraces and new-improved varieties of rice resistant to brown planthopper was very low (r = -0.119 and -0.023, respectively). The presence of Bph17 allele does not constantly express resistance to brown planthopper. The study suggests that Bph17 allele cannot be used as a tool of MAS for evaluating resistance of Indonesian landraces and new-improved varieties of rice to BPH. Further research is needed to obtain a specific gene marker that can be used as MAS and applicable for differential rice varieties from Indonesia.

ACKNOWLEDGEMENT

This research was financially supported by the Indonesian Center for Rice Research, Indonesian Agency for Agricultural Research and Development.

REFERENCES

Baehaki, S.E. (2012) Perkembangan biotipe hama wereng coklat pada tanaman padi. Iptek tanaman Pangan. 7 (1), 8–17.

Baehaki, S.E. & Mejaya, I, M.J. (2014) Wereng cokelat sebagai hama global bernilai ekonomi tinggi dan strategi pengendaliannya. Iptek Tanaman Pangan. [Online] 9 (1), 1–12. Available from: http://pangan.litbang.pertanian.go.id/files/01-Iptek012014-Baehaki.pdf.

Baehaki & Widiarta, I.N. (2009) Hama wereng dan cara pengendaliannya pada tanaman padi. Aan Darajat et al. (eds.) Padi Inovasi Teknologi Produksi. Buku 2. Jakarta, LIPI Press, pp.347–383.

Bahagiawati (2012) Kontribusi teknologi marka molekuler dalam pengendalian wereng coklat. Pengembangan Inovasi Pertanian. 5 (1), 1–18.

Bhogadhi, S.C. & Bentur, J.S. (2015) Screening of rice genotypes for resistance to brown plant hopper biotype 4 and detection of BPH resistance genes. International Journal of Live Science Biotechnology and Pharma Research. 4 (2), 90–95.

Brar, D.S., Virk, P.S., Jena, K.K. & Khush, G.S. (2009) Breeding for resistance to planthoppers in rice. In: Heong KL, H.B. (ed.) Planthoppers: new threats to the sustainability of intensive rice production systems in Asia. Los Banos, International Rice Research Institute, pp.401–428.


Carsono, N., Prayoga, G.I., Rostini, N. & Dono, D. (2016) Seleksi berbasis marka molekuler pada padi generasi F2 guna merakit galur padi harapan tahan wereng coklat. Jurnal Agrikultura. 27 (1), 9–15.

Direktorat Perlindungan Tanaman Pangan (2016) LAKIN 2015: Laporan Kinerja Perlindungan Tanaman Pangan 2015. Jakarta.

Francia, E., Tacconi, G., Crosatti, C., Barabaschi, D., Bulgarelli, D., Dall’Aglio, E. & Valè, G. (2005) Marker assisted selection in crop plants. Plant Cell, Tissue and Organ Culture. [Online] 82 (3), 317–342. Available from: doi:10.1007/s11240-005-2387-z.

Iswanto, E.H., Susanto, U. & Jamil, A. (2015) Perkembangan dan tantangan perakitan varietas tahan dalam pengendalian wereng coklat di Indonesia. Journal Penelitian dan Pengembangan Pertanian 34 (4), 187–193.

Jamil, A., Satoto, Sasmita, P., Guswara, A. & Suharna (2016) Deskripsi varietas unggul baru padi. Jakarta, Badan Penelitian dan Pengembangan Pertanian.

Jena, K.K., Jeung, J.U., Lee, J.H., Choi, H.C. & Brar, D.S. (2006) High-resolution mapping of a new brown planthopper (BPH) resistance gene, Bph18(t), and marker-assisted selection for BPH resistance in rice (Oryza sativa L.). Theoretical and Applied Genetics. [Online] 112 (2), 288–297. Available from: doi:10.1007/s00122-005-0127-8.

Liu, G., Yan, H., Fu, Q., Qian, Q., Zhang, Z., Zhai, W. & Zhu, L. (2001) Mapping of a new gene for brown planthopper resistance in cultivated rice introgressed from Oryza eichingeri. Chinese Science Bulletin. [Online] 46 (17), 1459–1462. Available from: doi:10.1007/BF03187031.

Liu, Y., Su, C., Jiang, L., He, J.U.N., Wu, H.A.N. & Peng, C. (2009) The distribution and identification of brown planthopper resistance genes in rice. Hereditas. [Online] 73, 67–73. Available from: doi:10.1111/j.1601-5223.2009.02088.x.

Pertiwi, W., Carsono, N. & Amien, S. (2014) Seleksi berbasis marka SSR untuk karakter ketahanan terhadap wereng coklat dan pengamatan fenotipik untuk daya hasil tinggi pada padi F 2. Agricultural Science Journal I (4), 275–285.

Prashant, Shivshankar, T., Chandrashekharaiah, Naveena, N.L. & Mallikarjun (2012) Incidence of brown planthopper (BPH) Nilaparvata lugens Stal. (Delphacidae : Hemiptera) in relation to age of the rice crop. International Journal of Agricultural Science. 3 (3), 197–200.

Rahman, M.L., Jiang, W., Chu, S.H., Qiao, Y., Ham, T.H., Woo, M.O., Lee, J., Khanam, M.S., Chin, J.H., Jeung, J.U., Brar, D.S., Jena, K.K. & Koh, H.J. (2009) High-resolution mapping of two rice brown planthopper resistance genes, Bph20(t) and Bph21(t), originating from Oryza minuta. Theoretical and Applied Genetics. [Online] 119 (7), 1237–1246. Available from: doi:10.1007/s00122-009-1125-z.

Sai, H., Sai, K., Padma, B., Richa, S., Ayyapa, D. & Vinay, S. (2013) Evaluation of rice genotypes for brown planthopper (BPH) resistance

using molecular markers and phenotypic methods. African Journal of Biotechnology. [Online] 12 (19), 2515–2525. Available from: doi:10.5897/AJB2013.11980.

Satoto, Sulistyowati, Y., Hartana, A. & Slamet-Loedin, I.H. (2008) The segregation pattern of insect resistance genes in the progenies and crosses of transgenic Rojolele rice. Indonesian Journal of Agricultural Science. 9 (2), 35–43.

Sitaresmi, T., Wening, R.H., Rakhmi, A.T., Yunani, N. & Susanto, U. (2013) Pemanfaatan plasma nutfah padi varietas lokal dalam perakitan varietas unggul. Iptek Tanaman Pangan. 8 (1), 22–30.

Sonnino, A., Carena, M.J., Guimarães, E.P., Baumung, R., Pilling, D. & Rischkowsky, B. (2007) An assessment of the use of molecular markers in developing countries.In: Guimarães, et.al. (ed.) Marker-assisted selection: Current status and future perspectives in crops, livestock, forestry and fis. Rome, Food and Agriculture Organization of the United Nations, pp.15–26.

Su, C. C., Zhai, H. Q., Wang, C. M., Sun, L. H. & Wan, J. M. (2006) SSR mapping of brown planthopper resistance gene Bph9 in Kaharamana, an indica rice (Oryza sativa L.). Acta Genetica Sinica. [Online] 33 (8), 717–723. Available from: doi:10.1016/S0379-4172(06)60104-2.

Sun, L. H., Wang, C. M., Su, C. C., Liu, Y. Q., Zhai, H. Q. & Wan, J. M. (2006) Mapping and marker-assisted selection of a brown planthopper resistance gene bph2 in rice (Oryza sativa L.). Acta Genetica Sinica. [Online] 33 (8), 717–723. Available from: doi:10.1016/S0379-4172(06)60104-2.

Sun, L.H., Su, C.C., Wang, C.M., Zhai, H.Q. & Wan, J.M. (2005) Mapping of a major resistance gene to the brown planthopper in the rice cultivar Rathu Heenati. Breeding Science. 55 (4), 391–396.

Wang, Y., Li, H., Si, Y., Zhang, H., Guo, H. & Miao, X. (2012) Microarray analysis of broad-spectrum resistance derived from an indica cultivar Rathu Heenati. Planta. [Online] 235 (4), 829–840. Available from: doi:10.1007/s00425-011-1546-1.

Wang, Y., Wang, X., Yuan, H., Chen, R., Zhu, L., He, R. & He, G. (2008) Responses of two contrasting genotypes of rice to brown planthopper. Molecular Plant-Microbe Interactions : MPMI. [Online] 21 (1), 122–132. Available from: doi:10.1094/MPMI-21-1-0122.

Watanabe, T., Matsumura, M. & Otuka, A. (2009) Recent occurrences of long-distance migratory planthoppers and factors causing outbreaks in Japan. In: Heong KL, H.B. (ed.) Planthoppers: new threats to the sustainability of intensive rice production systems in Asia. Los Banos, International Rice Research Institute, pp.179–190.

Yunani, N., Wening, R.H., Pramudika, E. & Maryati, E. (2014) Katalog Plasma Nutfah Padi. Sukamandi, Balai Besar Penelitian Tanaman Padi.



PHENOTYPIC PERFORMANCE OF CIHERANG SUB1 NEAR ISOGENIC LINE AS AN ADAPTIVE VARIETY FOR FLOODING CONDITIONS

Penampilan Fenotipik Galur Isogenik Ciherang Sub1 sebagai Varietas Tahan Genangan

Yudhistira Nugrahaa*, Nurul Hidayatunb, Trisnaningsiha, Dini Yuliania, Shinta Ardiyantia and Triny Suryani Kadira

aIndonesian Center for Rice ResearchJalan Raya No. 9 Sukamandi, Subang 41256, West Java, Indonesia

bIndonesian Center for Agricultural Biotechnology and Genetic Resource Research and DevelopmentJalan Tentara Pelajar No 3A, Bogor 16111, West Java, Indonesia

*Corresponding author: [email protected]

Submitted 21 May 2016; Revised 3 April 2017; Accepted 10 April 2017

ABSTRACT

Marker assisted back crossing (MABC) is a molecular tool that can help breeders in reducing backcrossed generation. However, effectiveness of this method still needs further approval using actual phenotypic performances. The International Rice Research Institute had developed Ciherang near isogenic line (NIL) of submergence tolerance, Sub1. The study aimed to evaluate phenotypic performances of Ciherang Sub1 NIL in the greenhouse and field conditions. The study was conducted in ten locations using five submergence-tolerant varieties and a control treatment under normal conditions. The results showed that the average grain yields and some agronomic traits of Ciherang Sub1 were not significantly different compared with those of Ciherang (recurrent parent). However, under 10- and 15-days of submergence. Ciherang Sub1 was significantly different to Ciherang. The survival rate of Ciherang Sub1 was higher than Ciherang after 14-days submerged in the greenhouse tank experiment. Response of Ciherang Sub1 to brown planthopper biotype 1, 2 and 3, Xanthomonas oryzae pathotype III, IV and VIII, and rice tungro virus inocula from Subang, Magelang and Lanrang were also comparable with its recurrent parent. Quality and physico-chemical properties of rice (milled rice) of Ciherang Sub1 were not different with those of Ciherang. Similarity level of phenotypic traits of Ciherang Sub1 compared to Ciherang was more than 87.5%. This finding proved that a single backcross method can produce progeny identic with its parent. This MABC line can be recommended to farmers in flood-prone area where the Ciherang is preferred.

[Key words: Ciherang Sub1, Euclidean, grain yield, near isogenic lines, rice, submergence]

ABSTRAK

Marker assisted back crossing (MABC) merupakan teknik molekuler yang dapat membantu pemulia dalam mengurangi generasi yang dibutuhkan dalam pemuliaan silang balik. Namun, efektivitas metode tersebut masih perlu dibuktikan melalui kinerja fenotipe yang sesungguhnya. International Rice Research Institute (IRRI) telah merakit varietas padi toleran rendaman menggunakan metode MABC dengan latar belakang genetik varietas padi yang populer

di Indonesia, yakni Ciherang. Penelitian ini bertujuan untuk mengevaluasi penampilan fenotipe galur isogenik Ciherang Sub1 di rumah kaca dan di lapangan. Uji daya hasil pada kondisi normal di 10 lokasi menggunakan lima varietas toleran rendaman dan satu varietas pembanding. Hasil penelitian menunjukkan rata-rata hasil dan sejumlah karakter agronomi tidak berbeda nyata. Namun, uji rendaman di lapangan selama 10 dan 15 hari menunjukkan Ciherang Sub1 berbeda nyata dengan Ciherang. Demikian pula pada pengujian di rumah kaca pada fase bibit selama 14 hari rendaman, Ciherang Sub1 memiliki persentase bibit hidup lebih tinggi dibandingkan dengan Ciherang. Respons Ciherang Sub1 terhadap cekaman biotik seperti wereng cokelat biotipe 1, 2, dan 3; Xanthomonas oryzae patotipe III, IV dan VIII; dan inokulum virus tungro dari Subang, Magelang dan Lanrang sama dengan tetuanya, yakni Ciherang. Penampilan kualitas fisik dan kimia beras Ciherang Sub1 juga sama dengan Ciherang. Kesamaan fenotipe antara Ciherang Sub1 dan Ciherang lebih dari 87,5%. Hasil penelitian ini menunjukkan bahwa silang balik gen target yang dilakukan satu kali dapat menghasilkan galur yang identik dengan tetuanya. Galur ini dapat direkomendasikan untuk ditanam di lahan yang bermasalah dengan banjir dan petaninya menyukai varietas Ciherang.

[Kata Kunci: Ciherang Sub1, Euclidean, hasil gabah, galur isogenik, padi, rendaman]

INTRODUCTION

Recent advances in rice genomic research and completion of the rice genome sequence have made it possible to identify and map precisely several genes through linkage to DNA markers (Jena and Mackill 2008). Furthermore, the use of cost-effective DNA markers derived from the fine mapped position of the genes for important agronomic traits will provide opportunities for breeders to develop high-yielding, stress-resistant, and better-quality rice cultivars. DNA marker as a tool for selection was initially used for confirming the targeted gene in selected individual in pedigree or bulk population hence it is called as a marker assisted selection (MAS). Its


usage had been expanded to back crossing selection, and it is termed as a marker assisted back crossing (MABC) (Collard and Mackill 2008). MABC may reduce the back cross generation, if the targeted gene and the genetic background of the recipient parent could be identified correctly. The recovery degree of the recurrent parent, however, may be offset by the smaller number of selected plants during the process of applying MABC.

Swarna-Sub1 and IR64-Sub1 were the first submergence-tolerant rice varieties developed using MABC approach in IRRI. Those two varieties performed similar agronomic traits, such as grain yield and grain quality with their recurrent parent (Singh et al. 2009). Further, those varieties showed higher grain yield advantage over their recurrent parent under submergence for 10 days or more during the vegetative stage (Sarkar et al. 2006; Neeraja et al. 2007; Septiningsih et al. 2009; Nugraha et al. 2013a). This indicated that there was a complete restoration of the recurrent parent genetic background. Those two varieties have been introduced in Indonesia and released as Inpara 4 and Inpara 5 in 2010 (Suprihatno et al. 2012) and the seed has been distributed to farmers in the flood-prone areas in Java and Sumatra (Ismail et al. 2013). However, result of a study in the flood-prone area of northern coast of West Java showed that the submergence-tolerant varieties were not adopted by farmers due to undesirable grain quality and susceptibility to pests and diseases (Manzanilla et al. 2011). Farmers preferred to plant submergence-sensitive variety, Ciherang, despite having to face a risk of devastated flooding during the wet season. Ciherang is not only preffered by farmers in this area but also occupies more than 45% of total rice planted area in Indonesia (Ruskandar 2010). It is important, therefore, to develop Ciherang-submergence tolerant variety to minimize crop losses due to unexpected inundation during rice growth and to accelerate its adoption by farmers who already familiar with Ciherang variety.

In the case of development of Ciherang Sub1, the SUB1 donor used in MABC was IR64 Sub1, the ancestor of Ciherang (IR64) which also has SUB1 (Ismail et al. 2013). This slightly close related genomic distance allows to apply ‘one back cross strategy’ by introgressing a major QTL/gene, such as Sub1, in a relatively short time, i.e. three seasons (Frisch and Melchinger 2001; Frisch and Melchinger 2005). The conventional breeding method requires 5–6 back cross generations to transfer more than 90% of recurrent parent genetic background (Vogel 2009). The MABC method facilitated the acceleration of releasing varieties within 1–1.5 years, depending on whether two or three generations of rice planting could be performed within a year.

IR09F436 (Ciherang Sub 1) was selected from F2BC2 generation which was developed using SC3 and ART5 marker for SUB1 locus (foreground selection) and 48 SSR markers for genetic background of the Ciherang genome (Septiningsih et al. 2014). Since the process had fewer polymorphic markers due to close relatedness of donor and recurrent parents, it successfully completes the conversion at the BC1F2 stages. This is faster than the standard BC3F2 usually employed, like the development of IR64 Sub1 and Swarna Sub1 (Septiningsih et al. 2009). After accomplishment of breeding process, the seed of Ciherang Sub1 was introduced in Indonesia in 2011. However, this breeding material requires field and greenhouse trials to test its phenotypic performances and similarity to its recurrent parent, Ciherang. The study result will also be able to confirm the effectiveness of a shorter process of backcrossing strategy in developing a new rice variety using MABC method. The objectives of this study were to evaluate the phenotypic performances of Ciherang Sub1 NIL in the greenhouse and field conditions. In this present study, we compared Ciherang Sub1 on the advanced yield trial in some locations with its recurrent parent, Ciherang. We observed the grain yield and agronomic characters, their response to major pest and diseases, and their grain/cooking quality.


Multi-Location Yield Trials

The experiments to evaluate yield potential and agronomic traits were carried out in the wet season of 2010/2011 and in the dry season of 2011 (Table 1) in ten locations representing rice production center with different soil types and elevations. Six rice genotypes consisted of five submergence-tolerant genotypes (Ciherang Sub1, PSBRc82 Sub1, Inpara 3, Inpara 5 and B13138-MR-2-7), and a sensitive-check variety, Ciherang, were evaluated. In each location, a randomized complete block design was used with three replications. Plot size was 4 m x 5 m and plant spacing was 25 cm x 25 cm, one plant per hill. Seeds were sown in the seedling bed for 21 days and then transplanted to the field. Nitrogen, phosphorus, potash and zinc nutrients were applied at a rate of 90:30:30:5 kg.ha-1 as basal fertilizers. Second and third applications of nitrogen were conducted at 40 days after transplanting (DAT) and 60 DAT, respectively. Crop management followed the standard rice cultural practices. Grain yield was measured at maturity from 10 m2 subplots, with area under the missing hills was subtracted from harvest area. The yield was adjusted to a moisture content of 14% fresh weight and converted to t.ha-1.

9Phenotypic performance of ciherang … (Yudhistira Nugraha, et al.)

Submergence Trial in the Field

The experiments to evaluate the response of rice genotypes under submerged conditions were carried out at Sukamandi Experimental Station of the Indonesian Center for Rice Research (ICRR) during the wet season of 2010/2011. The same genotypes as those tested in the grain yield trials were evaluated for submergence tolerance. The six genotypes were tested using a randomized complete block design, in three replicates. Plot size was 1 m x 5 m, plant spacing was 25 cm x 25 cm, one seedling per hill. Three ponds of 1000 m2

area, 1.5 m depth and surrounded with concrete cement in each side were used. The three ponds were set up for application of different submergences, e.i. (1) complete submergence for 5 days, (2) complete submergence for 10 days, and (3) complete submergence for 15 days. Crop management followed the standard rice cultural practices.

The submergence treatment was started at 14 days after transplanting. Irrigation was applied from noon to allow sufficient time for rice to accumulate carbohydrate through photosynthesis in the morning. Desired water depth was maintained at 1.2 m by adding water regularly in the ponds. Algae were minimized by removing from the water surface using small fish nets.

Data were collected for nondestructive samples, such as percentage of survival, days to flowering and plant height. The yield attributes were determined by random sampling of 10 hills from each plot. Panicles were hand-threshed and the filled and unfilled spikelets were separated after drying under the sun. The subsamples were then oven-dried at 70o C till constant weights to determine 1000-grain weight and spikelet number per panicle. Grain yield was measured at maturity from 1 m2 subplots, with area under the missing hills was subtracted from harvest area. The yield was then adjusted to a moisture content of 14% fresh weight and converted to t.ha-1.

Submergence Trial in the Greenhouse

Submergence trial in the greenhouse was carried out in the dry season of 2011 in Muara Experimental Station of ICRR. The submergence test followed the direct seeded method (Mazerado,A.M. and Vergara B.S.(1982)). The seeds of the same genotypes with the first experiment were sown in 12 cm x 24 cm x 30 cm trays filled with soil. Each genotype had one row followed the tolerant check, FR13A and sensitive check, IR42 in four replicates. At the 14-day-old seedlings the trays were transferred to the tank filled with water of 1 m depth. The water was maintained at desired depth by adding water regularly. After 14-day submergence, the water was removed. The shoot elongation was measured after the water was receded and compared with the genotypic measurements before submergence treatments. Survival rate was observed at seven days allowing plant to recover. The survival rate was determined by counting the ratio of survived plants after submerged to total plants used before submergence treatment.

Evaluation of Resistance to Pest and Disease

Ciherang and Ciherang Sub1 were used for evaluation of their resistance to biotic stress in the greenhouse experiment. Brown planthopper (BPH) test was carried out at Sukamandi Experimental Station of ICRR. Three BPH biotypes (biotype 1, 2 and 3) were bred in different varieties TN-1, IR26 and IR42, respectively following the method developed by Panda et al. (1982). Twenty five seedlings per genotype were planted in 200 cm x 75 cm x 20 cm wood box. Infestation used eight instars per seedling. Scoring was made when the different varieties died by following the Standard Evaluation System for Rice, SES (IRRI 2002).

