people.umass.edupeople.umass.edu/jmeagy/Increasing Nutrient Density of... · Web viewOrganically grown fruits and vegetables might differ from conventionally grown produce due to

Increasing Nutrient Density of Food Crops through Soil Fertility Management and Cultivar Selection

Proposal presented By

Md J Meagy

Department of Plant, Soil, and Insect Sciences

University of Massachusetts Amherst

Table of Contents1. Literature Reviews2. Research

i. Justification ii. Objectivesiii. Experiments

a. Experiment 1:b. Experiment 2:c. Experiment 3:d. Experiment 4:

3. Experiment 1:i. Introduction ii. Materials and Methods

a. Materials b. Methods

iii. Results iv. Discussion










7. Bibliography


Proposal presented

By

Md J Meagy




A Disertation Proposal Presented

By

MD J. MEAGY

Approved as to style and content by:

____________________________________________________Allen V. Barker, Chair

____________________________________________________Geunhwa Jung, Member

____________________________________________________Touria El Jaoual Eaton, Member




Abstract

Lettuce is the most widely used leafy vegetable around the world. This experiment will

be conducted on lettuce crop, organic and conventional fertility regimes, fertility

management practices, assessing the relationship between fertility regimes and cultivars

selection for increasing nutrient densities, and assessing the molecular similarities and

variations among the cultivars. Experiments will be conducted in greenhouse and field

sites. Organic and conventional fertilizer regimes will be used as treatment for the plant.

Growth parameter such as height, fresh wt and dry wt will be reported for each

experiment. Elemental analysis will be resulted accumulated by plants afterwards.

Nutrients densities in plants might be increases through fertility and management

practices.

1


Background

Malnutrition is a primary factor limiting human productivity in modern times, and

deficiencies of certain elements including calcium, magnesium, potassium, phosphorus,

zinc, copper, and others known as mineral nutrients, in diets of humans are a substantial

nutritional problem throughout the World (Darnton-Hill et al., 2005; Kataki and Babu,

2002; Schaetzel and Sankar, 2000). Davis (2009) reports 5% to 40% declines in mineral

contents of vegetables and fruits in the past 50 to 70 years in the United States. Reports

from the United Kingdom indicated that foods were depleted by about 20% during this

time (Anonymous, 2005; Anonymous, 2006; Mayer, 1997). Research on the diets of

subjects in Philadelphia warranted a downward revision in the intakes of iron,

magnesium, and vitamins (Guenther et al., 1994). The result of a study concluded that

many Americans are not meeting the current recommendations for calcium intake

through diet alone or with supplements (Ma et al., 2007).

Davis (2009) suggests that the decline in mineral and protein content in fruits and

vegetables is due partly to a dilution effect of high yields. Side-by-side comparisons of

low- and high-yielding vegetables and grains showed negative correlations between yield

of produce and concentrations of minerals. However, White et al. (2009) reported that

with potato (Solanum spp. L.), a dilution effect of high yields on nutrient concentration

was not observed universally and that soil fertility affected the mineral nutrients more

than the dilution effect.

2

Soil fertility problems associated with nutrient depletion by crop production are

worldwide (Tan et al., 2005). In the United States, potassium and phosphorus contents

are being drawn down in soils at an increasing rate every year, and the depletion

occurring for 40 years for potassium and for nearly 30 years for phosphorus (Stewart,

2004). Similar nutrient mining of essential elements occurs throughout the World

(Ayoub, 1998; Dobermann et al., 1996; Lal and Singh, 1998; Nandwa and Bekunda,

1998). Elemental depletion of soils must be compensated for by fertilization for

sustainable production of nutrient-sufficient foods (Buol, 1995).