Resistance to bacterial leaf blight was studied at the booting stage (50 days after planting) using three cell

Table 1. Characteristics of locations used for advanced yield trial of submergence-tolerant rice line.

Location Season Coordinate pointElevation above

sea level(m)

Soil type

Kesugihan-2, Cilacap WS 2010/2011 S 7° 19’ 45.98” E 108° 43’ 35.54” 16 AlluvialTanjung Lubuk, OKI WS 2010/2011 S 3° 33’ 45.23” E 104° 47’ 32.65” 15 OrganosolKayu Agung, Palembang WS 2010/2011 S 3° 28’ 59.75” E 104° 48’ 14.68” 11 OrganosolSolokanjeruk, Bandung WS 2010/2011 S 7° 01’ 039” E 107° 43’ 965” 687 AndosolCimalaka, Sumedang WS 2010/2011 S 6° 49’ 759” E 107° 58’ 676” 419 RegosolJatitujuh, Majalengka WS 2010/2011 S 6° 38’ 59.80” E 108° 13’ 35.36” 23 LatosolSukamandi, Subang WS 2010/2011 S 6° 21’ 02.07” E 107° 39’ 04.52” 14 AluvialCilamaya, Karawang DS 2011 S 6° 20’ 17.36” E 107° 33’ 09.85” 22 AluvialAnjatan, Indramayu DS 2011 S 6° 18’ 20” E 107° 56’ 10” 10 AluvialKesugihan-1, Cilacap DS 2011 S 7° 19’ 45.98” E 108° 43’ 5.54” 16 Aluvial

WS = wet season; DS = dry season


suspensions of Xanthomonas oryzae pv. oryzae (Xoo) pathotype III, IV and VIII at a concentration of 108 cells.ml-1. The rice genotypes were planted in the field at 20 cm x 20 cm plant spacing, 20 hills per row. The tolerant checks IRBB5 and IRBB7 and susceptible checks IR64 and TN1 were included. Inoculation was done by cutting the leaves at 5 cm from the tips. Disease severity was observed by measuring the length of symptoms at 15 days after inoculation (DAI). Disease severity was determined by counting the ratio between the length of symptoms to the length of leaves inoculated based on SES IRRI for rice (IRRI 2002).

Resistance to rice tungro virus was evaluated following the International Rice Tungro Nursery (IRTN). Seedlings were planted in a row in the 70 cm x 30 cm x 30 cm plastic box. Tukad Petanu (resistant check) and TN1 (susceptible check) were planted in every 10 rows. Tungro viruses were tested by feeding acquisition of Nepothettix virescens to tungro inocula from Subang, Lanrang and Magelang for 24 hours. The viruliferous N. virencens were then released to the ten-day old seedlings for 24 hours to inoculate tungro virus. The test plants were observed and determined the scale of symptom severity at 14 days after inoculation based on SES for Rice (IRRI 2002).

Evaluation of Physical and Chemical Quality of Rice

Physical and chemical characteristics of Ciherang and Ciherang Sub1 milled rice were evaluated in the post-harvest laboratory of ICRR using the method developed by Juliano (2003). The physical characteristics consisted of grain width and length, degree of whiteness, clearness, chalkiness, milling recovery, and head rice recovery. Meanwhile the chemical characteristics consisted of amylose content, gelatinization temperature, alkali value and gel consistency.

Statistical Analysis

The data resulted from this study were tabulated and computed using Microsoft EXCEL 2007© software. Comparisons among genotypes were analyzed using a least significant difference with SAS 9.0© (SAS Institute Inc 2009). Morphological and agronomic characters, reaction to pest and disease, and physical-chemical quality of the grain were used to analyze the genetic divergence among genotypes. Multivariate analysis was applied to study the similarity level among genotypes tested. The parameters used for analyzing the similarity were plant height, tiller number, flowering date, grain

number, filled grain number, fertility, 1000-grain weight, grain yield, reaction to brown planthopper, bacterial leaf blight, and tungro virus, and physical-chemical characteristics of milled rice consisted of grain width and length, whiteness, clearness, chalkiness, milling recovery, head rice recovery, amylose content, gelatinization temperature, alkali value and gel consistency. All parameters were counted for all possible pairwise comparisons between genotypes. Matrices of Euclidean similarity coefficients based on morphological data set were analyzed using Mini Tab V.5 (Minitab Inc. 2010).


Grain Yield under Normal Conditions

Grain yields among genotypes in all locations were significantly different, except for Majalengka. The effects of interaction between genotypes and environment on grain yield were also statistically significant, indicating that there was a high variation of genotype responses to different environmental conditions (Table 2). The average grain yield in ten locations for Ciherang Sub1 (6.18 t.ha-1) was not significantly different from that of Ciherang (5.89 t.ha-1). Genes that control grain yield are polygenic and affected by environment, therefore the grain yield genes of Ciherang might have been well recovered in the Ciherang Sub1. This was also confirmed by the performances of agronomic traits of Ciherang Sub1 tested in ten locations which were not significantly different from those of Ciherang (Table 3).

Grain yields of Ciherang and Ciherang Sub1 were not significantly different, but average grain yield of Ciherang Sub1 was slightly higher than that of Ciherang at seven out of ten locations. A similar phenomenon was reported by Singh et al. (2009) and Nugraha et al. (2013a) where Swarna Sub1 and IR64 Sub1 were insignificantly different with its parent under normal conditions. It had been reported that introgression of SUB1 gene resulted additional effects that the SUB1 lines demonstrated more tolerant to drought (Fukao and Xiong 2013) and to shading (Fukao et al. 2012). The SUB1 locus confers submergence tolerance in rice and the SUB1 was classified as a family gene called an ethylene response factor (ERF) like gene (Xu et al. 2006). The SUB1 genes are members of group VII in the ERF gene family (Nakano 2006) and are more closely related than any other rice ERF genes (Gutterson and Reuber 2004). The gene regulates ethylene, a common phyto-hormone produced by plant in stress conditions (Fukao et al. 2011). This result confirmed that introduction of SUB1 locus into rice varieties gave beneficial effect,


Table 2. Grain yields of five rice genotypes tested in ten locations for advanced yield trial.

GenotypesGrain yield (t.ha-1)

1 2 3 4 5 6 7 8 9 10 MeansCiherang Sub1 6.16 4.27 6.96 3.72 8.41 6.61 4.64 5.95 7.88 8.28 6.29Ciherang 5.39 4.01 7.16 3.05 8.30 6.65 4.97 5.40 7.81 8.15 6.09PSBRC82-SUB1 5.42 4.14 5.99 3.07 7.95 5.90 4.72 5.27 6.86 7.44 5.68B13138-7-MR-2 4.60 4.07 6.52 2.81 8.34 6.00 4.62 5.93 7.51 7.77 5.82Inpara 3 4.18 4.23 5.58 2.77 6.34 6.45 3.71 5.04 7.14 7.78 5.32Inpara 5 4.94 2.97 7.95 3.13 7.66 5.95 4.83 4.90 6.19 6.84 5.54Means 5.11 3.95 6.69 3.09 7.83 6.26 4.58 5.42 7.23 7.71 5.79G 2.63Rep (Loc) 0.37Loc 10.8G x Loc 3.58CV (%) 5.69LSD (0.05) 0.51

Notes: 1 = Cilacap 1; 2 = Karang Ampel, Indramayu; 3 = Tanjung Lubuk, Ogan Komering Ilir; 4 = Kayu Agung; 5 = Bandung; 6 = Sumedang; 7 = Majalengka; 8 = Sukamandi; 9 = Cilacap 2; 10 = Karawang.*) Significantly different at 5% level. G = Genotypes, Loc = Location, Rep = Replication.

Table 3. Yield components and agronomic data of Ciherang Sub1, Ciherang and other Sub1 varieties under control conditions in ten different sites in Indonesia under normal conditions.

GenotypesYield component

PH TN DF FG FR UFG 1000-WCiherang-Sub1 101.7 16 79 110 82 24 26.7Ciherang 100.3 16 77 105 81 21 26.7PSBRC-SUB1 95.3 18 78 96 82 22 26.0B13138-7-MR-2-KA 105.0 15 80 106 78 33 25.6Inpara3 100.8 15 80 102 78 26 25.6Inpara5 (IR64 Sub1) 94.2 19 75 92 81 18 26.0G ** ** ** ns ns * **Rep (L) ** ns ns ns ns ns **L ** ** ** ** ** ** **G x L ** ** ** ** ** ** **Means 99.5 17 78 102 80 24 26.1CV (%) 4.4 13.2 1.8 11.6 6.4 4.9 4.4LSD 0.05 1.7 0.8 0.5 4.8 1.8 0.4 1.7Data were collected from ten different sites in Indonesia, with four replications in each site: Cilacap in Central Java (2010 WS and 2011 DS); Indramayu, Bandung, Sumedang, Majalengka, Sukamandi, Karawang in West Java; Tanjung Lubuk and Kayu Agung, Ogan Komering Ilir in South Sumatra in 2011 DS.GY = grain yield, PH = plant height, TN = productive tiller number, DF = number of days to 50% flowering, FG = number of filled grains, FR = fertility, UFG = number of unfilled grains, 1,000-W = 1,000 grain weight.** and * Significantly different at 0.05 and 0.01 level, respectively; ns = not significantly different.

not only improving plant tolerance to submergence but also to other abiotic stress that might appear during the experiment in the field resulting in the increasing grain yield under normal conditions.

Genotypic Performance under Submergence Conditions

Ciherang Sub1 and Ciherang along with the two other checks were also planted at Sukamandi Experimental Station of ICRR during the dry season of 2011 under

5-d, 10-d and 15-d submergence. Plant survivals among all genotypes were not significantly different under 5-d submergence (Figure 1). Variations of plant survivals were observed under 10-d and 15-d submergence treatments, where the tolerant varieties survived better compared to Ciherang. The survival rate of Ciherang was 60% when submerged for 10 days, while Ciherang Sub1 could maintain its survival at 88%. The survival rate under 15-d submergence for Ciherang was 40%, while that of Ciherang Sub1 was 75%. Although the survival rates of Ciherang and Ciherang Sub1 decreased


under 15-d submergence, Ciherang Sub1 containing SUB1 gene survived better than Ciherang.

Plant survival affected grain yield only under severe submergence for 15 days. Submergence treatment for 5 days resulted insignificant effect compared to normal condition on plant survival and grain yield. Submergence for 10 days decreased grain yield of Ciherang to 3.9 t.ha-1 compared to that at normal conditions in Sukamandi (Table 2), but its grain yield was not significantly different to that of tolerant varieties (Table 4). This was attributed to the survival plants resulting more tillers to compensate spacious population due to some plants died during submergence as revealed by Ciherang producing 18 and 20 tillers under 10-d and 15-d submergence, respectively. However, under severe submergence for 15 days, genotypes revealed significant differences in grain yields, where Ciherang yielded only 2.0 t.ha-1 while Ciherang Sub1 produced grains almost double to 3.9 t.ha-1 followed other submergence-tolerant variety, Inpara 5. Reduction in grain yield under submerged conditions was attributed to the degree of plant injury, which was dependent on the level of submergence tolerance.

The result of greenhouse experiments confirmed the results in the field trials where Ciherang Sub1 survived

100%, while Ciherang survived only 60% under 14-d submergence treatment (Table 5). Survival of Ciherang Sub1 was also comparable to that of source gene of SUB1A-1, FR13A and other submergence-tolerant varieties (Figure 2). In the water tank experiment, Ciherang demonstrated slightly better survival rate than the sensitive check IR42. This result was also confirmed by the submergence field experiments demonstrating moderate tolerance (50% survival rate) of Ciherang under 10-d submergence treatment (Figure 1).

The SUB1 gene was reported encoding two or three ethylene-responsive factors, namely SUB1A, SUB1B and SUB1C. The SUB1A was subsequently identified as the major determinant for submergence tolerance, while SUB1B and SUB1C alleles did not show important roles in plant tolerance to submergence (Xu et al. 2006). Recent study reported that submergence-tolerant rice accessions possess the SUB1A-1 allele, whereas accessions that contain less highly expressed SUB1A-2 allele are submergence intolerant (Septiningsih et al. 2009). The slightly better survival rate of Ciherang than that of the sensitive check was probably because the genotypes had one of the three alleles of the SUB1 locus and expressed SUB1A-2 allele with small effect as it did in IR64, while

Fig. 1. Survival of some rice genotypes under 5, 10 and 15 days submergence in Sukamandi, wet season of 2010/2011. Error bar is standard error of the means of three replications.

100

90

70

80

40

50

60

10

20

30

0

Survival (%)

5 10 15

Ciherang-Sub 1

Ciherang

PSBRC82-SUB 1

B13138-7-MR-2

Inpara 3Inpara 5

Submergence period (days)


Table 4. Agronomic data and grain yield of Ciherang Sub1, Ciherang and other Sub1 varieties under 5-days submergence (5-d), 10-days submergence (10-d) and 15-days submergence (15-d) of field plot, in Sukamandi in 2011 dry season.

GenotypesPlant height (cm)

Tiller number (pieces)

Days to 50 % flower-ing (day)

Grain yield (t.ha-1)

5-d 10-d 15-d 5-d 10-d 15-d 5-d 10-d 15-d 5-d 10-d 15-d

Ciherang-Sub1 97 99 98 17 17 14 74 77 81 5.6 4.2 3.9Ciherang 96 98 95 16 18 20 74 76 89 5.2 3.9 2.0PSBRC-SUB1 97 99 91 17 17 14 75 72 79 5.1 3.5 3.1B13138-7-MR-2-KA-1 106 106 101 13 13 13 73 76 80 5.5 3.9 3.2Inpara 3 106 106 105 14 14 12 74 78 81 4.5 4.4 2.8

Inpara 5 (IR64 Sub1) 91 91 84 17 17 14 69 71 76 5.0 3.8 4.1CV (%) 3.4 3.4 5.1 12.6 12.6 6.2 1.8 1.8 1.6 6.7 4.9 13.4LSD 4.8 4.9 6.9 2.8 2.8 1.2 1.9 1.9 1.9 0.5 0.3 0.6

Ciherang Sub1

PSBRC82 Sub1

IR42Sensitivecheck

Ciherang Sensitive

B13138-7

Inpara5 FR13A Tolerant

Fig. 2. High seedling recovery and less elongation of Ciherang Sub1 (foremost left) after 14 days submerged in greenhouse trays, similar with Sub1 locus donor FR13A (foremost right) (A). High survival of Ciherang Sub1 after 15 days submerged in the field compared to its recurrent parent, Ciherang (B).

A

Ciherang Sub1

Ciherang

B

Table 5. Shoot length of rice genotypes as affected by 14 days submergence in greenhouse test, Bogor, 2011 dry season.

GenotypesShoot length (cm) Survival

(%)Score1)

Before submerged After submerged Differences

Ciherang Sub I 23.7 ± 2.2 29.4 ± 4.6 5.7 ± 2.4 100 1Ciherang 22.5 ± 2.5 42.8 ± 7.3 20.3 ± 5.2 63 7

PSBRC 82 Sub I 23.1 ± 1.9 30.2 ± 4.3 7.1 ± 2.4 98 3

B13138-7-MR-2-KA-1 21.9 ± 2.5 28.6 ± 3.6 6.7 ± 1.1 100 1Inpara 3 24.2 ± 2.3 34.1 ± 4.9 10.9 ± 2.6 93 5Inpara 5 22.5 ± 1.5 26.3 ± 6.7 3.8 ± 5.2 100 1

IR42 (sensitive check) 23.6 ± 1.4 45.8 ± 10.2 22.2 ± 9.2 10 9

FR13A (tolerant check) 29.4 ± 2.8 35.2 ± 4.5 5.8 ± 1.7 100 11)1 = tolerant; 3 = moderately tolerant; 5 = moderately sensitive; 7 = sensitive; 9 = very sensitive.The data are averages of three replications.


in the pedigree tree of Ciherang, one of its ancestors is IR64 (Suprihatno et al. 2012). The tolerant genotypes showed less shoot elongation compared to those of the sensitive genotypes (Table 5). Ciherang shoot elongation was similar to the sensitive check, IR42, which in turn their shoot length was four-fold higher than that of Ciherang Sub1. Other submergence-tolerant varieties showed less shoot elongation comparable to the tolerant check, FR13A. Under complete submergence, shoot elongation was not necessary for survival indicator which would tend to be lodging after water recede. Shoot elongation consumed more energy and took stored assimilate (Jackson and Ram 2003). The remaining carbohydrate after submergence will presumably be important for growth recovery after de-submergence (Singh et al. 2001; Ram et al. 2002; Nugraha et al. 2013b). Hence, genotypes which have less shoot elongation would recover faster and produce higher yield compared to elongated-type rice varieties during submergence.

Response to Pests and Diseases

Ciherang Sub1 and Ciherang varieties revealed the same response to major pests and diseases tested (Table 6). Both rice genotypes showed moderately susceptible to BPH biotypes 1 and 2, but were susceptible to BPH biotypes 3. The response to bacterial leaf blight (BLB) for both Ciherang and Ciherang Sub1 was moderately resistant to strain III but was moderately susceptible to strain IV and VIII, their response to rice tungro virus was susceptible on three different inoculation experiments. This indicated that there was no effect of the introgression of SUB1 locus into Ciherang variety, with regard to pest and disease reactions.

Grain Quality

Introgression of SUB1 locus to Ciherang variety did not alter the physical and chemical quality of the grain (Table 7). The grain type for both Ciherang Sub1 and Ciherang was long-slender, which met the preference of rice consumers and traders in Indonesia. Other physical grain qualities of both genotypes were also similar. The chemical properties of grain quality which related to the cooking quality of Ciherang Sub1 and Ciherang showed no any apparent differences. This suggests that Ciherang Sub1 would be accepted by farmers and consumers, because its performance is similar to high yielding popular variety, Ciherang.

Similarities Between Ciherang NIL and Its Parents

The genetic distance measured using Euclidean similarities analysis showed that Ciherang Sub1 had close position (95% similarity) with Ciherang (Figure 3). Inpara 5 or IR64 Sub1 which was the ancestor of both varieties were in the third position or had 65.9% similarity. This result indicated that although the process of backcrossing was done only twice, more than 87.5% phenotypic similarity of the parent was present in the offspring. This result also indicated that instead of recovering its parent genetic background, plant performance in the field was also homogenous (Figure 2B). Theoretically, the second backcross generation would be transferred 75% of the recurrent parent genetic background (Hospital 2005). In the process of MABC, from the F1BC1 generation only 2-3 plants were selected

Table 6. Response of Ciherang Sub1 and Ciherang to major pest and diseases.

Pest and diseasesCiherang Sub1 Ciherang

Score Criteria Score Criteria

Brown planthopper Biotype 1 5.0 MS 5.5 MS Biotype 2 5.0 MS 5.5 MS Biotype 3 6.5 S 7.0 S

Bacterial leaf blight Pathotype III 4 MR 3 MR Pathotype IV 6 MS 6 MS Pathotype VIII 5 MS 5 MS

Tungro Subang inoculum 7 S 7 S Lanrang inoculum 7 S 7 S Magelang inoculum 7 S 7 S

MR = moderately resistant; MS = moderately susceptible, S = susceptible.The data are averages of three replications.

Table 7. Grain quality of Ciherang Sub1 and Ciherang.

Grain qualityCiherang Sub1 Ciherang

Score Criteria Score CriteriaPhysical propertiesLength (mm) 7.36 Long 7.40 LongWidth (mm) 2.12 2.20Ratio L/W 3.47 Cylinders 3.36 CylindersWhiteness (%) 33.40 White 33.60 WhiteClearness 1.06 Clear 1.01 ClearMilling recovery (%) 60 61Dehull rice 78.76 78.43Milling rice 70.26 68.34Head rice 95.64 90.15Chalkiness 0.06 Small 0.27 SmallChemical propertiesAmylose (%) 22.40 Medium 23.13 MediumGel consistency (mm) 50 Medium 44 MediumAlkali value (score) 1 1Gelatination (C°) >74 High >74 HighThe data are averages of two replications.


having a homozygote allele of targeted gene from donor parent and all homozygote background alleles from recurrent parent. This process was then continued in the successive generation, F1BC2, to obtain the homozygote targeted locus and homozygotes in all loci of genetic background.

In development of Ciherang Sub1, a set of 285 SSR markers was used to survey polymorphism between the recurrent and donor parents, Ciherang and IR64 Sub1, respectively. However, since the two are closely related (IR64 is one of the parents of Ciherang), only 29 markers were found polymorphic and used for genotyping the population of 48 SSR markers (Hidayatun et al. 2011), which was less than those used in the development of Swarna Sub1 using 200 SSR markers. This was because the donor parent used was IR64 Sub1, which had similarity genetic background to that of Ciherang as confirmed by the genetic Euclidean analysis (Figure 3). This indicated that the backcross process would be accelerated if the donor and the recipient parents were similar. More recently molecular markers tools have been established using high-throughput and low-cost next generation sequencing (NGS) platforms, so that much of the genotyping work can now be easily outsourced in a cost-effective manner. These NGS platforms are being extensively utilized for de novo development of markers and also for genotyping (Edwards and Gupta 2013). In addition, a high throughput genotyping system using single nucleotide polymorphism (SNP) markers has been discovered and has commonly been applied in a number of crop species, including rice (Thomson 2014).

Several Sub1-varieties were previously released in Indonesia, including Inpara 3, Inpara 4 (Swarna-Sub1)

and Inpara 5 (IR64-Sub1). However, the development of Ciherang Sub1 could provide more options for farmers to choose their favorite varieties and minimize crop losses due to unexpected flooding. In 2012, Ciherang Sub1 was officially released in Indonesia and named Inpari 30 Ciherang Sub1 (Ministry of Agriculture of Republic of Indonesia Decree no: 2292.1/KPTs/SR120/6/2012).

CONCLUSION

Morphological performance, agronomic characters, grain yield and yield components of Ciherang and Ciherang Sub1 were similar based on the results of advanced yield trials in ten locations. Introgression of SUB1 locus to the genome of Ciherang variety did not alter the response of the variety to pests and diseases, such as brown planthopper, bacterial leaf blight, and rice tungro virus. There was also no notable changes in physical and chemical grain qualities of Ciherang Sub 1 and its recurrent parent. Ciherang Sub1 demonstrated grain yield advantage compared to that of Ciherang when it was subjected to submergence for 15 days during the vegetative stage. The morphological similarity between Ciherang Sub1 and Ciherang was also confirmed through phenotypic analysis which revealed 87.5% similarity based on similarity analysis.

ACKNOWLEDGEMENT

We thank Dr. David J. Mackill and Dr. Endang Septiningsih for the seeds and allowing Ciherang Sub1 to be tested in Indonesia. The work reported here was supported by the ICRR budget of 2010-2011 fiscal year.

REFERENCES

Collard, B.C.Y. & Mackill, D.J. (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. [Online] 363 (1491), 557–572. Available from: doi:10.1098/rstb.2007.2170.

Frisch, M. & Melchinger, A.E. (2001) Marker-assisted backcrossing for simultaneous introgression of two genes. Crop Science. [Online] 41 (6), 1716–1725. Available from: doi:10.2135/cropsci2001.1716.

Frisch, M. & Melchinger, A.E. (2005) Selection theory for marker assisted backcrossing. Genetics. [Online] 170 (2), 909–917. Available from: doi:10.1534/genetics.104.035451.

Edwards, D & Gupta, P. (2013). Sequence Based DNA Markers and Genotyping for Cereal Genomics and Breeding. pp: 57-76 In: Cereal Genomics II. Elsevier. Amsterdam, ND. [Online] Available from doi:10.1007/978-94-007-6401-9_3

Fukao, T. & Xiong, L. (2013) Genetic mechanisms conferring adaptation to submergence and drought in rice: Simple or complex? Current Opinion in Plant Biology. [Online] 16 (2), 196–204. Available from: doi:10.1016/j.pbi.2013.02.003.

DENDROGRAMSingle Linkage, Euclidean Distance

1 = Ciherang Sub 1; 2 = Ciherang; 3 = PSBRC 82 Sub 1; 4 = B13138-7-MR-2-KA-1; 5 = Inpara 3; 6 = Inpara 5

Fig. 3. Similarity of six rice genotypes based on phenotypic performance of 21 characters of yield, yield components, agronomic characters, pest and disease resistance, and grain quality using Euclidean analysis.

48.98

65.98

82.99

100.001 2 5 4 3 6

Similarity

Observations


Fukao, T., Yeung, E. & Bailey-Serres, J. (2012) The submergence tolerance gene, SUB1A, delays leaf senescence under prolonged darkness through hormonal regulation in rice. Plant Physiology. [Online] 160, 1795–1807. Available from: doi:10.1104/pp.112.207738.

Fukao, T., Yeung, E. & Bailey-Serres, J. (2011) The submergence tolerance regulator SUB1A mediates crosstalk between submergence and drought tolerance in rice. The Plant cell. [Online] 23 (1), 412– 427. Available from: doi:10.1105/tpc.110.080325.

Gutterson, N. & Reuber, T.L. (2004) Regulation of disease resistance pathways by AP2/ERF transcription factors. Current Opinion in Plant Biology. [Online] 7 (4), 465–471. Available from: doi:10.1016/j.pbi.2004.04.007.

Hidayatun N., Alvaro, P., Septiningsih, E.M., & Mackill, D.J. (2011) Pengembangan varietas toleran rendaman ciherang Sub1 melalui pendekatan marker assisted backcrossing (MABC).In: Prosiding Seminar Nasional Padi 2010. Buku 1. Sukamandi, Balai Besar Penelitian Tanaman Padi, pp.109–117.

Hospital, F. (2005) Selection in backcross programmes. Philosophical Transactions of the Royal Society B: Biological Sciences. [Online] 360 (1459), 1503–1511. Available from: doi:10.1098/ rstb.2005.1670.

IRRI (2002) Standard Evaluation System for Rice. Los Banos, International Rice Research Institute.

Ismail, A.M. Singh, U.S., Singh, S., Dar, M.D. & Mackill, D.J. (2013) The contribution of submergence-tolerant (Sub1) rice varieties to food security in flood-prone rainfed lowland areas in Asia. Field Crops Research. [Online] 152, 83–93. Available from: doi:10.1016/j.fcr.2013.01.007.

Jackson, M.B. & Ram, P.C. (2003) Physiological and molecular basis of susceptibility and tolerance of rice plants to complete submergence. Annals of Botany. [Online] 91 (SPEC. ISS. JAN.), pp.227–241. Available from: doi:10.1093/aob/mcf242.

Jena, K.K. & Mackill, D.J. (2008) Molecular markers and their use in marker-assisted selection in rice. Crop Science. [Online] 48 (4), 1266–1276. Available from: doi:10.2135/cropsci2008.02.0082.

Juliano, B. (2003) Rice Chemistry and Quality. [Online] Manila The Phillippines, Phillippines Rice Research Institute. Available from: doi:10.1002.

Manzanilla, D.O. Paris, T.R., Vergara, G.V., Ismail, A.M., Pandeya, S., Labios, R.V., Tatlonghari, G.T., Acdac, R.D., Chi, T.T.N., Duoangsila, K., Siliphouthone, I.,.Manikmas, M.O.A., & Mackill, D.J. (2011) Submergence risks and farmers ’ preferences : Implications for breeding Sub1 rice in Southeast Asia. Agricultural Systems. [Online] 104 (4), 335–347. Available from: doi:10.1016/j.agsy.2010.12.005.

Mazerado, A.M. & Vergara, B.S (1982). Physiological differences in rice varieties tolerant and susceptible to complete submergence. In Proceeding of the International Deepwater Rice Workshop. Manila: International Rice Research Institute 327-341

Minitab Inc. (2010) Minitab, 2010. Minitab Assistant White Paper.USA, Minitab Assistant White Paper.

Nakano, T. (2006) Genome-wide analysis of the ERF gene family in arabidopsis and rice. Plant Physiology. [Online] 140 (2), 411–432. Available from: doi:10.1104/pp.105.073783.

Neeraja, C.N., Maghirang-Rodriguez, R., Pamplona, A., Heuer, S., Collard, B.C.Y., Septiningsih, E.M., Vergara, G., Sanchez, D., Xu, K., Ismail, A.M., & Mackill, D.J. (2007) A marker-assisted backcross approach for developing submergence-tolerant rice cultivars. TAG. Theoretical and Applied Genetics. [Online] 115 (6), 767–776. Available from: doi:10.1007/s00122-007-0607-0.

Nugraha, Y., Vergara, G.V., Mackill, D.J., & Ismail A.M. (2013a) Genetic parameters of some characters and their correlation with rice grain yield in relation to the plant adaptability to semi-deep stagnant flooding condition. Penelitian Pertanian Tanaman Pangan. [Online] 32 (2), 74–82 Available from http://ejurnal.litbang.pertanian.go.id/index.php/jpptp/article/view/2882.

Nugraha, Y., Vergara, G.V., Mackill, D.J., & Ismail A.M (2013b) Response of Sub1 introgression lines of rice to various flooding conditions. Indonesian Journal of Agricultural Science. [Online] 14 (1), 15–22. Available from: doi:10.21082/ijas. v14n1.2013.p15-26.

Panda, N., Heinrichs, E.A. & Box, P.O. (1982) Levels of tolerance and antibiosis in rice varieties having moderate resistance to the brown planthopper, Nilaparvata lugens (Stål) (Hemiptera: Delphacidae). Population English Edition. 12 (2), 1204–1214.

Ram, P.C., Singh, B.B., Singh, A.K., Ram, P., Singh, P.N., Singh, H.P., Boamfa, I., Harren, F., Santosa, E., Jackson, M.B., Setter, T.L., Reuss, L.J., Wade, L.J., Singh, V.P., Singh, R.K. (2002) Submergence tolerance in rainfed lowland rice: Physiological basis and prospects for cultivar improvement through marker-aided breeding. Field Crops Research. [Online] 76 (2–3), 131–152. Available from: doi:10.1016/S0378-4290(02)00035-7.

Ruskandar, A. (2010) Persepsi petani dan identifikasi faktor penentu pengembangan dan adopsi varietas padi hibrida. Iptek Tanaman Pangan. [Online] 5 (2), 113–125. Available from http://ejurnal.litbang.pertanian.go.id/index.php/ippan/article/view/2602

Sarkar, R.K., Reddy J.N., Sharma, S.G., & Ismail, A.M. (2006) Physiological basis of submergence tolerance in rice and implications for crop improvement. Current Science. 91 (7), 899–905. Available from http://www.jstor.org/stable/24094287

SAS Institute Inc (2009) SAS/STAT 9.2 User’s Guide. SAS Institute Inc., Cary, NC. [Online] p. 8640. Available from: doi:10.1111/ j.1532-5415.2004.52225.x.

Septiningsih, E.M., Pamplona A.M., Sanchez, D., Neeraja, C.V., Vergara, G.V., Heuer, S., Ismail, A.M., & Mackill, D.J. (2009) Development of submergence- tolerant rice cultivars: The Sub1 locus and beyond. Annals of Botany. [Online] 103 (2), 151–160. Available from: doi:10.1093/ aob/mcn206.

Septiningsih, E.M., Hidayatun, N., Sanchez, D.L., Nugraha, Y., Carandang, J., Pamplona, A.M., Collard, B.Y.C., Ismail, A.M., & Mackill, D.J. (2014) Accelerating the development of new submergence tolerant rice varieties: The case of Ciherang- Sub1 and PSB Rc18-Sub1. Euphytica. [Online] 202 (2), 259–268.Available from: doi:10.1007/s10681-014-1287-x.

Singh, S., Mackill, D.J. & Ismail, A.M. (2009) Responses of SUB1 rice introgression lines to submergence in the field: Yield and grain quality. Field Crops Research. [Online] 113 (1), 12–23. Available from: doi:10.1016/j.fcr.2009.04.003.

Suprihatno, B. Darajat, A.A., Satoto, Baehaki, S.E., Suprihanto, Setyono, A., Indrasari, S.D., Wardana, I.P., & Sembiring, H. (2012) Deskripsi Varietas Padi. Sukamandi, Balai Besar Penelitian Tanaman Padi.

Thomson, M.J. (2014) High-Throughput SNP Genotyping to Accelerate Crop Improvement. Plant Breeding and Biotechnology [Online] 2(3), 195-212. Available from DOI: https://doi.org/10.9787/PBB.2014.2.3.195

Vogel, K.E. (2009) Backcross breeding. Methods in Molecular Biology. [Online] 526, 161–169. Available from: doi:10.1007/978- 1-59745-494-0-14.

Xu, K. et al. (2006) Sub1A is an ethylene-response-factor-like gene that confers submergence tolerance to rice. Nature. [Online] 442 (7103), 705–708. Available from: doi:10.1038/nature04920.



INHIBITION OF THE GROWTH OF TOLERANT YEAST Saccharomyces cerevisiae STRAIN I136 BY A MIXTURE OF SYNTHETIC INHIBITORS

Penghambatan Pertumbuhan Ragi Toleran Saccharomyces cerevisiae Strain I136 Menggunakan Campuran Inhibitor Sintetis

Eny Ida Riyanti* and Edy Listanto

Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and DevelopmentJalan Tentara Pelajar No. 3A Bogor 16111, West Java, Indonesia


Submitted 26 May 2016; Revised 10 April 2017; Accepted 12 April 2017

ABSTRACT

Biomass from lignocellulosic wastes is a potential source for bio-based products. However, one of the constraints in utilization of biomass hydrolysate is the presence of inhibitors. Therefore, the use of inhibitor-tolerant microorganisms in the fermentation is required. The study aimed to investigate the effect of a mixture of inhibitors on the growth of Saccharomyces cerevisiae strain I136 grown in medium containing synthetic inhibitors (acetic acid, formic acid, furfural, 5-hydroxymethyl furfural/5-HMF, and levulinic acid) in four different concentrations with a mixture of carbon sources, glucose (50 g.l-1) and xylose (50 g.l-1) at 30oC. The parameters related to growth and fermentation products were observed. Results showed that the strain was able to grow in media containing natural inhibitors (BSL medium) with µmax of 0.020/h. Higher level of synthetic inhibitors prolonged the lag phase, decreased the cell biomass and ethanol production, and specific growth rate. The strain could detoxify furfural and 5-HMF and produced the highest ethanol (Y(p/s) of 0.32 g.g-1) when grown in BSL. Glucose was utilized as its level decreased in a result of increase in cell biomass, in contrast to xylose which was not consumed. The highest cell biomass was produced in YNB with Y (x/s) value of 0.25 g.g-1. The strain produced acetic acid as a dominant side product and could convert furfural into a less toxic compound, hydroxyl furfural. This robust tolerant strain provides basic information on resistance mechanism and would be useful for bio-based cell factory using lignocellulosic materials.

[Keywords: inhibitors, growth profile, yeast, Saccharomyces cerevisiae]

ABSTRAK

Biomassa dari limbah lignoselulosa berpotensi sebagai sumber produk biologi. Namun, salah satu kendala pemanfaatan hasil hidrolisis biomassa adalah adanya senyawa inhibitor sehingga penggunaan mikroorganisme tahan inhibitor sangat diperlukan dalam proses fermentasi. Penelitian ini bertujuan untuk mengetahui pengaruh campuran inhibitor terhadap Saccharomyces cerevisiae strain I136 yang ditumbuhkan dalam medium yang mengandung campuran inhibitor sintetis (asam asetat, asam format, furfural, 5-hydroxymethylfurfural/5-HMF, dan asam levulinat) dalam empat

konsentrasi yang berbeda dengan sumber karbon glukosa (50 g.l-1) dan xilosa (50 g.l-1) pada suhu 30oC. Pengamatan dilakukan terhadap parameter yang terkait dengan pertumbuhan strain ini dan produk hasil fermentasi. Hasil penelitian menunjukkan bahwa strain I136 tahan terhadap media BSL dengan nilai µmax 0,020/h. Peningkatan konsentrasi inhibitor dalam medium memperpanjang fase lag serta menurunkan produksi biomassa sel, produksi etanol, dan laju pertumbuhan spesifik. Strain ini mampu mendetoksifikasi senyawa furfural dan 5-HMF dan menghasilkan etanol tertinggi dengan nilai Y(p/s) 0,32 g.g-1 ketika ditumbuhkan dalam media BSL. Glukosa dapat digunakan yang ditandai dengan menurunnya konsentrasi glukosa dan meningkatnya konsentrasi biomassa sel. Sebaliknya, xilosa tidak digunakan dan konsentrasinya tetap sekitar 50 g.l-1. Produksi biomassa sel tertinggi dicapai ketika strain ini ditumbuhkan dalam media YNB dengan nilai Y(x/s) 0,25 g.g-1. Strain ini menghasilkan asam asetat sebagai produk samping yang dominan dan dapat mengubah furfural menjadi senyawa yang kurang toksik, yaitu hidroksi furfural. Hasil penelitian ini memberikan informasi awal tentang mekanisme toleransi dan berguna sebagai pabrik sel untuk produk biologi dengan menggunakan materi dari bahan berlignoselulosa.

[Kata kunci: inhibitor, profil pertumbuhan, ragi, Saccharomyces cerevisiae]

INTRODUCTION

Concerns on sustainability and environment are the most important reasons for driving force research on bio-based chemicals and bioenergy. In particular, lignocellulosic waste is considered as the most potential raw material for sustainable industry due to its abundantly available and low cost to meet economic value of bio-based products (Riyanti 2009, Sinumvayo et al. 2015). The annual global production of lignocellulose was approximately 50 billion tons (Claasen et al. 1999), indicating a sufficient amount of materials to develop environmentally friendly and sustainable biofuel production (Naik et al. 2010; Sims et al. 2010). Biofuel by-products from lignocellulosic biomass could be utilized further for soil amendmend to substitute chemical fertilizer (Singla and Inubushi 2014).


Fermentable sugars from lignocelluloses can be exposed through several pre-treatment technologies including sulphuric acid treatment, alkaline treatment, steam explosion and enzymatic degradation (Hu and Ragauskas 2012; Saini et al. 2015; Wi et al. 2015). However, simple sugars produced by pretreatment of lignocelluloses generate a variety of inhibitory compounds by further degradation of simple sugars (Zha et al. 2014), and it is recognized as the greatest constraint in lignocelluloses industrialization. Research on various areas for utilizing sugars from lignocellulosic materials for valuable products, such as isolation of new microbes, gene studies, genetic manipulation and kinetic evaluation have long been conducted (Jeon et al. 2009; Riyanti and Rogers 2009a, 2009b; Riyanti 2011).

The growth of most robust microbe for fermentation, Saccharomyces cerevisiae, was inhibited by compounds resulted from lignocelullosic hydrolisate such as aldehydes, ketones, phenols and organic acids (Palmqvist and Hahn-Hagerdal 2000; Li et al. 2015). These inhibitory aldehyde compounds have been given more attention during the last two decades due to their toxicity to the fermentative microbe’s cells. The aldehyde compounds such as 5-hydroxymethyl furfural (5-HMF), furfural, methyl glyoxal, vanillin and glycol aldehyde are the main inhibitors present in the hot-compressed water-treated lignocelluloses (Yu et al. 2007; Jayakodi et al. 2011; Caspeta et al. 2015), while furfural is the most toxic compound in the lignocellulosic hydrolysate (Heer and Sauer 2008).

S. cerevisiae is the most robust microorganism for ethanol cell factory compared to other microbes due to its morphological advantages (Barnet 2003). However, the natural yeast is sensitive to inhibitors resulted from lignocellulosic hydrolysate materials. Aims to sought inhibitor-tolerant yeast have been reported by adaptation to toxic compound and genetic engineering. Few publications reported that tolerant yeast produced low ethanol in the presence of low concentrations of furfural and HMF (Taherzadeh et al. 2000; Liu et al. 2004). A recombinant inhibitor-tolerant S. cerevisiae strain D5A+

could grow in a medium consisting of 60% (v/v) non-detoxified hydrolysate from triticale straw, supplemented with 20 g.l-1 xylose as a carbon source, in semi-aerobic batch cultures. In the same medium, this strain exhibited a slightly lower maximum specific growth rate (μmax = 0.12 ± 0.01 h−1) compared to TMB3400, with no ethanol produced by the latter strain (Smith et al. 2014; Ohgren et al. 2006).

The objective of this study was to investigate the effect of a mixture of synthetic inhibitors on the growth of S. cerevisiae I136. The result would be useful for further survival mechanism study of microbes toward inhibitors.


Yeast Strain and Cell Culture Preparation

Saccharomyces cerevisiae strain I136 was maintained in Yeast Potato Dextrose (YPD) medium containing 10 g yeast extract, 20 g bacto peptone, 20 g glucose and 15 g agar per liter (Ausubel et al. (eds) 2003). The strain was obtained from and deposited at the Faculty of Chemical Engineering, Kobe University, Kobe, Japan.

Seed Inoculum

The single colony of strain I136 from YPD agar plate was cultured in 150 ml erlenmeyer flask containing 12.5 ml YNB broth medium and incubated overnight at 30oC, 150 rpm for seed culture. This pure I136 culture was then used for further assay.

Chemicals, Medium Preparation and Fermentation Conditions

Furfural and 5-HMF were purchased from Wako (Osaka, Japan) and Tokyo Chemical Industry (Tokyo, Japan), respectively. The purity of both furaldehydes was 95%. Furfuraldehyde was immediately prepared by dissolving in dimethyl sulfoxide (DMSO) as 2M stock solutions after the bottle was opened to prevent oxidation.

The batch cultivations were carried out in 250 ml conical flasks equipped with rubber stoppers for aerobic cultivation. Fermentation media with four degrees of complex inhibitor strength, namely medium I, II, III and IV, and control medium using natural inhibitors (steamed high pressure treated-bagase/Bagase Sugar Lysate, BSL), and control medium without inhibitors (Yeast Nitrogen Base, YNB) were used in this experiment. Medium IV contained 6.7 YBS without amino acid, 50 g glucose, 50 g xylose, 40 mg adenine sulfate salt, and a mixture of inhibitors: 60 mM acetic acid, 30 mM formic acid, 60 mM furfural, 10 mM 5-HMF, and 5 mM leuvinic acid in 1 L. YNB medium consisted of 50 g glucose, 50 g xylose, 6.7 g YNB without amino acid and 40 mg adenine salt. The experiment was carried out three times as replication. The inhibitor concentrations used in this experiment were shown in Table 1.

Seed culture of 1.2 ml was used to inoculate the 12 ml fermentation medium to give 10% concentration. Fermentation was conducted in a shaker incubator at 150 rpm, 30oC for 48 hours. A sample of 500 µl was taken every 3 hours during fermentation. The samples were then centrifuged 5,000 g at 4oC for 5 min, and then 450 µl supernatant were transferred into a High-Performance Liquid Chromatography (HPLC) vial for further analysis.