Organically grown fruits and vegetables might differ from conventionally grown

produce due to differences in the types of fertilizers used in the two practices. Low

availability of nutrients in organic fertilizers could limit mineral accumulation in plants

relative to fertilization with chemical fertilizers with high nutrient availability, thereby

making the chemical fertilizers a superior nutrient source. On the other hand, high

availability of certain nutrients or failure to provide elements in chemical fertilizers could

lead to nutrient imbalances in foods (Lundegaardh and Maartensson, 2003). A study

noted that compost increased nutrient concentrations in soils but not always in plants

(Roe, 1998). The result of another study reported no consistent differences in nitrogen,

phosphorus, and potassium concentrations in several vegetables in crops fertilized with

composts and crop residues or with synthetic mineral fertilizers (Herencia et al., 2007). A

recently published study (Benbrook et al., 2008) reported that organically grown foods

derived from plants were superior to those grown conventionally with respect to

phosphorus, potassium, nitrates, several antioxidants, and vitamin C. An experiment

result suggested that the high yields achieved through farming systems with high nitrogen

3

fertilizer inputs led to a dilution of nutrient density in vegetables relative to organic

systems with low nitrogen inputs (Benbrook and Scientist, 2009). High nitrate

concentrations in foods are considered as a factor adversely affecting human health

(Maynard et al., 1976). Organically grown vegetables may have less nitrate accumulation

than conventionally fertilized vegetables (Benbrook et al., 2008). The result of a study

reported that farm manure had a more favorable effect on certain plant constituents

(nitrate and oxalic acid) than potassium nitrate (Turan and Sevimli, 2005). However,

Maynard et al. (1976) noted that the amount of nitrogen fertilization regardless of source

was the principal factor leading to nitrate accumulation in vegetables. A study noted that

with fertilization for optimum yield, nitrate concentrations of vegetables were not

different between organically and chemically fertilized vegetables (Barker, 1975).

Regardless of soil conditions, fruits and vegetables, although high in vitamins, are

typically low in mineral nutrients (Elless et al., 2000). Except for potassium, the fruit-

vegetable food group contributes less than 30% of the total dietary intake of mineral

nutrients (Levander, 1990). To counter this problem, several attempts have been made to

increase the mineral nutrient content of fruits and vegetables. These actions have

included enrichment of foods in processing, but not much attention has been directed

toward improvement of foods through enhanced soil fertility and cultivar selection,

although these two factors appear to be principal agents affecting the nutrient density of

fruits and vegetables.

Methods of increasing the nutrient content of foods must be developed through

improved practices in fertilization and in the development and selection of crop varieties

that accumulate the nutrients in amounts that are adequate for intake in normal diets of

4

humans. This research will involve studies with heritage and modern hybrids of several

types of vegetable crops grown under differing regimes of fertilization. It is likely that

heritage and modern hybrids will differ in susceptibility to diseases. . The high levels of

horizontal or broad resistance to pathogens are often observed in heritage cultivars due to

their adaptation over time to climate and soil conditions where they have grown in when

they are compared to modern cultivars. The modern cultivars drop in horizontal or broad

resistance to pathogens during breeding and under protection of pesticides. Soil fertility

practices also are likely to affect the prevalence of diseases in the soil and plant

susceptibility to diseases. Plant pathogenic diseases can be stimulated by excess levels of

available nitrogen under favorable conditions.

Justification

The need for this project was raised by the food consumers and producers as well as by

the scientific community. Literature on food composition demonstrates that the mineral

nutrient density of vegetables has fallen in the past 50 years. This decline is associated

with declines in soil fertility and with the genetics of plant cultivars that increase yield at

higher rates than mineral nutrients increases. Research is needed to develop systems of

food crop production that will supply adequate mineral nutrition to people directly. Use

of nutrient-dense crops provide an opportunity for vegetable producers to diversify

production and market, and to increase income and profitability as there appear to be a

ready market for these crops.

5

Research Objectives

1. To determine if the mineral nutrient densities of selected vegetable crops can be

increased through cultivar selection.

2. To determine if the nutrient densities of selected vegetable crops can be increased

by elevating nutrient contents in the medium in which these plants grow.

3. To determine if the nutrient densities of selected vegetable crops can be increased

through soil fertility practices (e.g., organic vs conventional fertilizers; different

fertilizer regimes), and

4. To assess genetic similarities among selected cultivars within species, for genetic

purity and diversity, using molecular markers.

Research

Four experiments will be set up for this project based on objectives. The brief discussions

of the experiment are as follows:

Experiment 1. Assessment of the relationship between nutrient density in crops and

cultivar selection and nutrient availability in the greenhouse.

This experiment will be designed to determine the mineral nutrient contents of lettuce

through cultivar selection using different fertilizer regimes.