19Inhibition Of The Growth Of … (Eny Ida Riyanti and Edy Listanto)

Cell Staining and Examination

Cells were stained using propidium iodine (PI) (Annexin V-FITC apoptosis detection kit, AbcamR). Cells from 100 µl broth culture were sedimented using centrifugation at 5000 rpm for 2 min. After cells wash with 100 µl PBS, the 100 µl binding solution and 1 µl Anexin VFITC were added, resuspended and incubated for 15 min at 300C, 150 rpm in DeepWell Maximizer, Taitec (Bio Shaker M-BR022UP) shaker incubator. At a final step, PI (1 µl) was added and incubated for 5 min at 150 rpm, 30oC using DeepWell Maximizer, Taitec (Bio Shaker M-BR022UP) shaker incubator. The cells were then examined under microscope (Biozero BZ-8000) with Nikon Plant APO 40 x 0.95 lenz.

Fermentation Product Analysis

Cell biomass was monitored using UV mini-1240, UV-VIS Spectrophotometer, Shimadzu with OD600

measurement. The standard curve for OD600 reading and dried cells was determined earlier for conversion of OD600 reading during fermentation. Sugar consumption (glucose and xylose) and fermentation products such as ethanol, acetic acid and lactic acid were assayed using HPLC Shimadzu machine LC2010, equipped with ISEP ICE-COREGEL 87H3 column (Biorad, Hercules, USA) at 80°C. Elution of analytes was done at a flow rate of 0.4 ml.min-1 using H2SO4 as the mobile phase. Sample injection was conducted at 20 µl per sample according to the manual for ISEP ICE-COREGEL 87H3 column (Biorad, Hercules, USA).

Inhibitor concentrations were analyzed using a gas chromatograph-mass spectrometer (GC-MS) (QP2010 Ultra, Shimadzu) with a DB-FFAP column (60 m × 0.25 mm i.d., 0.50-μm film thickness) Agilent Technologies, CA, USA. The column temperature was maintained at 80°C. Peak areas were normalized to the internal standard and used for representing the abundance of furans in the samples.

Data Analysis

Data analysis was performed using excel program (@Microsoft 2017). Error bars were added for the standard deviation as follow:

Where x represents each value in the population, x is the means of the sample, Σ is the sum (total), and n-1 is the number of values in the sample minus 1.

The biomass was sampled each hour for 48 hour. One ml of culture was dried in a vacuum dryer for 2 x 24 hour and then weighed using a fine balance to make calibration curve for biomass vs OD600. Biomass produced was then calculated based on the biomass calibration curve.

The growth kinetic parameters of strain I136 were estimated using the following formula. Specific growth rate (µmax) = 1/x (dx/dt); x = cell mass concentration (g.l-1), t = time. Growth yield coefficient = Yx/s = dx/ds; x = cell mass concentration (g.l-1), s = substrate (g.l-

1). Product yield coefficient Yp/s = dp/ds; p = product (ethanol) (g.l-1), s = substrate (g.l-1).


Growth Profiles of Strain I136

The growth of strain I136 in media containing four different concentrations of synthetic inhibitors (acetic acid, formic acid, furfural, 5-HMF and levulinic acid) showed that strain I136 grew well in natural medium from liquefied lignocellulosic material, BSL (Figure 1 F) containing natural inhibitors (Table 1). This means that the strain is tolerant to natural inhihitors. The rate of glucose consumption varied depending on the inhibitor concentrations in the medium. In medium without inhibitors (YNB), the strain used glucose to start the fermentation and continued to use it upto 12 hrs after incubation (Figure 1 A).

Table 1. Composition of inhibitors in four different concentrations.

Inhibitors Inhibitor concentration (mM)

BSL YNB Medium I Medium II Medium III Medium IV

Acetic acid 24 0 24 30 36 60

Formic acid 10 0 12 15 18 30

Furfural 5.7 0 24 30 36 60

5- HMF 0.5 0 4 5 6 10

Levulinic acid 3.1 0 2 2.5 3 5

s = S√ ( x - x )2

n - 1


Figure 1 (A-E) shows that higher concentrations of synthetic inhibitors prolonged the lag phase during fermentation process. In medium I, with the least inhibitor concentration, the strain started to utilize glucose rapidly after the lag phase at 12 hrs, and used up all the glucose at about 24 hrs. Similarly, in medium II the lag phase was upto 12 hrs, and then the strain started to uptake the glucose for cell growth and used up at about 30 hrs. In medium III (Figure 1 D), the strain used glucose slowly after the lag phase at 12 hrs, and uptaken all the glucose in the medium at 48 hrs after fermentation. In medium IV (Figure 1 E), containing the highest inhibitor concentration, the strain did not grow properly as the cell biomass did not increase during fermentation process, and the sugar carbon was not utilized. Interestingly in medium containing natural inhibitor (BSL) (Figure 1 F), the strain uptook glucose directly when the fermentation process started, but the strain experienced slugish lag phase compared to that grown in medium without inhibitors (YNB) (Figure 1A). Lag-phase is the period before the growth takes place, which is mainly influenced by the initial media composition. A longer lag-phase indicates the presence of compounds that inhibit the growth (Liu 2004; Zha et al. 2014). During this phase, the strain may adapt to the medium either

by degrading or converting its compounds. Glucose of about 50 g/l-1 in the BSL medium was taken up after 35 hrs. Ethanol was produced as a result of glucose utilization and the growth increased exponentially after 12 hrs of fermentation. In medium IV, the strain was not able to utilize both sugars, glucose and xylose. and growth was stopped as the cells deceased. Dong et al. 2016 reported that yeast cells perform a programmed cell death to response environmental stress such as acetic acid treatment. Observation under a microscope showed that the death cells would be red as a result of PI absorbtion, while the healthy cells remained colorless (Figure 2). PI is a fluorescent intercellating agent which cannot cross the membrane of live cells, therefore it is commonly used for differentiating between necrotic and healthy cells (Lecoeur 2002)

Herr and Sauer (2008) reported that inhibitors affected cell growth resulting in longer lag phase. Furan furfural inhibits at least three enzymes in the central carbon metabolism (Modig et al. 2002). According to Heer and Sauer (2008), furfural concentrations in different lignocellulosic raw materials and hydrolysis processes ranged from 5.5 to 30 mM, leading to the inhibition of yeast growth. Lag phases of various yeast strains due to the presence of inhibitors ranged from 7 to 90 hrs. Strain

Fig. 1. Growth profiles of Saccharomyces cerevisiae strain I136 in different inhibitor-containing media. A = medium without inhibitor (YNB), B = medium I, C = medium II, D = medium III, E = medium IV, F = BSL.

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resistance was based on its capacity to remain viable in a toxic environment during prolonged furfural induced lag phase. In this experiment, the media contained higher concentrations of furfural, i.e. 24, 30, 36 and 60 mM in medium I, II, III and IV, respectively. The long lag phase suggested that the cells adapted to the inhibitors for growth and survival. Moreover, the strain was not able to utilize xylose as a carbon source as its concentration remained at 50 g.l-1 at the end of cultivation period.

Factors influencing bioethanol production include temperature, sugar concentration, pH, fermentation time, agitation rate and inoculum size (Zabed et al. 2014). Ethanol production increased rapidly when the strain started to utilize the glucose. The maximum ethanol yield (Y (p/s)) was acheived when the strain was grown in BSL medium (0.32 g.g-1) (Table 2). In medium without inhibitor, the maximum ethanol production of 11 g.l-1 was reached at 12 hrs after fermentation. In medium I, ethanol increased slightly to 12 g.l-1 at 24 hrs, and in medium II and III the maximum ethanol was produced at 30 hrs after fermentation. In medium IV, ethanol was not produced because the inhibitors totally inhibited the cell growth.

Growth Kinetic Parameters on Batch Fermentation

The YNB medium provided the best growth for the strain with the highest maximum specific growth rate (µmax) of 0.08/h compared to that in other media containing inhibitors. Biomass coefficient determines the efficiency of conversion of substrate to biomass which was reflected in the Y(x/s) values (Table 2). The highest biomass production was achieved when the strain was grown in YNB (without inhibitors) with Y (x/s) value of 0.25 g. g-1 and then the biomass

production decreased as a result of increasing inhibitor concentration in medium I, II, III, and IV (Table 2). This result was supported by the highest specific growth rate in medium without inhibitors (YNB) compared to that in medium containing inhibitors. Harsh conditions during biomass pretreatment processes cause sugars and lignin in biomass hydrolysates to degrade, forming products that posses inhibitory effects towards fermenting hosts, resulting in reduced growth and productivity (Palmqvist and Hahn-Hägerdal 2000; Panagiotopoulos et al. 2011; Zha et al. 2011).

Product formed in batch fermentation can be expressed in Y(p/s) (Table 2). The highest product formation was achieved in BSL medium, indicating that the strain was tolerant to natural inhibitors in the medium. This medium is a liquid biomass resulted from hydrolysis using steam explotion method which contained complex natural inhibitors. Increasing concentrations of synthetic inhibitors (from medium I to medium IV) decreased the biomass yield Y(x/s). The highest biomass yield was achieved when the strain was grown in medium without inhibitor (YNB) as shown in Table 2. Increasing inhibitor concentrations in the medium also decreased the fermentation product (Y(p/s)). Palmqvist and Hahn-Hägerdal (2000) reported that inhibitors in the lignocellulosic hydrolysate limited efficient utilization of hydrolysates for ethanol production. The highest ethanol yield was obtained when the strain was grown in BSL medium containing natural inhibitors with the Y(p/s) value of 0.32 g.g-1, suggesting that ethanol production was not inhibited by the presence of natural inhibitors. The growth of most ethanol producing microbes is inhibited by inhibitors present in the lignocellulosic hydrolysate (Palmquist and Hahn–Hagerdal 2000), however the studied strain was not affected by natural inhibitors in the BSL medium.

4

Fig. 2. Saccharomyces cerevisiae strain I136 examination under fluorescent microscope after staining using propidium iodine (PI); the cells previously were grown in medium containing synthetic inhibitors; transparent cells = healthy cells, red cells = death cells.

Table 2. Growth kinetic parameters of Saccharomyces cerevisiae strain I136 in different media containing synthetic inhibitors.

MediumY(x/s) Y(p/s)

µmax (/h)(g.g-1)

BSL 0.20 0.32 0.020

YNB 0.25 0.28 0.080

I 0.17 0.30 0.062

II 0.16 0.30 0.058

III 0.16 0.26 0.052

IV 0.09 0.22 0.008

Y(x/s) = cell biomass yield based on substrate utilization, Y(p/s) = ethanol yield based on substrate utilization, S = substrate (glucose), µmax = specific growth rate.


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Inhibitor Detoxification

Inhibitor detoxification positively correlated with fermentation period; the higher the concentration the longer the detoxification process (Figure 3A). Furfural concentration decreased according to the increasing concentrations of inhibitors in the medium and reached the zero level after 12 hrs, 24 hrs and 30 hrs in medium I, II, and III, respectively. In medium IV, the furfural decreased slowly and remained of about 25 mM at the end of fermentation process as the yeast cells stopped growing (µmax = 0.008/h). Our study result is in a good agreement with the previous findings, where several yeast strains could withstand in the presence of lignocellulosic inhibitor by detoxifying the toxic compound into a less toxic one. In this experiment, the toxic compound and the detoxified compound, furfuryl alcohol, were monitored (Figure 3A and 3B). Concentration of the less toxic compound resulting from furfural detoxification, furfuryl alcohol, increased in the fermentation process (Figure 3B). During the fermentation process, the aldehyde

furfural and 5-HMF reduced to their corresponding less toxic alcohols (Palmqvist and Hahn-Hagerdal 2000; Jonsson et al. 2013).

Lignocellulosic hydrolysis lead to the dehydration of glucose and xylose to furfural and HMF, respectively, which are inhibitory compounds to yeast growth and alcohol fermentation. The most toxic compound in lignocellulosic hydrolysate is furfural (Jonsson et al. 2013; Field et al. 2015). This I136 strain could detoxify furfural into a less toxic coumpound, furfuryl alcohol (Figure 3), and the highest rate of detoxification was found in medium II (Table 3).

Detoxification rate was measured for two important inhibitors, furfural and 5-HMF (Table 3). The concentration of 5 HMF decreased during fermentation in medium I, II and III containing synthetic inhibitors. However, in medium IV its concentration remained stable and the cells were unable to grow properly due to inhibition (Figure IE). Levulinic acid and formic acid concentration remained stable in the medium. It shows that S. cerevisiae enzymatically converts most of these

Fig. 3. Detoxification of furfural into furfuryl alcohol. A = furfural, B = furfuryl alcohol.

Fig. 4. The dynamic of inhibitors during fermentation process. A = 5-HMF, B = levulinic acid, C = formic acid.

Concentration (nM) Concentration (nM)

Time (h) Time (h)

BA

A B C


toxic compounds into the less toxic ones. Multiple genes possibly involved in the conversion pathways coupled with nicotinamide adenine dinucleotide (NADH) and nicotinamide adenine dinucleotide phosphate (NADPH) (Jayakodi et al. 2014).

CONCLUSION

Saccharomyces cerevisiae I136 was capable of growing in medium containing synthetic inhibitors and produced ethanol. This strain was able to grow in natural medium from lignocellulosic hydrolysate, BSL, containing natural inhibitors and produced high ethanol. The inhibitors prolonged the lag phase of the strain and decreased the cell biomass and ethanol production. The strain stopped growing in medium containing high inhibitors (60 mM acetic acid, 30 mM formic acid, 60 mM furfural and 10 mM 5-HMF) and the cells died. Strain I136 was able to detoxify furfural into a less toxic compound, furfuryl alcohol.

ACKNOWLEDGEMENT

This study is a part of post-doctorate training funded by the Indonesian Agency for Agricultural Research and Development (IAARD) under the SMARD Project. The research was conducted at Kobe University, Japan in 2015. The authors sincerely thank to Prof. Chiaki Ogino and Dr. Prihardi Kahar for acceptation and providing research materials and guidance in Kobe University.

REFERENCES

Ausubel, F.M., Brent, R., Kingston, R.E., Moore, D.D., Seidman, J.G., Smith, J. A, Struhl, K., Wiley, C.J., Allison, R.D., Bittner, M. & Blackshaw, S. (2003) Current Protocols in Molecular Biology. Frederick M. Ausubel, Roger Brent, Robert E. Kingston, David D. Moore, J.G. Seidman, John A. Smith,K.S. (ed.) Molecular Biology. [Online] 1, John Wiley & Sons. Available from: doi:10.1002/mrd.1080010210.

Barnett, J.A. (2003) Beginnings of microbiology and biochemistry: The contribution of yeast research. Microbiology. [Online] 149 (3), 557–567. Available from: doi:10.1099/mic.0.26089-0.

Caspeta, L., Castillo, T. & Nielsen, J. (2015) Modifying yeast tolerance to inhibitory conditions of ethanol production processes. Frontiers in Bioengineering and Biotechnology. [Online] 3, 1–15. Available from: doi:10.3389/fbioe.2015.00184.

Claassen, P.A.M., van Lier, J.B., Lopez Contreras, A.M., van Niel, E.W.J., Sijtsma, L., Stams, A.J.M., de Vries, S.S. & Weusthuis, R.A. (1999) Utilisation of biomass for the supply of energy carriers. Applied Microbiology and Biotechnology. [Online] 52 (6), 741–755. Available from: doi:10.1007/s002530051586.

Dong, Y., Hu, J., Fan, L. & Chen, Q. (2017) RNA-Seq-based transcriptomic and metabolomic analysis reveal stress responses and programmed cell death induced by acetic acid in Saccharomyces cerevisiae. Scientific Reports. [Online] 7, Nature Publishing Group. Available from: doi:10.1038/srep42659.

Field, S.J., Ryden, P., Wilson, D., James, S.A., Roberts, I.N., Richardson, D.J., Waldron, K.W. & Clarke, T.A. (2015) Identification of furfural resistant strains of Saccharomyces cerevisiae and Saccharomyces paradoxus from a collection of environmental and industrial isolates. Biotechnology for Biofuels. [Online] 8 (1), 33. Available from: doi:10.1186/s13068-015-0217-z.

Heer, D. & Sauer, U. (2008) Identification of furfural as a key toxin in lignocellulosic hydrolysates and evolution of a tolerant yeast strain. Microbial Biotechnology. [Online] 1 (6), 497–506. Available from: doi:10.1111/j.1751-7915.2008.00050.x.

Hu, F. & Ragauskas (2012) Pretreatment and lignocellulosic chemistry. BioEnergy Research. [Online] 5 (4), 1043–1066. Available from: doi:10.1007/s12155.

Jayakody, L.N., Hayashi, N. & Kitagaki, H. (2013) Molecular mechanisms for detoxification of major aldehyde inhibitors for production of bioethanol by Saccharomyces cerevisiae from hot- compressed water-treated lignocellulose.In: Méndez-Vilas,A. (ed.) Materials and processes for energy: communicating current research and technological developments. Badajoz, Spain, Formatex Research Center, pp.302–311.

Jeon, Y.J., Fong, J.C.N., Riyanti, E.I., Neilan, B.A., Rogers, P.L. & Svenson, C.J. (2008) Heterologous expression of the alcohol dehydrogenase (adhI) gene from Geobacillus thermoglucosidasius strain M10EXG. Journal of Biotechnology. [Online] 135 (2), 127–133. Available from: doi:10.1016/j.jbiotec.2008.02.018.

Jönsson, L.J., Alriksson, B. & Nilvebrant, N.-O. (2013) Bioconversion of lignocellulose: inhibitors and detoxification. Biotechnology for Biofuels. [Online] 6 (16). Available from: doi:10.1186/1754-6834-6-16.

Lecoeur, H. (2002) Nuclear apoptosis detection by flow cytometry: Influence of endogenous endonucleases. Experimental Cell Research. [Online] 277 (1), 1–14. Available from: doi:10.1006/excr.2002.5537.

Li, H., Wu, M., Xu, L., Hou, J., Guo, T., Bao, X. & Shen, Y. (2015) Evaluation of industrial Saccharomyces cerevisiae strains as the chassis cell for second-generation bioethanol production. Microbial Biotechnology. [Online] 8 (2), 266–274. Available from: doi:10.1111/1751-7915.12245.

Liu, Z.L., Slininger, P.J., Dien, B.S., Berhow, M.A., Kurtzman, C.P. & Gorsich, S.W. (2004) Adaptive response of yeasts to furfural and 5-hydroxymethylfurfural and new chemical evidence for HMF conversion to 2,5-bis-hydroxymethylfuran. Journal of Industrial Microbiology and Biotechnology. [Online] 31 (8), 345–352. Available from: doi:10.1007/s10295-004-0148-3.

Modig, T., Liden, G. & Taherzadeh, M.J. (2002) Inhibition effects of furfural on alcohol dehydrogenase, aldehyde dehydrogenase and pyruvate dehydrogenase. Biochemical Journal. [Online] 363 (3), 769–776. Available from: doi:10.1042/bj3630769.

Naik, S.N., Goud, V. V., Rout, P.K. & Dalai, A.K. (2010) Production of first and second generation biofuels: A comprehensive review. Renewable and Sustainable Energy Reviews. [Online] 14 (2), 578–597. Available from: doi:10.1016/j.rser.2009.10.003.

Öhgren, K., Bengtsson, O., Gorwa-Grauslund, M.F., Galbe, M., Hahn-Hägerdal, B. & Zacchi, G. (2006) Simultaneous saccharification and co-fermentation of glucose and xylose in steam-pretreated corn stover at high fiber content with Saccharomyces cerevisiae TMB3400. Journal of Biotechnology. [Online] 126 (4), 488–498. Available from: doi:10.1016/j.jbiotec.2006.05.001.

Palmqvist, E. & Hahn-Hägerdal, B. (2000) Fermentation of lignocellulosic hydrolysates. II: Inhibitors and mechanisms of inhibition. Bioresource Technology. [Online] 74 (1), 25–33. Available from: doi:10.1016/S0960-8524(99)00161-3.

Panagiotopoulos, I.A., Bakker, R.R., de Vrije, T. & Koukios, E.G. (2011) Effect of pretreatment severity on the conversion of barley straw


to fermentable substrates and the release of inhibitory compounds. Bioresource Technology. [Online] 102 (24), Elsevier Ltd, 11204–11211. Available from: doi:10.1016/j.biortech.2011.09.090.

Riyanti, E.I. (2011) Beberapa gen pada bakteri yang bertanggung jawab terhadap produksi bioetanol. Jurnal Penelitian dan Pengembangan Pertanian. 30 (3), 41–47.

Riyanti, E.I. (2009) Biomassa sebagai bahan baku bioetanol. Jurnal Penelitian dan Pengembangan Pertanian. 28 (3), 101–110.

Riyanti, E.I. & Rogers, P.L. (2009a) Construction and expression of pet operon using shuttle vector for mesophilic and thermophilic bacteria. Jurnal Agrobiogen. 5 (1), 7–15.

Riyanti, E.I. & Rogers, P.L. (2009b) Kinetic evaluation of ethanol-tolerant thermophile Geobacillus thermoglucosidasius M10EXG for ethanol production. Indonesian Journal of Agricultural Science. 10 (1), 34–41.

Saini, J.K., Saini, R. & Tewari, L. (2015) Lignocellulosic agriculture wastes as biomass feedstocks for second-generation bioethanol production: concepts and recent developments. 3 Biotech. [Online] 5 (5), 337–353. Available from: doi:10.1007/s13205-014-0246-5.

Sims, R.E.H., Mabee, W., Saddler, J.N. & Taylor, M. (2010) An overview of second generation biofuel technologies. Bioresource Technology. [Online] 101 (6), Elsevier Ltd, 1570–1580. Available from: doi:10.1016/j.biortech.2009.11.046.

Singla, A. & Inubushi, K. (2014) Effect of biochar on CH4 and N2O emission from soils vegetated with paddy. Paddy and Water Environment. [Online] 12 (1), Springer Japan, 239–243. Available from: doi:10.1007/s10333-013-0357-3 [Accessed: 17 July 2017].

Sinumvayo, J.P., Ishimwe, N., Komera, I. & Niyomukiza, S. (2015) Ethanol biofuel production from lignocellulosic biomass by engineered saccharomyces cerevisiae. Journal of Academia and Industrial Research. 3 (10).

Smith, J., van Rensburg, E. & Görgens, J.F. (2014) Simultaneously improving xylose fermentation and tolerance to lignocellulosic inhibitors through evolutionary engineering of recombinant Saccharomyces cerevisiae harbouring xylose isomerase. BMC biotechnology. [Online] 14 (1), 41. Available from: doi:10.1186/1472-6750-14-41.

Taherzadeh, M.J., Gustafsson, L., Niklasson, C. & Lidén, G. (2000) Physiological effects of 5-hydroxymethylfurfural on Saccharomyces cerevisiae. Applied Microbiology and Biotechnology. [Online] 53 (6), 701–708. Available from: doi:10.1007/s002530000328.

Yu, Y., Lou, X. & Wu, H. (2008) Some recent advances in hydrolysis of biomass in hot-compressed water and its comparisons with other hydrolysis methods. Energy and Fuels. [Online] 22 (1), 46–60. Available from: doi:10.1021/ef700292p.

Zabed, H., Faruq, G., Sahu, J.N., Azirun, M.S., Hashim, R. & Nasrulhaq Boyce, A. (2014) Bioethanol production from fermentable sugar juice. The Scientific World Journal. [Online] 2014. Available from: doi:10.1155/2014/957102.

Zha, Y., Westerhuis, J.A., Muilwijk, B., Overkamp, K.M., Nijmeijer, B.M., Coulier, L., Smilde, A.K. & Punt, P.J. (2014) Identifying inhibitory compounds in lignocellulosic biomass hydrolysates using an exometabolomics approach. BMC Biotechnology. [Online] 14 (22), BMC Biotechnology. Available from: doi:10.1186/1472-6750-14-22.



GENE ACTION AND HERITABILITY ESTIMATES OF QUANTITATIVE CHARACTERS AMONG LINES DERIVED FROM VARIETAL CROSSES OF SOYBEAN

Aksi Gen dan Dugaan Heritabilitas Karakter Kuantitatif pada Populasi Galur Kedelai Hasil Persilangan

Lukman Hakima* and Suyamtob

aIndonesian Center for Food Crops Research and DevelopmentJalan Merdeka No. 147, Bogor 16111, West Java, Indonesia, Phone +62-251 8334089, Fax +62-251 8312755

Email: [email protected] Legumes and Tuber Crops Research Institute

Jalan Kendal Payak, km 66, PO Box 66, Malang 65101, East Java, Indonesia*Corresponding author: [email protected]

Submitted 19 December 2016; Revised 10 May 2017; Accepted 15 May 2017

ABSTRACT

The knowledge of genetic action, heritability and genetic variability is useful and permits plant breeder to design efficient breeding strategies in soybean. The objectives of this study were to determine gene action, genetic variability, heritability and genetic advance of quantitative characters that could be realized through selection of segregation progenies. The F1 population and F2 progenies of six crosses among five soybean varieties were evaluated at Muneng Experimental Station, East Java during the dry season of 2014. The lines were planted in a randomized block design with four replications. The seeds of each F1 and F2 progenies and parents were planted in four rows of 3 m long, 40 cm x 20 cm plant spacing, one plant per hill. The result showed that pod number per plant, seed yield, plant yield and harvest index were found to be predominantly controlled by additive gene effects. Seed size was also controlled by additive gene effects, with small seed dominant to large seed size. Plant height was found to be controlled by both additive and nonadditive gene effects. Similarly, days to maturity was due mainly to additive and nonadditive gene effects, with earliness dominant to lateness. Days to maturity had the highest heritability estimates of 49.3%, followed by seed size (47.0%), harvest index (45.8%), and pod number per plant (45.5%). Therefore, they could be used in the selection of a high yielding soybean genotype in the F3 generation.

[Keywords: gene action, heritability, soybean, varietal crosses]

ABSTRAK

Dalam pemuliaan kedelai, pengetahuan tentang aksi gen, heritabilitas, dan keragaman genetik sangat diperlukan agar pemulia dapat merencanakan program seleksi yang efektif dan efisien. Penelitian ini bertujuan untuk mempelajari aksi gen, heritabilitas, kemajuan genetik, dan keragaman genetik karakter kuantitatif, galur kedelai hasil persilangan. Tanaman F1 dan galur F2 keturunan dari enam kombinasi persilangan, dan lima varietas tetua dievaluasi di Kebun Percobaan Muneng, Jawa Timur pada musim kemarau 2014. Percobaan menggunakan rancangan acak kelompok dengan empat ulangan. Biji F1 dan F2 dari setiap kombinasi persilangan dan varietas tetua ditanam masing-masing empat baris dengan panjang

barisan 3 m, jarak tanam 40 cm x 20 cm, satu tanaman per rumpun. Hasil penelitian menunjukkan jumlah polong per tanaman, hasil biji per tanaman, bobot brangkasan, dan indeks panen secara dominan dikendalikan oleh gen aditif. Ukuran biji juga dikendalikan oleh gen aditif, dan ukuran biji kecil bersifat dominan terhadap biji besar. Tinggi tanaman dikendalikan oleh gen aditif dan nonaditif, demikian pula umur polong masak secara dominan dikontrol oleh banyak gen (aditif dan nonaditif), dan umur genjah bersifat dominan terhadap umur dalam. Umur polong masak mempunyai dugaan heritabilitas paling tinggi (49,3%), diikuti ukuran biji, indeks panen, dan jumlah polong per tanaman, masing-masing 47,0%, 45,8%, dan 45,5%. Seleksi terhadap umur polong masak, ukuran biji, indeks panen, dan jumlah polong per tanaman mempunyai harapan kemajuan genetik cukup tinggi, masing-masing 41,0%, 38,8%, 33,6%, dan 29,1%. Oleh karena itu, karakter tersebut dapat digunakan sebagai kriteria seleksi untuk memperoleh genotipe kedelai yang berdaya hasil tinggi, berumur genjah, dan berukuran biji besar pada galur F3.

[Kata kunci: aksi gen, heritabilitas, kedelai, galur persilangan]

INTRODUCTION

In a selection program, knowledge of gene action, heritability and genetic variability is useful and permits plant breeder to design efficient selection strategies. Many traits of soybean are inhereted in a quantitative manner. The quantitative characters of soybean have been extensively studied included the seed yield, primary yield components, such as pods per plant, seed weight per plant and seed size as well as the trait related to plant size and development.

Seed yield of soybean is an important trait as it measures the economic productivity of the plant. However, inheritance of this character is extremely complex. Studies on combining ability and types of gene action on soybean by Murty et al. (2009) indicated that both additive and nonadditive gene effects contribute to seed yield with parent cultivars differing in the


relative importance of each. Similarly, Rao et al. (2009) reported that seed yield, harvest index and seed size were predominantly controlled by additive genes effects, while days to maturity was apparently controlled by both additive and nonadditive gene effects and the dominance effects being more evident in F2 generation.

Hakim et al. (2014) reported that in F2 progenies of three cross combinations among three soybean varieties, inheritance for pod number per plant, plant height and seed size in the next generation were high, while that for seed yield per plant was relatively small. Selection for high yielding soybean genotypes by increasing pod number per plant, plant height and seed size should be possible. While selection for increasing grain yield through improvement of seed yield per plant was relatively difficult.

Nonadditive gene action is the most important character in the F1 generation of Phaseolus aureus with degree of dominance reduced in the F2 and F3 (Singh and Singh 1987). These data illustrate the complexity of inheritance for seed yield. Imrie et al. (1987) reported that plant yield, seed yield and harvest index of mungbean were predominantly controlled by additive genes effects. Similarly, seed size was controlled by additive gene effects, while days to maturity by both additive and dominant gene effects. Knowledge of heritability and genetic advance of soybean may provide a basis for efficient planning in breeding program for soybean. Uzun et al. (2013) stated that studies on heritability estimates are helpful in knowing parent performance in hybrids of sesame.

Increasing grain yield would be most effective if the components involved were highly heritable and genetically independent of positively correlated of physiologically related in positive manner (Gravois and Mc New 1993). Genetic improvement of crops for quantitative characters requires reliable estimates of genetic diversity, heritability and genetic advance (Chand et al. 2008; Kumar and Kamendra 2009). If the heritability for the characters is higher, then selection progress becomes easier and thus response to selection will be greater.

Abady et al. (2013) reported that in F3 progenies of two cross combinations among three soybean varieties, seed yield per plant, plant height and days to maturity had the mean heritability estimates of 39.4%, 63.0% and 67.1%, respectively. While Zafar et al. (2010) reported that in F3 population, days to flowering, days to maturity and plant height had the highest heritability estimates of 56.0%, 71.1% and 70.2%, respectively. Whereas the heritability estimate for seed weight per plant was low of only 27.4%. Aditya et al. (2013) reported that among

eight quantitative characters studied, plant height and pod number per plant had the highest heritability estimates of 78.0% and 81.0% coupled with high genetic advance of 25.3% and 45.4%, respectively. Similar result was found by Akhter and Sneller (1996) who obtained heritability estimate for plant height of 46.7% and pod number per plant of 70.5%. The genetic progress of selection for these characters was predicted 67.4% and 20.9%, respectively.

The objectives of this study were to determine the magnitude of gene action, genetic variability, heritability and expected genetic advance that could be realized through selection of segregation progenies. Information obtained from this study would be helpful to specify certain traits as selection indices for identification of potentially high yielding soybean genotypes.


Genetic Materials and Development of F2 Populations

Genetic materials used and their characteristics are shown in Table 1. Six cross combinations among five soybean varieties (Muria x Grobogan, Muria x Burangrang, Muria x Panderman, Kawi x Grobogan, Kawi x Burangrang, Kawi x Panderman) were conducted in the wet season of 2013 at Screen House, Muneng Experimental Station, Probolinggo, East Java. The main aims of the crosses were to improve grain yield (>2 t.ha-1), days to maturity (75 days) and seed size (> 17 g.100-1 seeds) of variety Muria and Kawi which at present both varieties have low yield, late maturity and small seed size.

The F1 seeds were planted at Muneng Experimental Station, Probolinggo, East Java, during the dry season of 2013. The F1 plants were harvested through a bulk method. A total of twenty four F2 progenies of each cross were developed from each F1 plant.

Table 1. Characteristics of parental varieties of soybean used in crosses for developing F2 populations.

Code of parents

Varieties Days to maturity

Plant height (cm)

Seed size (g.100-1 seeds)

Yield (t.ha-1)

P1 Muria 90 50 12 1.7

P2 Kawi 95 70 10 1.8

P3 Grobogan 73 65 19 2.7

P4 Burangrang 78 70 17 2.5

P5 Panderman 80 65 19 2.4

Source: Indonesian Legumes and Tuber Crops Research Institute (2005).

27Gene Action and Heritability … (Lukman Hakim et al.)

Field Trials of F1 and F2 Progenies

The F2 progenies derived from the six crosses consisted of two hundred and four progenies each were evaluated together with their parents (Muria, Grobogan, Burangrang, Panderman and Kawi) at Muneng Experimental Station, Probolinggo, East Java during the dry season of 2014. In case of expected genetic advance, the F2 populations were selected based on 10% selection intensity.

The experiment was arranged in a randomized block design with four replications. The seeds of each F1 and F2 progenies and their parents were sown in four rows of 3 m long, 40 cm x 20 cm plant spacing, one plant per hill. Population of each F1 plant, F2 progenies and the parents were 60 plants in each plot. Basal fertilizers were applied at the rate of 50 kg urea, 100 kg Phonska and 50 kg SP36 per hectare. Agronomic practices such as weeding and insect pest control were carried out according to recommendation.

Data were collected based on individual plants of sixty plants per plot. Parameters observed included days to maturity (DM), plant height (PH), pod number per plant (PP), seed size (SS), seed yield per plant (SY), plant yield (PY) and harvest index (HI). Collected yield data were then calculated as SY/(SY+PY).

Data Analyses

The genetic variation was estimated using a formula suggested by Stuber (1970): additive variance (S2A) = (S2m + S2f); nonadditive variance (S2D) = S2mf, in the F1 generation and a S2D = 4S2mf, in the F2 generation. Whereas, S2m is the variance for male parents, S2F is a variance for female parents, and S2mf is a male x female interaction variance.

The ratio of additive to nonadditive (dominance) variance was calculated using a formula of S2A/ S2D. The heritability (H) was estimated using a formula: H = S2A/(S2A + S2D + S2e). Genetic advance (GA) was estimated using a formula: GA = K (VF2)½ x H/X, based on 10% selection intensity, K = 2.06, VF2 = variance among F2 plants, H = heritability, X = means of F2 population.

The genetic coefficient of variation (VG) was estimated using a formula suggested by Empig et al. (1970): (VG/X) x 100, where VG = VF2- [(VP1)(VP2]½; VF2 is a variance among F2 plants, VP1 is a variance within female parents, and VP2 is a variance within male parents.


Gene Action

Estimates of various components based on individual plants in F1 and F2 gene actions are presented in Table 2. Days to maturity was predominantly controlled by both additive and nonadditive (dominant) gene effects. Therefore, inheritance of days to maturity was associated with both additive and nonadditive gene effects and the dominance effects being more evident in F2 generation. This observation is comparable with that reported by Kumar et al. (2009) where days to maturity was mainly controlled by additive and nonadditive gene effects. In mungbean, Wilson et al. (1986) reported that earliness was controlled by additive gene and dominance or partial dominance. In this study the variance analysis indicated that additive effects were significant in F1, while nonadditive effects were significant in F2 generations, with earliness being dominant to lateness (Table 2).

Examination of individual crosses for days to maturity revealed underlying simple segregation ratio of 3:1 in progenies of late maturing parent (Muria) which matured 90 days, where three parts of the tested plants showed early maturity (<82 days) and one part of the tested plants showed late maturity (>82 days). However, the progeny of the other late maturing parent (Kawi) which matured 95 days, segregated in the ratio of 15:1, where fifteen parts of the plants showed early maturity (<82 days) and one part of the plants demonstrated late maturity (>82 days) (Table 3).

Results of variance analysis showed that plant height was predominantly controlled by both additive and nonadditive gene effects (Table 2). Therefore, inheritance of plant height was associated with both additive and nonadditive gene effects. Similar results were observed by Murty et al. (2009) who found significant effects of additive and nonadditive genes for tallness in some parents and dwarfness in other parent. Rao et al. (2009) reported that dominance effects and duplicate epistatic played an important role in expression of plant height. However, Wilson et al. (1986) stated that mode of gene action for plant height was determined by parent genotypes used in crosses.

Pod number per plant was significantly controlled by additive gene effects. This indicated that inheritance of pod number per plant was associated with additive gene effects. Similar results was reported by Singh and Malhotra (2007). They stated that additive gene effects were significant and played an important role in expression of pod number per plant. Luthra et al. (2009) stated that additive effects on pods per plant were larger


in F2 generation, while in F1 generation the effects were not significant.

Seed size was predominantly controlled by additive gene effects. This means that the additive gene effects were significant and played an important role in expression of inheritance on seed size. Similar results were obtained by Matik et al. (2007), reporting that seed size was apparently controlled by additive gene effects in F1 and F2 generations, with small seeds being dominant to large seeds. Malhotra et al. (2008) on the other hand reported that small seed size was partially dominant over large with predominantly additive gene action.

Examination of individual cross combinations for seed size in F2 generation revealed underlying segregation ratio of 15:1 in each progeny derived from large seed

size parents P3 (Grobogan), P4 (Burangrang) and P5 (Panderman), which had seed size of 19 g, 17 g and 19 g.100-1 seeds, respectively. Each progeny segregated in the ratio of fifteen progenies demonstrated small seed size (<13 g.100-1 seeds) and one progeny had large seed size (>13 g.100-1 seeds) (Table 4).

Seed yield per plant was predominantly controlled by additive gene effects. Similarly plant yield and harvest index were controlled by additive effects (Table 2). This indicated that inheritance of these characters was predominantly controlled by additive gene effects. Analyses of variance indicated that additive gene effects for seed yield and plant yield were greater than those of nonadditive gene effects. Malik et al. (2007) and Rao et al. (2009) reported that additive gene effects were important in the expression of inheritance on seed yield per plant. Singh and Singh (1987) reported that nonadditive gene effects (dominant and epistatic) were mostly important in plant seed yield in F1 generation, while degree of dominance reduced in F2 and F3 generations.

Results of variance analysis indicated that additive gene effects for harvest index were greater than nonadditive gene effects (Table 2). Harvest index was less subjected to environmental variation and consequently had a higher heritability (45.8%) (Table 5). Therefore, selection criteria based on this character would be more useful for yield improvement. Similar result was reported by Ahuja and Chowdhury (1981) and Gupta and Singh (1987). They stated that harvest index had a substantially higher additive variance component than that of nonadditive component. This character is mainly governed by additive genes.

Table 2. Estimates of variance components of seven characters in F1 and F2 soybean progenies, Muneng Experimental Station, dry season of 2014.

CharactersGenera-

tionVariance components Male Female interac-

tion variance (S2mf )Ratio (S2A/S2D)

Male parents (M) Female parents (F)

Days to maturity F1F2

0.000.00

3.11*2.24

2.387.21*

3.250.16

Plant height (cm) F1F2

0.010.03

3.183.08

2.016.31

2.080.20

Pod number per plant F1F2

06112620

2.753.80

1305188

2.053.03

Seed size (g.100-1 seeds) F1F2

87.9**46.5*

4.11*3.27

1.476.23**

2.270.18

Plant yield (g) a F1F2

7812*3202**

68704218**

0.00.0

1.121.39

Seed yield per plant (g) F1F2

2225*1305

1.18371

1265163

1.872.57

Harvest index F1F2

239**438*

2337**1021**

0.01.90

1.892.00

*P<0.05; **P<0.01. aPlant yield is a seed yield plus the weight of all other plant parts.

Table 3. Segregation ratio between earliness and lateness par-ents in F2 progenies of six soybean cross combinations, Muneng Experimental Station, dry season of 2014.

Earlya parents

Late parentsb

P1 P2

Ratioc X2d (3:1) Prob. Ratioc X2d

(15:1) Prob.

P3 20:3 1.755 P>0.10 15:1 0.044 P>0.80

P4 10:5 0.636 P>0.30 17:1 0.019 P>0.90

P5 25:6 0.408 P>0.50 24:3 1.035 P>0.20

Total 55:14 1.349 P>0.20 55:5 0.549 P>0.70

aEarly parents and progenies matured <82 days; bLate parents and progenies matured >82 days; cRatio of early to late maturity prog-enies observed from this study;, dChi-square test of the tested ratio; Prob = probability level.


Heritability and Genetic Advance

Heritability estimates (broad sense) obtained in the F2 are shown in Table 5. The means of heritability estimates of seven characters ranged from 13.0% to 49.3%. Days to maturity had the highest heritability estimate of 49.3% followed by seed size of 47.0%. This indicates that inheritance of days to maturity and seed size in the next generation (F3) are high, and selection to obtain soybean genotypes with early maturity and large seed size in the F3 is relatively easy. Similar results were reported by Abady et al. (2013), who obtained heritability estimates of 46.6% for days to maturity and 43.0% for seed size. Aditya et al. (2013) pointed out that days to maturity and seed size were heritable and they suggested that selection to increase grain yield through days to maturity and seed size should consider plant height and pod number per plant.

Harvest index also demonstrated high heritability estimates with mean value of 45.8% across the six F2 populations used in this study (Table 5). Ahuja and Chowdhury (1981) reported heritability estimates for harvest index of 56.7%. They stated that inheritance of harvest index was quite high, and genotypes showing higher harvest index could produce higher grain yield. Harvest index, therefore, is an important character and this character can be used as a selection criterion in soybean yield improvement program.

Plant height, on the other hand, showed moderate heritabilitity estimate of 33.2% (Table 5). This indicates that inheritance of plant height in the F3 is relatively low. This result is comparable to that observed by Zafar et al (2010), reporting the mean heritability estimates for plant height of 35.0% in the F2 and 37.6% in the F3 plants, while Karasu (2009) observed mean heritability estimate for plant height of only 19.7%. Variation of heritability

estimates in those studies might be mostly due to high differences in environmental conditions affecting high variation among the study results.

Pod number per plant also had a high heritability estimate of 45.5%. This result is comparable with that reported by Arsyad et al. (2006). They found that in F3 progenies of two cross combinations among three sobyean varieties, pod number per plant, seed yield per plant and plant height had high heritability estimates of 57.2%, 53.0% and 39.4%, respectively. While Faisal et al. (2007) found heritability estimate of 45.6% for pod number per plant in the F2 segregating population. Abady et al. (2013) stated that pod number per plant had a high mean heritability estimate, then selection for this character in the next generation (F3) became easier and thus showing a greater response to selection.

In this study, seed yield per plant had a low heritability estimate of only 18.3% (Table 5). This indicates that inheritance of seed yield per plant in the next generation (F3) is relatively small. Therefore, selection for hight yielding genotypes based on seed yield per plant in the F3 generation is relatively difficult. Karasu et al. (2009) found heritability estimate for seed yield per plant in F2 plants of only 19.7% with expected genetic advance of 27.4%. They stated that selection to increase grain yield based on seed yield per plant in the early generation (F2-F3) would not be effective. Selection based on this character should be done in a later generation (F6-F7).