The experiment will be conducted in the greenhouse to evaluate regimes of fertilization

and cultivars for evaluation in fields. The same fertilizers suggested for the field

evaluation will be used in this experiment. The greenhouse experiments will help to

evaluate fertility regimes before and after application in the field. The lettuce crop will be

6

grown in peat-based media (Canadian Growing Mix 1-PV, Conrad Fafard Inc, Agawam,

MA) (Boodley et al., 1996). The elemental nutrient composition will be determined in

edible parts (fresh leaves) of lettuce. Because of their adaptability to greenhouse

production, the lettuce crop to be evaluated using different lettuce cultivars. Each crop

will be evaluated for their growth and nutrient contents. The experimental design of the

experiment will be followed by complete random block design.

Experiment 2. Assess the effect between mineral nutrient density in crops and cultivar

selection by elevating nutrient contents in the medium in which the plants grow.

This experiment will be assessed differences in the mineral densities of lettuce cultivar

through increasing the nutrient contents in the medium. The differences of this

experiment from the experiment one will be in elevating nutrient contents in the medium

in which the plant grow. The experiment will be conducted in greenhouse and field to

assess the response of lettuce using the increasing nutrient contents. The same fertilizers

will be used in the field experiment. The crop will be grown in peat-based media

(Canadian Growing Mix 1-PV, Conrad Fafard Inc, Agawam, MA) (Boodley et al., 1996).

The fertilizer regimes will be chemical fertilizer organic fertilizer with increasing nutrient

contents. The increasing nutrient contents in the fertilizer regimes will be calcium based

on nutrient demand for human dietary nutrient requirement. The nutrient contents will be

measured in the edible parts (fresh leaves) of the plant. This crop will be evaluated for

growth and nutrient densities in produce. The experimental design of the experiment will

be followed by complete random block design.

7

Experiment 3. Assess the effect of organic and conventional soil fertility practices on

mineral accumulation in vegetables in field experimentation.

Fertilization will be provided in the experiment using organic and conventional fertilizer

regime. Two regimes of organic and one conventional fertilizer will be selected to

provide nutrients. Organic fertilizer will come from the individual sources includes

soybean meal for nitrogen, colloidal rock phosphate for the phosphorus, and mined

potassium sulfate for the potassium. The compost will be obtained from the University

Office of Waste Management, which produces compost from dining commons food

waste and yard waste from the Amherst campus. Produce will be harvested and evaluated

for yield and nutrient densities at edible plant parts (e.g. fresh leaves). In addition,

whenever pathogen resulted damages or symptoms are observed under natural conditions

(no artificial inoculations), accurate identification of the disease will be carried out in

conjunction with Plant Disease Diagnostician and a vegetable pathologist (Dr. Robert

Wicks, Plant, Soil, and Insect Sciences) at the University of Massachusetts Amherst. The

disease severity per cultivar will be rated. The experimental design of the experiment

will be followed by complete random block design.

Experiment 4. Assessment of the genetic purity and genetic diversity among cultivars of

lettuce using molecular markers in greenhouse experiment.

8

This experiment is planned to determine the genetic purity and genetic diversity among

cultivars of lettuce crops using molecular markers. The experiment will be conducted in

the greenhouse using the same cultivars as used in the previous experiments. Standard

fertilizer will be used to grow the cultivars. Fresh tissue will be sampled in the middle of

the growth period for genomic analysis. Genomic DNA will be extracted from plant

tissues according to the procedures used in (Curley and Jung, 2004; Simko, 2008) and

(Sim et al., 2009). EST- and genomic-SSR markers of respective vegetables, these will be

selected from the most recent papers (Cavagnaro et al., 2009; Kong et al., 2006; Liu et

al., 2007b; Liu et al., 2007c; Richards et al., 2004; Simko, 2008; Yi et al., 2006) will be

screened against selected cultivars within the vegetable species and used for genetic

similarities. PCRs will be conducted in conditions as described in the respective papers.

DNA similarities among cultivars within each of species will be estimated. The

experimental design of the experiment will be followed by complete random block

design.

Statistical analysis

Plant heights, fresh weights, and dry weights data will be processed as analysis of

variance using the SAS (SAS 9.1.3, SAS Institute Inc., SAS Campus Drive, Cary, NC

27513) PROC GLM procedure. Mean separation will be conducted by F test and

Duncan’s New Multiple Range Test (P=0.05).

9

Total N and elemental analysis data will be analyzed using SAS PROC GLM procedure.

Polynomial comparison among cultivars will be performed by orthogonal polynomial test

using PROC GLM and PROC IML procedure.

.

Assessment of the relationship between nutrient density in crops and cultivar

selection and nutrient availability in the greenhouse.

Introduction

Mineral deficiency adversely affect a third of world’s population. Consequently,

micronutrient deficiencies affect global health and limit human productivity in recent

times, and deficiency of certain mineral nutrients like calcium, potassium, magnesium,

phosphorus, zinc, iron, copper, manganese and others are a substantial nutritional

problem in diets of human around the world (Darnton-Hill et al., 2005; Kataki and Babu,

2002). Nutrient content in vegetables and fruits reported declines of 5% to 40% or more

in some soils in the past 50 to 100 years in the United States (Davis, 2009). Reports

indicated the in the United Kingdom foods contents decreased by about 20% during this

time (Anonymous, 2005; Anonymous, 2006; Mayer, 1997). Study on the diets of subjects

in Philadelphia, PA warranted a downward revision in the intakes of iron, magnesium,

and vitamins (Guenther et al., 1994). Another study concluded that many Americans,

particularly men, social disadvantaged groups, and ethnic minorities are not meeting the

current recommendations for calcium intake through diet alone or with supplements (Ma

et al., 2007).

10

Davis (2009) suggests that the decline in mineral and protein content in fruits and

vegetables is due partly to a dilution effect of high yields. Side-by-side comparisons of

low- and high-yielding vegetables and grains showed negative correlations between yield

of produce and concentrations of minerals. However, a dilution effect of high yield on

nutrient concentration was not observed universally on potato (Solanum spp L.) and that

soil fertility affected the mineral nutrients more than the dilution effect (White et al.,

2009).

Micronutrient malnutrition is a growing concern all over the developing world having

consequence a mental retardation, impairments of the immune system, and overall poor

health (Cakmak, 2009).

Soil fertility problems associated with nutrient depletion by crop production are

worldwide, and also nutrient depletion can be caused to insufficient fertilizers use and

unbalanced fertilization (Tan et al., 2005). In United States, potassium and phosphorus

are being drawn in soils on a national basis at an increasing rate every year, and the

depletion has occurred for 40 years for potassium and for nearly 30 years for phosphorus

(Stewart, 2004). A study suggest prediction of nitrogen uptake for sustainable nitrate pool

of lettuce was depended on the water content (Seginer et al., 2004).

The objective of the study will be to determine if the mineral nutrient densities of

selected vegetable crops can be increase through cultivar selection.

Materials and Methods

Materials

11

Eighteen lettuce (Lactuca sativa) cultivars will be used in this experiment. Nine varieties

will be heritage and nine will be modern for this study. Three varieties (Table 1) of each

group (Butterhead, Romaine/Cos, and Loose leaf) will be chosen in heritage and modern

type of lettuce based on widely used and marketability. Then eighteen varieties (nine

heritages and nine moderns) of both groups will be used for the treatment. Three

fertilizer regimes will be used for this experiment.

Methods

Eighteen different cultivars of lettuce will be grown in the Bowditch greenhouse at

University of Massachusetts Amherst. Seeds of those cultivars were collected from

professional seed producers. Heritage type of seeds will be collected from certified

organic seeds producer (Seed of Change Seeds Co., Spicer, MN 56288) and modern type

of seeds will be collected from another successful seeds producer (Johnny Seeds Co.,

Winslow, ME 04901). All seeds of these cultivars will be planted in peat moss medium

on December 18, 2009 in the greenhouse at 2-3 seeds/cube. . For best germination of

seeds media temperature will be maintained of 68oF (20oC). After 32 days, lettuce

seedlings will be transferred to plastic containers (6 inch diameter) in a peat-based

medium (MetroMix 360, SunGro Horticulture, Vancouver, Canada).