Among seven characters studied in the F2 progenies, plant yield showed the lowest heritability estimate of only 13% (Table 5). This indicates that inheritance of plant yield in the next generation (F3) is small. Sabu

Table 4. Segregation ratio between large seed and small seed parents in F2 progenies of six soybean cross combinations, Muneng Experimental Station, dry season of 2014.

Large seeds parentsa

Small seed parentsb

P1 P2

Ratioc X2d (15:1) Prob. Ratioc X2d

(15:1) Prob.

P3 21:4 1.445 P>0.20 20:3 1.022 P>0.30

P4 12:6 0.612 P>0.30 16:1 0.16 P>0.70

P5 27:9 0.403 P>0.30 23:3 1.032 P>0.40

Total 60:19 1.127 P>0.20 P>0.20 0.878 P>0.50aLarge seeds of parents and progenies >13 g.100-1 seeds; bSmall seeds of parents and progenies < 13 g.100-1 seeds, cRatio of small to large seed size progenies observed from this study;, dChi-square test of the tested ratio, Prob = probability level.

Table 5. Estimates of broad sense heritability of seven quantitative characters in the F2 generation of six soybean crosses, Muneng Experimental Station, dry season of 2014.

CharactersBroad sense heritability estimates among

six F2 populations (%)a Means (%)

1 2 3 4 5 6

Days to maturity

43.0 47.1 59.4 50.2 45.0 51.1 49.3

Plant height 29.8 36.5 40.3 33.9 21.7 37.0 33.2

Pod number per plant

42.2 39.2 47.1 50.0 40.3 54.2 45.5

Seed size 46.5 49.0 38.6 51.3 43.6 53.0 47.0

Plant yield 11.2 16.8 13.0 9.1 12.3 15.6 13.0

Seed yield per plant

16.4 21.6 11.9 20.1 24.5 15.3 18.3

Harvest index

42.8 39.2 47.5 50.6 40.4 54.3 45.8

a1, 2, 3, 4, 5, 6 are six F2 populations developed from six independent cross combinations.


et al. (2009) observed heritability estimate for plant yield in the F3 of only 11.6%, thus selection based on this character would not be effective. Uzun et al. (2013) reported that genotypes which had a high plant yield may not always produce high seed yield.

Estimates of genetic advance of seven characters at 10% selection intensity are shown in Table 6. Genetic advances expected at 10% selection intensity of the seven characters observed in this study ranged from 14.9% to 41.0%. Days to maturity and seed size had the highest expected genetic advances of 41.0% and 38.8%, respectively (Table 6). The genetic advances of these characters were predicted as a substantial gain for one generation of selection obtaining 41% for days to maturity and 38.8% for seed size. This result is comparable to that found by Akhter and Sneller (1996) who obtained genetic advance of 39.7% for days to maturity and 43.1% for seed size. Seed yield per plant and harvest index also showed high expected genetic advance of 35% and 33.6%, respectively. The genetic advance of these characters that would be obtained for one generation of selection was estimated to be 35% for seed yield per plant and 33.6% for harvest index. A similar result was reported by Aditya et al. (2013) who found genetic advance of 45.4% for seed yield per plant and 45.1% for harvest index. This means that genetic progress for seed yield per plant and harvest index were predicted as a substantial gain for one generation of selection obtaining 45.4% and 45.14%, respectively. Parida et al. (2007) reported that genetic advance for seed yield per plant in F2 generation of mungbean was 37.2% and for harvest index was 40.3%. This indicates that genetic progress for seed yield per plant obtained for

one generation of selection was estimated to be 37.2%, while for harvest index was 40.3%.

Pod number per plant and plant height had moderate expected genetic advances of 29.1% and 25.7%, respectively (Table 6). This indicates that genetic progress of pods per plant and plant height was predicted as a substantial gain for one generation of selection obtaining 29.1% and 25.7%, respectively. These results were comparable with the genetic advance of pods per plant and plant height that were considered as moderate.

Among the characters studied, plant yield showed the lowest expected genetic advance of 14.9% (Table 6). This observation was comparable with that reported by Rohman and Husain (2003) who found genetic progress for plant yield of only 11.7%. The lowest expected genetic advance for plant yield was due to its low heritability.

Genetic Variability

Genetic variability of seven quantitative characters observed in the F2 population is shown in Table 7. The mean variability of the seven characters observed in F2 population ranged from 15.6% to 53.5%. Among the characters studied, seed weight per plant, plant height and pod number per plant showed the highest coefficient of variability with the mean values of 53.5%, 49.0%, and 43.2%, respectively. Days to maturity, harvest index, and seed size showed moderate coefficient of variability of 36.5%, 33.6% and 33.0%, respectively, whereas plant yield demonstrated the lowest variability with the mean value of 15.6% (Table 7).

Results of this study showed that days to maturity, seed size, harvest index and pod number per plant had

Table 6. Estimates of genetic advance by using 10% selection intensity of seven quantitative characters observed in F2 generation of six soybean crosses, Muneng Experimental Station, dry season of 2014.

CharactersEstimates of genetic advance (%)a Means

(%)1 2 3 4 5 6

Days to maturity

42.0 48.1 44.5 39.4 32.0 40.0 41.0

Plant height 24.7 25.4 25.3 28.9 23.6 26.3 25.7


22.7 38.0 25.1 24.3 38.7 25.8 29.1

Seed size 37.4 40.1 35.5 39.0 36.4 44.4 38.8

Plant yield 19.1 14.0 10.0 19.8 10.7 16.0 14.9


40.7 35.1 30.9 38.3 43.2 26.0 35.7

Harvest index

27.6 35.0 31.5 41.0 28.5 38.0 33.6

a1, 2, 3, 4, 5, 6 are six F2 populations developed from six independent cross combinations used in this study.

Table 7. Coefficient of genetic variability of seven quantitative characters in F2 generation of six soybean crosses, Muneng Experimental Station, dry season of 2014.

CharactersEstimates of genetic variability (%)a Means

(%)1 2 3 4 5 6

Days to maturity

40.4 38.7 35.4 32.1 42.4 30.0 36.5

Plant height 51.2 44.6 43.8 50.4 54.0 50.0 49.0


48.6 53.1 40.1 37.0 40.0 40.4 43.2

Seed size 35.0 30.1 35.5 29.7 35.2 32.5 33.0

Plant yield 18.7 18.1 17.2 15.3 20.0 24.3 15.6


58.0 55.1 48.7 50.5 54.7 54.0 53.5

Harvest index 35.3 30.8 32.6 33.0 35.9 34.0 33.6

a1, 2, 3, 4, 5, 6 are six populations developed from six independent crosses combination used in this study.


high heritability estimates of 49.3%, 47.0%, 45.8% and 45.5% coupled with high expected genetic advances of 41.0%, 38.8%, 33.6% and 29.1% respectively (Tables 5 and 6). The coefficients of genetic variability of these characters were also quite high with the means of 36.5%, 33.0%, 33.6% and 43.2%, respectively (Table 7). This indicates that inheritance for days to maturity, seed size, harvest index and pod number per plant in the next generation (F3) were high, and selection to obtain high yielding soybean genotypes with early maturity and large seed size in F3 progenies would be relatively easy. Therefore, pod number per plant, harvest index, days to maturity and seed size could be suggested as selection criteria to obtain high yielding soybean genotypes with early maturity and large seed size in the F3 generation.

Seed yield per plant had a low heritability estimate. This indicates that inheritance of seed yield per plant in the next generation (F3) was low. Therefore, yield improvement based on this character is relatively difficult. The yield improvement may be enhanced through selection for harvest index.

Results of this study indicated that in a breeding program for improving soybean production, selection of progenies derived from a cross between low yield, late maturity and small seed size varieties such as Muria and Kawi with those having high yielding, early maturity and large seed size such as Grobogan, Burangrang and Panderman should generate several soybean genotypes demonstrating high yield, early maturiy and large seed size. Therefore, increasing grain yield of soybean varieties such as Muria and Kawi that currently have early maturity and large seed size through improving pod number per plant, harvest index, days to maturity and seed size should be possible.

CONCLUSION

Pod number per plant, seed yield per plant, plant yield and harvest index were predominantly controlled by additive gene effects. Similarly seed size was also controlled by additive gene effects with small seed is dominant to that of large seed size. Plant height was predominantly controlled by both additive and nonadditive gene effects. Similarly days to maturity was due mainly to additive and nonadditive gene effects, with earliness is dominant to that of lateness.

Days to maturity, seed size, harvest index and pod number per plant had high heritability estimates coupled with high expected genetic advance. Therefore, pod number per plant, harvest index, days to maturity and seed size could be suggested as selection criteria to obtain high yielding soybean genotypes with early maturity and large seed size in the F3 generation. It should be possible

to increase grain yield of variety Muria and Kawi that currently have early maturity and large seed size by improving pod number per plant, harvest index, days to maturity and seed size.

ACKNOWLEDGEMENT

This study was funded by the Indonesian Agency for Agricultural Research and Development through the 2013 and 2014 national budget. We deeply thank to Mr Suyamto and his field technicians of Muneng Experimental Station for their support and assistance during the study.

REFERENCES

Abady, S.F. Merkeb & Dilnesaw, Z. (2013) Heritability and path coefficient analysis in soybean genotypes. Journal Environmental Science and water resources, 2(8), 270-276.

Aditya, J.P., Bhartya, P. & Anuradha, B. (2013) Genetic variability, heritability and character association for yield and component character in soybean. Journal Central Europe Agriculture, 12(1), 27-34.

Ahuja, S.L., & Chowdhury, R.K. (1981) Genetic of harvest index in mungbean (vigna radiata). Genetic Agraria, 35, 301-311.

Akhter, M., & Sneller, C.H. (1996). Yield and yield components of early maturing soybean genotypes in Mid-South. Crop Science, 36, 877-882.

Arsyad, Ali, N. & Ghafoor, A. (2006) Character association and path coefficient analysis in soybean (Glycine max (L.) Merrill). Pakistan Journal of Botany, 38(1), 121-130.

Chand, N., Viswakarma, S.R. & Verma O.P. (2008) Worth of genetic parameters to sort out new elite barley lines over heterogenous environment. Barley Genetic Newsletter, 38, 10-13.

Empig, L.T., Lantican, R.M. & Escuro, P.B. (1970) Heritability estimates of quantitative characters in mungbean (Phaseolus aureus Roxb.). Crop Science, 10, 240-242.

Faisal, M.A.M., Ashraf, M. & Ghafoor, A. (2007) Assessment of genetic variability, correlation and path analysis for yield and its component in soybean. Pakistan Journal of Botany, 39(2), 405-413.

Gravois, K.A. & Mc. New, R.W. (1993) Genetic relationship among and selection for rice yield components. Crop Science, 33, 249-252.

Gupta, N.P. & Singh, R.B. (1987) Genetic divergence for yield and its components in greengram. Indian Journal of Genenetic and Plant Breeding, 30, 212-221.

Hakim, L., Suyamto & Paturohman, E. (2014) Genetic variability, heritability and expected genetic advances of quantitative characters in F2 progenies of soybean crosses. Indonesian Journal of Agricultural Science, 15(1), 11-16.

Imrie, B.C., Rateliff, D. & Eerens, J.P. (1987) Analysis of gene action in crosses between early and late maturing mungbean, Proceedings of second International Mungbean Symposium AVRDC, Taiwan. P, 146-151.

Indonesian Legumes and Tuber Crops Research Instititue. 2005. Description of Legumes and Tuber Crops Varieties, ILETRI, Malang, East Java, 154p.

Karasu, A.A., Goksoy, T. & Turan, Z.M. (2009) Interrelationship of agronomical characteristic in soybean grown in difference environemnt. International Journal of Agricultural and Biology, 1(1), 85-88.


Kumar, M.K. & Kamendra, S. (2009) Studies on genetic variability. Character association and path coefficient for seed yield and its contributing traits in soybean. Legume Research Journal, 32(1), 70-73.

Luthra, O.P., Aaron, N.O. & Chaudhury, B.D. (2009) Genetic analysis for metric traits in soybean (Glycine max (L.) Merrill). Haryana Agricultural University Journal of Research, 9, 19-24.

Malhotra, R.S. Gupta, P.K. & Arora, N.D. (2008) Diallel analysis over environments in mungbean. Indian Journal of Genenetic and Plant Breeding, 38, 64-67.

Malik, B.P., Gupta, P.K. & Singh, V.P. (2007) Detection of epistatic, additive and dominance variation in soybean. Indian Journal of Genetic and Plant Breeding, 40, 119-128.

Murty, B.K., Patel, G.I. & Jalsani, B.G. (2009) Gen action and heritability estimate of some quantitative traits in mungbean. Indian Research Journal, 2, 1-4.

Parida, D & Singh, D.P. (2007) Association, heritability and genetic advance in the F2 generation of wide and varietal crosses of greengram. Madras Agricultural Journal, 71, 35-38.

Rao, S.S., Singh, S.P. & Rao, S.K. (2009) Estimation of additive, dominance, digenic epistatic interaction effects for yield and its components in soybean. Legume Research Journal, 7, 8-13.

Rahman, M.M., & Hussain, A.S.M. (2003) Genetic variability, correlation and heritability estimate in mungbean. Asian Journal of Plant Science 2, 1209-1211.

Sabu, K.K., Abdullah, M.Z. & Lin, I.S. (2009) Analysis of heritability and genetic variability of agronomically important traits in oriza sativa x oriza rupipagon crosses. Agronomy Research Journal, 7(1), 97-102.

Singh, TP & Singh, K.B. (1987) Mode of inheritance and gene action for yield and its components in phaseolus aureus. Canadian Journal of Genetics and Cytology, 14, 517-525.

Singh, T.P. & Malhotra, R.S. (2007) Components of genetic variance and dominance pattern for some quantitative traits in soybean. Indian Agricultural Journal, 71, 233-242.

Stuber, C.W. (1970) Estimation of genetic variances using inbred relatives. Crop Science, 10, 129-135.

Uzun, B., Engin, Y. & Furat, S. (2013) Genetic advance, heritability and inheritance in determinate growth habit of sesame. Australian Journal of Crop Science, 7(7), 978-983.

Weber, C.R. & Moorthy, B.R. (2006) Heritable and nonheritable rerelationship and variability of agronomic characters in the F2 generation of soybean crosses. Agronomy Journal, 4, 202-206.

Wilson, D., Mercy, S.T. & Nayar, N.K. (1986) Combining ability in greengram (Vigna radiata). Indian Journal Agricultural Science, 55, 665-670.

Zafar, I., Arshad, M., Ashraf M. & Waheed, A. (2010) Genetic divergence and correlation studies of soybean (Glycine max (L.) Merrill) genotypes. Pakistan Journal of Botany, 42(2), 971-976.



COMPLETE RUMEN MODIFIER SUPPLEMENTATION IN CORN COB SILAGE BASAL DIET OF LAMB REDUCES METHANE EMISSION

Suplementasi Complete Rumen Modifier dalam Pakan Silase Tongkol Jagung untuk Menurunkan Emisi Metana pada Domba

Dwi Yulistiania*, Wisri Puastutia, Budi Haryantoa, Agung Purnomoadib, M. Kuriharac and Amlius Thaliba

aIndonesian Research Institute for Animal ProductionPO Box 221, Bogor 16002, West Java, Indonesia

bFaculty of Animal and Agricultural Sciences, Diponegoro University, Semarang 50275, Central Java, IndonesiacNational Institute of Livestock and Grassland Science, Tsukuba Norin-Kenkyu Danchi, PO Box 5, Ibaraki Japan


Submitted 3 April 2017; Revised 10 May 2017; Accepted 18 May 2017

ABSTRACT

Feeding animal with fibrous materials such as corn cob will emit methane. Complete rumen modifier (CRM) is an improved feed additive comprised a mixture of Sapindus rarak, sesbania, albizia leaves and minerals that functions as a methane inhibitor. The study aimed to determine the effect of CRM supplementation on the feed intake, nutrient digestibility, rumen fermentation, methane emission and growth of lambs. The experiment was designed in a complete randomized block, four levels of CRM (0%, 1%, 2%, and 3%), six group of 24 male lambs per treatment based on the body weight. Basal diet used was corn cob silage ad libitum and concentrate (500 g/day) as a supplement. The results showed that CRM supplementation did not affect feed consumption and average daily gain, but significantly decreased the dry matter, as well as organic matter and protein digestibility. The neutral detergent fiber (NDF) and acid detergent fiber (ADF) digestibility linearly decreased with increasing level of CRM. Ruminal pH, ammonia concentration and volatile fatty acid (VFA) concentration were not affected by the CRM supplementation. Methane production expressed in kJ/MJ gross energy (GE) or digestible energy (DE) intake significantly decreased by 32% at the 2–3% CRM supplementation and reduced by 39% when methane production was expressed in g/kg digested NDF. It can be concluded that 2% CRM supplementation in the corn cob basal diet did not affect nutrient intake and growth rate of the lamb, as well as rumen fermentation. The study suggests that CRM is an environmentally friendly feed additive for lamb.

[Keywords: complete rumen modifier, supplementation, corn cob silage, lamb, methane]

ABSTRAK

Pemberian pakan berserat seperti tongkol jagung pada domba dapat menghasilkan gas metana sebagai salah satu gas rumah kaca. Complete rumen modifier (CRM) merupakan pakan aditif yang mengandung buah lerak, daun sesbania dan albizia, serta campuran mineral dan vitamin yang berfungsi sebagai inhibitor metana. Penelitian bertujuan mengetahui pengaruh suplementasi CRM terhadap konsumsi pakan, kecernaan nutrisi pakan, fermentasi rumen,

emisi metana, dan pertumbuhan domba. Penelitian menggunakan rancangan acak kelompok lengkap dengan empat level CRM (0%, 1%, 2%, 3%) dan enam kelompok domba (masing-masing kelompok 24 ekor), berdasarkan bobot badan. Domba diberi pakan dasar silase tongkol jagung ad libitum dan konsentrat 500 g/hari. Hasil penelitian menunjukkan bahwa suplementasi CRM tidak berpengaruh terhadap konsumsi pakan dan pertambahan bobot badan harian domba, tetapi menurunkan kecernaan bahan kering, bahan organik, dan protein. Kecernaan serat detergen netral (NDF) dan serat detergen asam (ADF) menurun secara linier seiring dengan meningkatnya suplementasi CRM. pH rumen, konsentrasi amonia, dan VFA tidak dipengaruhi oleh suplementasi CRM. Produksi metana dalam kJ/MJ konsumsi energi kasar (GE) atau energi tercerna (DE) turun 32% pada suplementasi CRM 2–3% dan berkurang 39% jika dihitung berdasarkan g/kg serat detergen netral tercerna. Dapat disimpulkan bahwa suplementasi CRM 2% pada pakan dasar silase tongkol jagung tidak berpengaruh terhadap konsumsi pakan, pertumbuhan domba, dan fermentasi rumen. Oleh karena itu, CRM dapat disarankan sebagai pakan aditif pada domba.

[Kata kunci: complete rumen modifier, suplementasi, silase tongkol jagung, domba, metana]

INTRODUCTION

The major constraint in improving ruminant production in Indonesia is discontinuous availability of forage feed throughout the year, particularly in a dry season when the forage sources are limited. Utilization of agricultural by-products such as corn cob is usually practiced to overcome this problem. However, corn cob is unpalatable and easily contaminated by toxic fungi such as Aspergillus flavus. This contamination could be solved by ensiling, which is a simple and an applicative preservation method to small scale farmers. Ensiled corn cob is very palatable as shown by a higher feed consumption of sheep fed on ensiled corn cob basal diet than that fed on grass basal diet (Yulistiani and Puastuti


2012). Although it is palatable, the fiber content of corn cob silage was high (Yulistiani et al. 2012a), which is potential in producing methane during fermentation in the rumen.

Methane emission by ruminants has negative effects on the animal and causes greenhouse effect to the environment. Methane which is an end product of fermentation process of feed is formed through methanogenesis. Methanogenesis cause 2–12% energy loss of the digested energy depending on diet type (Johnson and Johnson 1995). Methane emission from enteric fermentation contributes 25% to the total global greenhouse gases from agriculture (Oliver et al. 2005).

Previous studies showed that saponin feed additive is effective to inhibit methanogenesis through defaunation mechanism on protozoa population. Saponin is a plant bioactive compound and can be obtained from Sapindus spp. (Hess et al. 2003), tea (Mao et al. 2010; Zhou et al. 2011), Carduus, Knautia, sesbania leaves and fenugreek seed (Goel et al. 2008), Albizia lebbeck (Sirohi et al. 2014), and mangosteen peel (Sineenart et al. 2016). Saponin in Sapindus rarak was effective as a defaunator and methanogenesis inhibitor (Thalib 2004; Wina et al. 2005). Supplementation of crude extract of S. rarak in the diet increased average daily gain (ADG) of sheep by 40% (Wina et al. 2005b).

Complete rumen modifier (CRM) is a mixed feed additive formulated from S. rarak, sesbania and albizia with the addition of minerals and vitamins to promote microbial growth. The formulae have been developed at the Indonesian Research Institute for Animal Production (Thalib et al. 2010) based on the results of serial experiments. As a single feed additive, S. rarak (seed pericarp) was able to reduce protozoa population and increase the growth of sheep by 44% (Thalib et al. 1996). It also decreased methane production and protozoa population, but enhanced propionate production (Thalib 2004). Those findings indicated that saponin from S. rarak is effective as a protozoal defaunator and methanogenesis inhibitor.

A mixture of S. rarak with minerals and vitamins (microbial growth factors, MGF) decreased protozoa population and increased bacterial population and rice straw digestibility (Thalib et al. 1998). In in vivo study, supplementation of S. rarak and MGF mixture in grass basal diet increased the growth of sheep and feed digestibility (Thalib 2002). To increase protein and saponin contents of ground S. rarak seed pericarp, the finely ground sesbania and albizia leaves, respectively, containing 8.4% and 12.9% saponin and 26.3% and 24% protein are added (Thalib et al. 2010). This mixture was then added with vitamin and minerals to formulate CRM. Minerals and vitamins have a function as a bacterial

growth factor, fiber digestion stimulator and CO2 anti-reductance. Therefore, CRM serves as a defaunator, methanogenesis inhibitor, bacterial growth factor, fiber digestion stimulant and CO2 anti-reductance.

The use of CRM as a feed additive in rice straw basal diet was reported to reduce enteric methane production, increase average daily gain and improve feed efficiency in sheep (Thalib et al. 2010). In dairy cow fed on grass basal diet, CRM supplementation reduced methane production by 14% and improved milk quality (Thalib et al. 2011). In dairy goat diet, supplementation of CRM mixed with Calliandra increased milk production and production efficiency of Etawah cross bred goat and reduced methane emission (Sukmawati et al. 2011). Utilization of CRM as a methane inhibitor and stimulator of fiber digestibility also occurred on grass and rice straw basal diet. In vitro study on rumen fluid of sheep fed on corn cob basal diet supplemented with CRM showed that protozoa population and methane production were lower than those of the control (Yulistiani et al. 2012b). Currently, no information is available on in vivo study of CRM supplementation in corn cob basal diet for sheep and its effect on methane emission and growth of lamb. The objective of this study was to determine the effect of CRM supplementation on nutrient digestibility, rumen fermentation, methane emission, and growth of lamb fed on corn cob silage basal diet.


The study consisted of two experiments. The first experiment was conducted in the research station of the Indonesian Research Institute for Animal Production (IRIAP), Bogor, to measure the effect of CRM supplementation in corn cob basal diet on growth of lamb, nutrient digestibility and rumen fermentation. The second experiment was conducted in the field laboratory of the Faculty of Animal and Agricultural Sciences, Diponegoro University, Semarang to measure methane production of lamb fed on corn cob basal diet and supplemented with CRM.

Feeding Trial and Growth Study

Feed Preparation

Corn cob was obtained after the grain was removed from corn field in Sukabumi, West Java. The cob was ground into 1 cm mesh (similar size to corn grain) and stored in plastic bags. Corn cob silage was prepared by mixing 100 kg corn cob (94% dry matter, DM) with 2 kg finely ground maize (2% of ground corn cob DM) as a source

35Complete Rumen Modifier Supplementation … (Dwi Yulistiani et al.)

of fermentable carbohydrate, then sprayed with water at 60% of corn cob DM to obtain a mixture DM of 30-40%. The mixture was thoroughly mixed and transferred into black plastic bags. The bag (15 kg treated straw per bag) was carefully trampled to remove the air, tightly sealed and stored for at least 3 weeks. After the curing period, the corn cob silage was ready for feeding.

CRM was prepared using S. rarak seed pericarp, sesbania and albizia leaves (Thalib 2004). The seed pericarp was separated from seed, dried under sunshine, finely ground and kept for treatments. Similarly, sesbania and albizia leaves were dried and finely ground. The CRM was formulated by mixing finely ground S. rarak, sesbania and albizia leaves with some microminerals and vitamins. The 1%, 2% and 3% CRM contained saponin of about 4.56%, 9.12% and 13.68%, respectively.

Animals and Diets

A digestibility study was conducted using 24 male lambs of Sumatra composite breed sheep with an average body weight of 14.8 + 1.66 kg. The lambs were divided into four groups in a completely randomized design. The lambs were kept in individual pen during the experimental period (13 weeks) and fed corn cob silage as a basal diet with four supplemental treatment diets. The diet treatments were the level of CRM supplementation in concentrate diet which consisted of 0% (control), 1%, 2%, and 3% CRM. The concentrate was formulated in iso-nitrogenous and iso-energetic containing calculated crude protein (CP) of 18% and metabolizable energy (ME) of about 9 MJ/kg. The concentrate was offered at 500 g/head/day while corn cob silage offered ad libitum. The concentrate consisted of coconut meal, rice bran, ground corn grain, soybean meal, molasses, urea, salt and mineral mix. Water was available at all time. The chemical composition of feed ingredients used in experiment is presented in Table 1.

Digestibility Trial and Growth Study

The growth trial was conducted for 13 weeks included one week adaptation period. Lambs were weighed on

weekly basis to observe the growth rate. Feed offered and refusal were weighed daily before morning feeding to measure daily feed intake. Feed conversion ratio was calculated from daily feed intake divided by average daily gain (ADG). Protein conversion ratio was calculated from daily protein intake divided by ADG. The energy conversion ratio is the daily gross energy intake divided by ADG. At the end of feeding trial, the lambs were placed in metabolic crates for digestibility measurement.

The digestibility trial consisted of 14 days for adaptation period, 7 days for feces and urine collection, and 1 day for sampling of rumen fluid. During the collection period, daily feed intake and refusal, fecal and urine output of the individual lamb were measured. Urine and fecal samples were separated by the separator attached below each metabolic crate. Daily fecal output was collected from individual lamb before morning feeding. Each representative portion (10% of total fecal production) of fecal sample was oven-dried at 60oC for 48 hours. At the end of collection period, the feces were pooled for individual lamb and 10% was sub-sampled, ground passed through 1 mm sieve and stored in the freezer for analyses. Total urine produced daily per lamb was collected in a plastic bucket containing 100 ml of 10% sulfuric acid to maintain the pH below 3 to inhibit microbial activity and N losses. The sample was collected every morning and after recording the volume, the urine was mixed thoroughly. A representative of urine sample was collected and kept in the freezer and pooled for each animal at the end of collection period for urine-N analyses.

On the final day of digestibility trial, rumen fluid from individual lamb was sampled using a stomach tube at 0 and 4 hours after morning feeding. Rumen fluid pH was measured immediately after sampling using a portable pH meter. One drop of concentrated sulfuric acid was then added (for stopping microbial activity) and the fluid was later centrifuged at 3000 g for 10 minutes. After centrifugation, 10 ml of each supernatant was kept in air tight container and stored at –20oC for further analyses of rumen ammonia N (NH3-N) and volatile fatty acid (VFA).

Methane Emission Measurement

Measurement of methane emission was conducted in the field laboratory of Diponegoro University, Semarang. Sixteen lambs with an average body weight of 15.0+1.53 kg were kept in individual pen. The lambs were divided into four groups in which each lamb in each group was fed one of the diet treatments. The diet treatments were

Tabel 1. Chemical analysis of the feed used in the experiment.

Feed ingredientChemical composition (% dry matter) GE

(kcal/kg)CP OM NDF ADF Lignin

Corn cob silage 2.77 97.6 79.9 40.60 8.1 4186

Concentrate 19.20 90.0 27.2 17.53 7.8 3994CP = crude protein; OM = organic matter; NDF = neutral detergent fiber; ADF = acid detergent fiber; GE = gross energy.


the same composition to feeding trial study. Lambs were adjusted to the diet treatment for 2 weeks to achieve dry matter intake (DMI) with a proportion of concentrate and corn cob silage similar to feeding trial study. During the adaptation period, feed offering and refusal were recorded daily to measure feed intake. At the end of adaptation period, methane emission of the lamb was measured using face mask method as described by Kawashima et al. (2001). The face mask was connected to a methane analyzer (Horiba, Japan) for determining methane concentration and airflow meter for measuring total air volume. The measurement was done for 10 minutes at 3-hour intervals for 2 days. Methane emission values were expressed in several units, as L/day, L/kg DMI, kJ/MJ GE intake, kJ/MJ DE intake, g/kg digested NDF. The value of digested NDF was calculated by multiplying NDF intake in methane study and NDF digestibility obtained from digestibility trial. Similarly, methane production efficiency was calculated from methane production (L/day obtained from methane measurement study) divided by ADG (g/day, obtained from growth trial). The factor used for converting units of methane production GE (kJ/MJ) and DE (kJ/MJ) were 1L methane = 0.716 g = 39.54 kJ (Ramin and Huhtanen 2013).

Chemical Analyses

Feeds, residues and feces were analyzed for DM, OM and crude protein (CP) contents according to AOAC

(1990). The fiber components (NDF and ADF) were determined according to van Soest et al. (1991). NH3-N was determined by Conway method (Conway and Byrne 1933). Concentration of rumen VFA was determined using gas chromatography (GC-14A, Shimadzu Corporation, Japan, Tokyo) fitted with a flame ionization detector. Separation was carried out using a stainless steel column packed with GP 107, SP 1,000/L % H3PO4 on Chromosorb WAW (100/120 mesh).

Statistical Analyses

Data were analysed using general linear model (GLM) for randomized complete block design (SAS 2004) and differences among means were compared using Duncan’s multiple range test. All data were analysed for linear (L), quadratic (Q) and cubic (C) responses to CRM level using Orthogonal Polynomial contrast of SAS 9.1 (SAS 2004).

RESULTS

Feed Consumption, Lamb Growth and Nutrient Digestibility

Feed consumption and ADG of lambs are presented in Table 2. DM consumption was not significantly different between treatments. The average of total DMI (g/day) and DMI per body weight were 698.6 g/head/day and 3.81%, respectively. CP consumption was cubically affected by

Table 2. Feed consumption, average daily gain and feed conversion of lambs fed on silage basal diet supplemented with different levels of complete rumen modifier (CRM).

ParameterCRM levels (%)

S.E.MEffects

0 1 2 3 L Q C

Total DMI (g/head/day)) 640.2 732.9 696.4 724.8 33.459 NS NS NS

DMI/BW (%) 3.78 3.92 3.72 3.84 0.158 NS NS NS

Silage intake (g/head/day) 246.0 316.6 283.1 308.6 30.868 NS NS NS

Proportion of silage intake (%) 38.15 42.64 39.83 41.85 2.581 NS NS NS

CP intake (g/head/day) 73.95b 83.32a 70.6b 82.21a 2.061 NS NS *

CP intake/BW0.75 (g/kg BW0.75) 8.92a 9.45a 8.18b 9.47a 0.241 NS NS *

GE intake (kkal/day) 2757.7b 3369.6a 3222.1a 3341.9a 124.244 * NS NS

GE intake/BW0.75 (kg BW0.75) 330.9b 379.0a 370.2a 381.9a 10.279 * NS NS

ADG (g/head/day) 84.417 92.2 87.867 97.4 6.773 NS NS NS

Feed conversion 7.85 7.97 8.2 7.47 0.489 NS NS NS

CP conversion ratio 0.925 0.907 0.837 0.851 0.065 NS NS NS

Energy conversion ratio 34.43 36.66 38.02 34.52 2.553 NS NS NSDifferent superscripts in one row indicate significantly different (P<0.05); L= linear; Q = quadratic; C = cubic; NS = non significant; * significant effect at P<0.05; SEM = standard error mean; CRM = complete rumen modifier; DMI = dry matter intake; BW = body weight; CP = crude protein; GE = gross energy; ADG = average daily gain.


Body weight (kg)23

22

21

20

19

18

17

16

15

14

CRM supplementation. CP consumption at 1% CRM was similar to control, then decreased at 2% CRM and increased again at 3% CRM. CP intake of lambs at 2% CRM was significantly lowest. On the other hand, energy consumption linearly increased with an increasing level of CRM supplementation. GE consumption of control was significantly lower compared to that of 1%, 2% and 3% CRM rates. However, there were no significant differences among 1%, 2% and 3% CRM rates. The ADG was not significantly affected by CRM supplementation with the average ADG of 90 g/head/day. Similarly, feed conversion ratio (DMI/ADG), protein conversion ratio (CP intake/ADG) and energy conversion ratio (energy intake/ADG) were not significantly different between treatments with average values of 7.87, 0.88 and 35.91, respectively.

Growth pattern of lambs during experiment is presented in Figure 1. The growth of lambs was still in linear stage, in which the growth increased with an increasing time of feeding. From the equation of lamb growth pattern, it shows that the slopes of 1% and 3% CRM rates were

higher than those of 0% and 2% CRM rates. This indicates that the growth rates of lambs received 1% and 3% CRM were faster than those with 0% and 2% CRM supplementation.

Nutrient digestibility of lambs fed on corn cob silage basal diet supplemented with CRM is presented in Table 3. DM digestibility significantly decreased at 3% CRM supplementation and OM digestibility linearly decreased with increasing levels of CRM supplementation. However, the decreased OM digestibility at 3% CRM supplementation was only significantly lower than the control. The decreased OM digestibility was about 12%. On the other hand, CP digestibility was significantly lower at 2% and 3% CRM supplementation than that of the control and 1% CRM supplementation. There was no significant difference between 2% CRM and 3% CRM treatments on CP digestibility. Energy digestibility linearly decreased with an increasing level of CRM supplementation. The lowest energy digestibility was at 3% CRM supplementation.

Fig.1. Growth pattern of post-weaning male lambs fed on corn cob basal diet supplemented with different levels of complete rumen modifier (CRM).

Table 3. Means of nutrient digestibility of lambs fed on silage basal diet supplemented with different levels of complete rumen modifier (CRM).


S.E.MEffects

0 1 2 3 L Q C

Dry matter (%) 55.48a 51.019ab 51.90ab 49.23b 1.531 NS NS NS

Organic matter (%) 57.14a 52.86ab 54.00ab 50.38b 1.507 * NS NS

Crude protein (%) 57.36a 54.18a 47.74b 52.12b 2.736 NS NS NS

Neutral detergent fiber (%) 45.80a 47.83a 45.26a 38.53b 1.614 * NS NS

Acid detergent fiber (%) 39.23a 33.54ab 27.45b 31.72b 2.196 * NS NS

Energy (%) 56.59a 51.6ab 53.22ab 49.88b 1.501 * NS NSDifferent superscripts in one row indicate significantly different (P<0.05); L = linear; Q = quadratic; C = cubic; NS = non significant; * significant effect at P<0.05; SEM = standard error mean; CRM = complete rumen modifier.

0% CRM1% CRM2% CRM3% CRM

(0% CRM) y = 0.5958x + 12.591 (R2 = 0.9934)(1% CRM) y = 0.7041x + 12.972 (R2 = 0.9906)(2% CRM) y = 0.6308x + 13.059 (R2 = 0.9924)(3% CRM) y = 0.7032x + 12.633 (R2 = 0.9849)

Time (week)0 2 4 6 8 10 12


Rumen Fermentation

Rumen pH and rumen ammonia (NH3-N) and VFA concentration of rumen fluid taken at 0 and 4 hours after feeding are shown in Table 4. The rumen pH either taken at 0 or 4 hours after feeding was not significantly different between treatments. The rumen pH decreased at 4 hours after feeding. Similarly, rumen ammonia (NH3-N) concentration was not significantly different between treatments either at 0 or 4 hours after feeding. In contrast to rumen pH, the rumen NH3-N concentration increased at 4 hours after feeding, from 7.04 mg/100 ml at 0 hour to 17.50 mg/100 ml at 4 hours after feeding.

Total VFA production at 0 and 4 hours after feeding was not significantly different between treatments, except for acetic acid production at 4 hours after feeding, linearly and quadratically affected by CRM supplementation. At 1% CRM supplementation, acetic

acid proportion increased, while at 2% and 3% CRM supplementation, its proportion decreased but it was not significantly different to the control.

Methane Emission

Methane emission either in L/day or in L per DMI was not significantly affected by CRM supplementation rates (Table 5). However, methane emission expressed in kJ/MJ energy intake (GE or DE) at 2% CRM supplementation showed the significantly lowest value. Similarly methane emission in g/kg digested NDF of 2% CRM supplementation was significantly the lowest.

DISCUSSION

The DMI was not affected by CRM supplementation with the average of 3.8% of body weight (BW) (Table 2). This

Table 4. Means of rumen pH, ammonia (NH3-N) concentration, and volatile fatty acid (VFA) taken at 0 and 4 hours after feeding from lambs fed on corn cob basal diet supplemented with complete rumen modifier (CRM).

Parameter Time (h)CRM levels (%)

SEMEffects

0 1 2 3 L Q CpH 0 7.16 6.94 7.12 7.03 0.008 NS NS NS

4 6.22 6.11 6.24 6.15 0.018 NS NS NSNH3-N (mg/100 ml) 0 6.71 7.88 6.89 6.68 0.546 NS NS NS

4 18.97 19.65 15.90 15.48 3.600 NS NS NSVFA (mmol) 0 123.60 103.30 105.60 110 7.964 NS NS NS

4 119.50 146.90 122.40 116.30 8.864 NS NS NSMolar proportion (%)Acetate 0 0.723 0.743 0.726 0.725 0.006 NS NS NS

4 0.648b 0.665a 0.621b 0.618b 0.009 * * NSPropionate 0 0.148 0.158 0.161 0.164 0.007 NS NS NS

4 0.204 0.200 0.222 0.204 0.011 NS NS NSButyrate 0 0.087 0.072 0.073 0.080 0.009 NS NS NS

4 0.122 0.114 0.119 0.152 0.017 NS NS NSOthers VFA 0 0.041 0.026 0.039 0.031 0.003 NS NS NS

4 0.025 0.019 0.037 0.025 0.008 NS NS NSAcetate:propionate ratio 0 3.93 4.58 3.64 4.42 0.223 NS NS NS

4 3.25 3.22 3.02 2.48 0.129 NS NS NS

Different superscripts in one row indicate significantly different (P<0.05); L = linear; Q = quadratic; C = cubic; NS = non significant; * significant effect at P<0.05; SEM = standard error mean; CRM = complete rumen modifier; VFA = volatile fatty acid; others VFA included isobutyric, valeric and isovaleric acid.

Table 5. Methane emission of lambs fed on corn cob silage basal diet supplemented with complete rumen modifier (CRM).


S.E.MEffects

0 1 2 3 L Q CMethane L/day 33.49 31.44 26.31 32.25 2.721 NS NS NSMethane L/kg DMI 50.76 46.49 39.31 48.49 3.780 NS NS NSMethane kJ/MJ GEI 84.17a 77.40a 57.03b 80.17a 5.064 NS NS NSMethane kJ/MJ DEI 159.10a 141.40a 107.20b 154.10a 5.870 NS NS NSMethane g/kg digested NDF 197.37ab 177.50b 124.50c 222.60a 11.459 NS NS NS

Different superscripts in one row indicate significantly different (P<0.05).


value was comparable to a previous study reported by Yulistiani et al. (2012a) where total feed consumption of lambs fed on corn cob silage basal diet and supplemented with concentrate was 3.8% of BW. This value was higher than the total feed consumption supplemented with CRM for lambs fed on fermented rice straw basal diets, with DMI of 3.5% (Thalib et al. 2010). The nonsignificant effect of CRM supplementation on DMI in the current study indicated that CRM supplementation did not affect palatability of the diet. The implication was saponin in CRM derived from S. rarak, sesbania and albizia did not affect palatability of the diet. Similar results of mangosteen peel saponin supplementation, containing 11.3% crude saponin, did not affect DMI either mixed with or without garlic to rice straw basal diet (Manasri et al. 2012). In addition, Aazami et al. (2013) reported that DMI was not affected by commercial saponin extracted from Quillaja saponaria. Although energy intake was significantly increased by CRM supplementation (Table 2), the energy digestibility decreased significantly at 3% CRM supplementation. This might be due to the decrease in fiber digestibility at 3% CRM diet (Table 3).

Compared to the control treatment, only a higher rate of CRM supplementation (3%) reduced NDF digestibility, whereas ADF digestibility decreased at 2% CRM supplementation (Table 3). Reduction of fiber digestibility (NDF and ADF) could be due to the decrease in protozoa population as reported by Yulistiani et al. (2012b) where protozoa population decreased linearly with increasing CRM supplementation rates. Protozoa excreted enzyme to digest fiber, therefore, fiber digestibility in the rumen decreased if protozoa population decreased (Wina 2012). Furthermore, Wang et al. (2000) reported that steroidal saponins inhibited rumen cellulolytic bacteria and ruminal fungi thereby decreasing fiber digestibility. Similar findings were reported by Wina et al. (2005a) in in vitro study using S. rarak extract and by Manasri et al. (2012) using mangosteen supplementation containing saponin where NDF and ADF digestibility decreased. On the other hand, saponin supplementation did not affect nutrient digestibility on tropical grass hay basal diet (Abreu et al. 2004; Wang et al. 2009) and on fermented rice straw basal diet (Thalib et al. 2010). Results from various studies showed that the effect of saponin supplementations on nutrient digestibility, particularly fiber digestibility was not consistent, depending on saponin plant sources and types of basal diets.

The growth of lambs was not affected by CRM supplementation in diets. The ADG of lambs was 90.5 g/head/day (Table 2). However, other studies showed the increase in growth rate of lambs fed on CRM supplemented diet (Thalib et al. 2010) and the increase in growth rate of kids fed on tea seed or tea seed saponin

extract supplemented diet (Kumar et al. 2016). The ADG of lambs in the current study was higher (90.5 g/head/day) than ADG (71.4 g/head/day) reported by Thalib et al. (2010) in lamb fed on fermented rice straw basal diet supplemented by CRM. This difference might be due to the difference in diet qualities and feed consumption. Similar to the current study, Mao et al. (2010) did not detect any significant increase in body weight gain of lambs fed on Chinese wild rye basal diet supplemented by tea saponin either alone or mixed with soybean oil.

Ruminal pH in all diets either at 0 or 4 hours after feeding was not affected by CRM supplementation. Although at 4 hours after feeding the ruminal pH decreased which was caused by diet just after feeding, the pHs of all diets were the ideal range for rumen microbial growth and activity (pH 6-7). Similar to ruminal pH, ruminal ammonia (NH3-N) concentration was not affected by CRM supplementation. These results were supported by previous study by Thalib et al. (2010) on CRM supplementation in fermented rice straw basal diet, and Hess et al. (2004) on Sapindus saponaria supplementation in tropical grass hay basal diet.

In the present study, total VFA production was not affected by CRM supplementation, either at 0 or 4 hours after feeding. This result was similar to previous studies (Pen et al. 2006, 2007; Guo et al. 2008; Holtshausen et al. 2009). On the other hand, Lovet et al. (2006) reported the reduction of total VFA production due to saponin supplementation.

CRM supplementation did not affect molar proportion of VFA which its value was similar in all diets except for acetic acid at 4 hours after feeding. The effect of saponin supplementation on VFA production is diet dependent. Supplementation of saponin from Y schidigera in barley grain diet increased total VFA production, while in lucerne hay diet it reduced VFA production (Wang et al. 2000). Moreover, Cardozo et al. (2005) reported that in high concentrate diet, ruminal pH affected VFA profile due to saponin supplementation. At pH 5.5 saponin supplementation increased molar proportion of propionate and reduced proportion of acetate, whereas at pH 7 no effect was observed. In the current study, either total VFA or VFA proportion was not affected by CRM supplementation. This indicated that CRM supplementation did not have an adverse effect on rumen fermentation. Similar results have been shown by Thalib et al. (2010) where CRM supplementation in fermented rice straw basal diet increased proportion of acetate. Results of Thalib et al. (2010) and the present study disagreed to most studies which concluded that saponin supplementation increased proportion of propionate and reduced acetate, butyrate, and branched chain fatty acid (Castro-Montoya et al. 2011; Pilajun and Wanapat


2011; Anantasook et al. 2014; Norrapoke et al. 2014). It seems that saponin was able to change the pattern of VFA production by increasing proportion of propionic acid and decreasing ratio of acetic to propionic acids. The higher proportion of propionic acid might be due to the lower production of acetic and butyric acids, which are protozoal fermentation products (Wina 2012). Patra and Saxena (2012) reviewed the effect of saponin on VFA composition and concluded that the inconsistency of saponin effects among studies was attributed by the type of diets and saponin sources.

In the present study, CRM supplementation in in vivo study did not significantly reduced methane production when expresses as production L/day. However, energy loss through methane relative to GE and DE intake significantly decreased at 2% CRM supplementation by 32.2% and 32.6%, respectively. Similarly methane released relative to digested NDF significantly decreased by 36.9% at 2% CRM supplementation (Table 5). Results of the present in vivo study confirmed the finding of in vitro study (Yulistiani et al. 2012a) that reduction in protozoa population reduced methane production. Thalib et al. (2010) also reported that CRM supplementation (combination of S. rarak and Acetoanaerobium noterae) reduced methane production by 24% in sheep fed on fermented rice straw basal diet. The results of the current study and previous studies reported by Sukmawati et al. (2011), Thalib et al. (2004; 2010) and Wina et al. (2006) indicated that saponin from S. rarak was able to be used as a methane inhibitor. Similar to S. rarak, tea saponin could also decreased methane production by 27.7% in growing lambs (Mao et al. 2010).

Methane is an end product of carbohydrate fermentation in the rumen which can be reduced by promoting a shift of fermentation products into propionate production. However, methane production cannot be completely eliminated without any adverse effect on ruminant production (Moss 2000). Therefore, Moss (2000) suggested that increasing ruminant production would be the most effective means of reducing methane production. Increased animal products (meat or milk) would mean declining methane production per unit of animal products. In this study, if methane production was calculated into per unit of ADG (methane production/ADG; L/g), methane production decreased by 14.0%, 28.5% and 21.9% for 1% CRM, 2% CRM and 3% CRM, respectively compared to control. These values had a significant meaning when it was observed in macro-environment, especially in Indonesia where ruminant feeding was based on agricultural by-products containing high fiber.

CONCLUSION

Complete rumen modifier (CRM) supplementation in corn cob basal diet did not affect nutrient intake, lamb growth rate and rumen fermentation, but decreased methane emission. Supplementation of 2-3% CRM in the diets decreased nutrient digestibility and methane production. It is suggested that 2% CRM supplementation in the corn cob basal diet of lambs can be recommended to reduce glasshouse methane emission.

ACKNOWLEDGEMENT

The authors would like to thank the Indonesian Agency for Agricultural Research and Development, Ministry of Agriculture, Republic of Indonesia, for financial support. We thank to undergraduate students, Faculty of Animal and Agriculture, Diponegoro University for their assistance in measuring methane production.

REFERENCES

Aazamil, M., Tahasbi, A., Ghaffari, M., Naserian, A., Valizadeh, R. & Ghaffari, A. (2013) Effects of saponins on rumen fermentation, nutrients digestibility, performance, and plasma metabolites in sheep and goat kids. Annual Review & Research in Biology. 3 (4), 596–607.

Abreu, A., Carulla, J.E., Lascano, C.E., Díaz, T.E., Kreuzer, M. & Hess, H.D. (2004) Effects of Sapindus saponaria fruits on ruminal fermentation and duodenal nitrogen flow of sheep fed a tropical grass diet with and without legume. Journal of Animal Science, 82 (5), 1392–1400.

Anantasook, N., Wanapat, M. & Cherdthong A. (2014) Manipulation of ruminal fermentation and methane production by supplementation of rain tree pod meal containing tannins and saponins in growing dairy steers. Journal of Animal Physiology and Animal Nutrrient, (98), 50-55.

AOAC (1990) Association of Official Analytical Chemist, Official Method of Analysis. 12th Edition. AOAC, Washington. USA.

Cardozo, P.W., Calsamiglia, S., Ferret, A. & Kamel, C. (2005) Screening for the effects of natural plant extracts at different pH on in vitro rumen microbial fermentation of a high-concentrate diet for beef cattle. American Society of Animal Science, (February), 2572–2579.

Conway, E.J. & Byrne, A. (1933) An absorption apparatus for the determination of certain volatile substances. I. The microdetermination of ammonia. Biochemical Journal, (27), 419–429.

Goel, G., Makkar, H.P.S. & Becker, K. (2008) Effects of Sesbania sesban and Carduus pycnocephalus leaves and fenugreek (Trigonella foenumgraecum L.) seeds and their extracts on partitioning of nutrients from roughage- and concentrate-based feeds to methane. Animal Feed Science and Technology. [Online] 147 (1–3), 72–89. Available from: doi:10.1016/j.anifeedsci.2007.09.010.

Goel, G., Makkar, H.P.S. & Becker, K. (2008b) Changes in microbial community structure, methanogenesis and rumen fermentation in response to saponin-rich fractions from different plant materials. Journal of Applied Microbiology, (105), 770–777.


Guo, Y.Q., Liu, J.X., Lu, Y., Zhu, W.Y., Denman, S.E. & McSweeney, C.S. (2008) Effect of tea saponin on methanogenesis, microbial community structure and expression of mcrA gene, in cultures of rumen micro-organisms. Letters in Applied Microbiology. [Online] 47 (5), 421–426. Available from: doi:10.1111/j.1472-765X.2008.02459.x.

Hess, H.D., Beuret, R.A., Lotscher, M., Hindrichsen, I.K., Machmuller, A., Carulla, J.E., Lascano, C.E. & Kreuzer, M. (2004) Ruminal fermentation, methanogenesis and nitrogen utilization of sheep receiving tropical grass hay-concentrate diets offered with Sapindus saponaria fruits and Cratylia argentea foliage. Animal Science. [Online] 79, 177–189. Available from: isi:000222788700018%5Cnc:/reference/1488.pdf.

Holtshausen, L., Chaves, A.V., Beauchemin, K.A., McGinn, S.M., McAllister, T.A., Odongo, N.E., Cheeke, P.R. & Benchaar, C. (2009) Feeding saponin-containing Yucca schidigera and Quillaja saponaria to decrease enteric methane production in dairy cows. Journal of Dairy Science. [Online] 92 (6), 2809–2821. Available from: doi:10.3168/jds.2008-1843.

Johnson, K.A. & Johnson, D.E. (1995) Methane emissions from cattle. Journal of Animal Science. [Online] 73 (8), 2483–2492. Available from: doi:/1995.7382483x.

Kawashima, T., W. Sumamal, F. Terada, and M. Shibata. 2001. Respiration trial system using ventilated flow-through method with facemask. JIRCAS Journal, 9, 53–74.

Kumar, M., Kannan, A., Bhar, R., Gulati, A., Gaurav, A. & Sharma, V.K. (2017) Nutrient intake, digestibility and performance of Gaddi kids supplemented with tea seed or tea seed saponin extract. Asian-Australasian Journal of Animal Sciences. [Online] 30 (4), 486–494. Available from: doi:10.5713/ajas.16.0451.

Lovett, D.K., Stack, L., Lovell, S., Callan, J., Flynn, B., Hawkins, M. & O’Mara, F.P. (2006) Effect of feeding Yucca schidigera extract on performance of lactating dairy cows and ruminal fermentation parameters in steers. Livestock Science. [Online] 102 (1–2), 23–32. Available from: doi:10.1016/j.livsci.2005.11.005.

Manasri, N., Wanapat, M. & Navanukraw, C. (2012) Improving rumen fermentation and feed digestibility in cattle by mangosteen peel and garlic pellet supplementation. Livestock Science. [Online] 148 (3), 291–295. Available from: doi:10.1016/j.livsci.2012.06.009.

Mao, H.L., Wang, J.K., Zhou, Y.Y. & Liu, J.X. (2010) Effects of addition of tea saponins and soybean oil on methane production, fermentation and microbial population in the rumen of growing lambs. Livestock Science. [Online] 129 (1–3), 56–62. Available from: doi:10.1016/j.livsci.2009.12.011.

Moss, A.R., Jouany, J.P. & Newbold, J. (2000) Methane production by ruminants : its contribution to global warming. Annales de Zootechnie. [Online] 49 (3), 231–253. Available from: doi:10.1051/animres:2000119>.

Norrapoke Thitima, Metha Wanapat And Suban Foiklang. 2014. Influence of tropical plant sources containing plant secondary compound on rumen fermentation using in vitro gas fermentation technique. Indian Journal of Animal Sciences, 84 (9): 1004–1010.

Olivier, J.G.J., van Aardenne, J.A., Dentener, F., Ganzeveld, L., & Peters, J.A.H.W. 2005. Recent trends in global greenhouse gas emissions: Regional trends and spatial distribution of key sources. In A. van Amstel (Ed.) Non-CO2 Greenhouse Gases (NCGG-4) (pp. 325–330). Rotterdam: Millipress.

Patra, AK & Saxena, J. 2009. The effect and mode of action of saponin on the microbial populations and fermentation in the rumen and ruminant production. Nutrision Research Review, (22): 204-219.

Pen, B., Sar, C., Mwenya, B., Kuwaki, K., Morikawa, R. & Takahashi, J. (2006) Effects of Yucca schidigera and Quillaja saponaria extracts

on in vitro ruminal fermentation and methane emission. Animal Feed Science and Technology. [Online] 129 (3–4), 175–186. Available from: doi:10.1016/j.anifeedsci.2006.01.002.

Pen, B., Takaura, K., Yamaguchi, S., Asa, R. & Takahashi, J. (2007) Effects of Yucca schidigera and Quillaja saponaria with or without? 1-4 galacto-oligosaccharides on ruminal fermentation, methane production and nitrogen utilization in sheep. Animal Feed Science and Technology. [Online] 138 (1), 75–88. Available from: doi:10.1016/j.anifeedsci.2006.11.018.

Pilajun, R., & Wanapat, M. (2011) Effect of coconut oil and mangosteen peel supplementation on ruminal fermentation, microbial population, and microbialprotein synthesis in swamp buffaloes. Livestock Science, (141), 148–154.

Sineenart, P., Wanapat, M., Cherdthong, A., Kang, S. (2016) Rumen microorganisms, methane production, and microbial protein synthesis affected by mangosteen peel powder supplement in lactating dairy cows. Tropical Animal Health Production (48), 593–601

Ramin, M. & Huhtanen, P. (2013) Development of equations for predicting methane emissions from ruminants. Journal of dairy Science. [Online] 96 (4), 2476–2493. Available from: doi:10.3168/jds.2012-6095.

SAS. (2004) SAS/STAT User’s Guide (Release 9.1). SAS Inst, Inc. Carry, NC, USA.

Sirohi, S.K., Goel, N. & Singh, N. (2014) Influence of Albizia lebbeck saponin and its fractions on in vitro gas production kinetics, rumen methanogenesis, and rumen fermentation characteristics. ISRN Veterinary Science. [Online] 2014, 1–10. Available from: doi:10.1155/2014/498218.

Sukmawati, N.M.S., Ermana, I.G.P., Thalib, A. & Kompyang, S. (2011) Pengaruh Complete Rumen Modifier (CRM) dan Calliandra calothyrus terhadap produktivitas dan gas metan enterik pada kambing perah PE. Indonesian Journal of Animal and Veterinary Sciences, 16 (3), 173–183.

Thalib, A., Widiawati, Y., Hamid, H., Suherman, D. & Sabrani, M. (1996) The effects of saponin from Sapindus rarak fruit on rumen microbes and performance of sheep. Indonesian Journal of Animal and Veterinary Sciences, [Online] 2 (1), 17–21. Available from: doi:10.14334/jitv.v2i1.39.

Thalib, A., Devi, D., Widiawati, Y. & Mas’ud, Z. (1998) Efek kombinasi defaunator dengan faktor pertumbuhan mikroba terhadap kecernaan ruminal jerami padi. Indonesian Journal of Animal and Veterinary Sciences, 3, 171–175.

Thalib, A. (2002) Pengaruh imbuhan faktor pertumbuhan mikroba dengan dan tanpa sediaan mikroba terhadap performans kambing Peranakan Etawah ( PE ). Journal of the Indonesian Tropical Animal Agriculture, 7 (4), 220–226.

Thalib, A. (2004) Uji efektivitas saponin buah Sapindus rarak sebagai inhibitor metanogenesis secara in vitro pada sistem pencernaan rumen. Journal of the Indonesian Tropical Animal Agriculture, 9 (3), 164–171.

Thalib, A., Situmorang, P., Mathius, I.W., Widiawati, Y. & Puastuti, W. (2011) The utilization of the complete rumen modifier on dairy cows. Journal of the Indonesian Tropical Animal Agriculture, 36 (2), 137–142.

Thalib, A., Widiawati, Y. & Haryanto, B. (2010) Penggunaan Complete Rumen Modifier ( CRM ) pada ternak domba yang diberi hijauan pakan berserat tinggi. Journal of the Indonesian Tropical Animal Agriculture, 15 (2), 97–104.

Van Soest, P.J., Robertson, J.B. & Lewis, B.A. (1991). Methods for dietary fiber, neutral detergent fiber andnon-starch polysaccharides in relation to animalnutrition. Journal Dairy Science, 74: 3583-3593.


Wang, Y., McAllister, T. a, Yanke, L.J. & Cheeke, P.R. (2000) Effect of steroidal saponin from Yucca schidigera extract on ruminal microbes. Journal of Applied Microbiology. [Online] 88, 887–896. Available from: doi:jam1054 [pii].

Wang, C.J., Wang, S.P. & Zhou, H. (2009) Influences of flavomycin, ropadiar, and saponin on nutrient digestibility, rumen fermentation, and methane emission from sheep. Animal Feed Science and Technology. [Online] 148 (2–4), 157–166. Available from: doi:10.1016/j.anifeedsci.2008.03.008.

Wina, E., Muetzel, S. & Becker, K. (2005a) The impact of saponins or saponin-containing plant materials on ruminant production-a review. Journal of Agricultural and Food Chemistry. [Online] 53, 8093–8105. Available from: doi:10.1021/jf048053d.

Wina, E., Muetzel, S., Hoffmann, E., Makkar, H.P.S. & Becker, K. (2005b) Saponins containing methanol extract of Sapindus rarak affect microbial fermentation, microbial activity and microbial community structure in vitro. Animal Feed Science and Technology. [Online] 121 (1–2), 159–174. Available from: doi:10.1016/j.anifeedsci.2005.02.016.

Wina, E., Muetzel, S. & Becker, K. (2006) Effects of daily and interval feeding of Sapindus rarak saponins on protozoa, rumen fermentation parameters and digestibility in sheep. Asian-Australasian Journal of Animal Sciences, 19 (11), 1580–1587.

Yulistiani D. & Puastuti W. (2012a). Feed consumption and growth response of lambs fed on different basal diet. In: Koonawootrittriron S. (eds) Proceedings of the 15th AAAP Animal Science Congress 26-30 November 2012 Thammasat University, Bangkok, Thailand. pp: 733-736.

Yulistiani, D., Puastuti, W., Wina, E. & Supriati. (2012a) Pengaruh berbagai pengolahan terhadap nilai nutrisi tongkol jagung : komposisi kimia dan kecernaan in vitro. Journal of the Indonesian Tropical Animal Agriculture, 17, 59–66.

Yulistiani, D., Thalib, A., Haryanto, B. & Puastuti, W. (2012b) The total gas and methane productions of grass incubated In Vitro using rumen liquor from sheep adapted to complete rumen modifier supplement. In: Koonawootrttriron, K. et al. (eds.) Proceedings of the 15th AAAP Animal Science Congress, (November), Rangit, Thammasat University, pp.3535–3538.

Zhou, Y.Y., Mao, H.L., Jiang, F., Wang, J.K., Liu, J.X. & McSweeney, C.S. (2011) Inhibition of rumen methanogenesis by tea saponins with reference to fermentation pattern and microbial communities in Hu sheep. Animal Feed Science and Technology, [Online] 166–167, Elsevier B.V., 93–100. Available from: doi:10.1016/j.anifeedsci.2011.04.007.

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content of seven Indonesian soils as affected by elemental compositions of parent rocks. Geoderma. 189–190, 388–396.

Akhter, M. & Sneller, C.H. (1996) Yield and yield components of early maturing soybean genotypes in the mid-south. Crop Science. 36, 877–882.

Anda, M, Suryani, E., Husnain & Subardja, D. (2015) Strategy to reduce fertilizer application in volcanic paddy soils: Nutrient reserves approach from parent materials. Soil and Tillage Research. 150, 10–20

Sumarno & Zuraida, N. (2006) Hubungan korelatif dan kausatif antara komponen hasil dengan hasil kedelai. Penelitian Pertanian Tanaman Pangan. 25(1), 38–43.

Book/complete bookBosc, A.N., Ghosh, S.N., Yang, C.T. & Mitra, A. (1991)

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Articles in book/chapterPowers, D.A. & Schulte P.M. (1996) A molecular

approach to selectionist/neutralist controversy. In: Ferraris, J.D. & Palumbi, S.R. (Eds.) Molecular Zoology: Advances, Strategies, and Protocols. Wilmington, Delaware (DE). Wiley-Liss, Inc.

Sudaryono, Taufik, A. & Wijanarko, A. (2007) Peluang peningkatan produksi kedelai di Indonesia. In: Sumarno et al. (Eds.) Kedelai: Teknik produksi dan pengembangannya. Bogor, Indonesia. Pusat Penelitian dan Pengembangan Tanaman Pangan.

Dissertation/thesesSimpson, B.K. (1984) Isolation, Characterization, and

Some Application of Tripsin from Greenland Cod (Gadus morhua). PhD Thesis. Memorial University of Newfoundland.

Conference proceedingsTangendjaja, B. & Wina, E. (2000) Tannins and ruminant

production in Indonesia. In: Brooker, J.D. (Ed.) Tannins in Livestock and Human Nutrition. Proceedings of an International Workshop, Adelaide, Australia, 31 May-2 June 1999. ACIAR. pp. 40-43

Budi, D.S. 2000. Toleransi kedelai (Glycine max (L.) Merr.) terhadap genangan air statis pada berbagai fase pertumbuhan. In: Gunawan, V.W., Sunarlin, N., Handayani, T., Soegiarto, B., Adil, W., Priyanto, B. & Suwarno (Eds.) Prosiding Lokakarya Penelitian dan Pengembangan Produksi Kedelai di Indonesia. Jakarta, Indonesia. Direktorat Teknologi Lingkungan., pp. 207–212.

Conference paperChin, L.J., Tan, L.M. & Wegleitner, K. (2007) The

occurrence of mycotoxins in feed samples from Asia. A continuation of the Bromin mycotoxin survey program.

Paper presented at the 15th Annual ASA-IM Southeast Asian Feed Technology and Nutrition Workshop, Bali-Indonesia, 27–30 May 2007.

Research papers/reports/working papersOnly papers appearing as part of an institutions working papers series should be classified as working process. These should always include a specific working paper number as assigned by the institution.Example:Heidhues, P. & Kassogi, B. (2005) The Impact of

Consumer Loss Aversion on Pricing. Centre for Economic Policy Research Discussion Paper 4849.

Article onlineHawk, A. 2004. Mycotoxins. Procceding Grain Elevator and Processing Society (GEAPS). http://www.geaps.com/ proceedings/2004/Hawk.ctm. (Accessed 1 July 2008).

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Documents

Vol. 18 No. 1, June 2017 - Balai PATPbpatp.litbang.pertanian.go.id/balaipatp/assets/upload/download/file/Dokumen_378.pdf · Vol. 18 No. 1, June 2017 Indonesian Journal of Agricultural