Three different combinations (regimes) of fertilizers will be chosen for nutrient sources

of lettuce cultivars. With different cultivars different nutrient regimes will be tested if

nutrient content increases through cultivars selection. Three treatments will be Hoagland

#1 solution (complete), Jack’s Fertilizer (20-10-20) Peat-Lite (add CaSO4 to medium),

and organic Pure blend Pro Grow (3-1.5-4) for this experiment. The purpose of the

application of different fertilizer regimes is to investigate the nutrient content of the

12

lettuce through cultivar selection. The lettuce will be grown in greenhouse for about 7-9

weeks from seedlings to maturation.

Table 1. Varietal selection of each cultivarHeritage variety (H) Modern variety (M)

Butterhead (C1):1. Buttercrunch (V1)2. Bronze Mignonette (V2)3. Tom thumb (V3)

Romaine/Cos (C2):1. Coastal Star (V1)2. Cosmo-Savoy Leaf (V2)3. Forellenschluss (V3)

Loose leaf (C3):1. Salad Bowl (V1)2. Simpson black-seeded (V2)3. Red deer tongue (V3)

Butterhead (C1):1. Adriana (V1)2. Focea (V2)3. Australe (V3)

Romaine/Cos (C2):1. Red rosie (V1)2. Claremont (V2)3. Winter density (V3)

Loose leaf (C3):1. Tropicana (V1)2. Simpson elite (V2)3. Two star (V3)

Each regime will carry a fertilizer treatment with different combination. The first

fertilizer treatment contained of 210 ppm N, 31 ppm P, 234 ppm K, 200 ppm Ca, 48 ppm

Mg, 64 ppm S, and micronutrient composite and Fe chelate 1 ppm from a Hoagland’s

solution (Hoagland and Arnon, 1950). The second fertilizer treatment carried of using

3% N, 1.5% P, 4% K with trace minerals 1.0% Ca and 0.5% Mg from a 3-1.5-4 formula

organic fertilizer (Pure Blend Pro Grow, Botanicare, Tempe, AZ) and with this fertilizer

4 ml 0.5 M MgSO4/liter will be added for Mg and S. The third fertilizer treatment

consisted of 20 % N, 10 % P, 20 % K, 1.5 % Mg, 0.02 % B, 0.01 % Cu, 0.1 Fe, 0.05 %

Mn, 0.01 % Mo, and 0.05 % Zn from a Jack’s 20-10-10 Peat-Lite commercial fertilizers

13

(Jack’s Professional Fertilizers, J.R. Peters, Inc., Allentown, PA 18106) and with this

fertilizer I g CaSO4/pot will be mixed in media for Ca, and additionally 4 ml 0.5 M

MgSO4/liter will be added for Mg and S. The treatment of fertilizer regime will be

applied one time in one day interval at the amount 100 ml/plant for 1st 10 days after

transplanted of lettuce seedlings. Then amount of treatment of each regime then will be

increased at the rate 200 ml/plant for one day interval and continued at maturity. The

fertilizer regimes will be applied to a plant in every two days.

Media pH values will be measured in a water extract after shaking for 15 m (Hesse,

1971) using a pH meter (CRISON micro pH 2002). Media EC values will be determined

in a media/water extract after shaking for 15 m (Hesse, 1971) using a conductivity meter

(CRISON micro pH 2002).

At harvest, growth parameters including plant height, plant size and color, leaf size or

whole heads, leaf color, number of leaf, and fresh weights of leaf will be recorded.

Oven-dry weights of plant leaf and stem will be recorded afterwards.

Portions of dry plant sample of leaves will be ground to pass a 30-mesh screen and sub

sampled and stored in coin envelops for elemental analysis of N, P, K, Ca, Mg, Cu, Zn,

Fe, Mn and Cr accumulated by lettuce leaves. Kjeldhal N will be determined by acid-

digestion and posterior determination by auto analyzer (BRAN+LUEBBE, method G-

188-97, BRAN+LUEBBE, Norderstedt, Germany). Pulverized samples (0.5 g) will be

ashed at 500oC for 12 h in a muffle furnace and the ash will be dissolved in 10% HCl

solution prepared in deionized H2O. For P, K, Ca, Mg, Cu, Zn, Fe, Mn and Cr, the ash

14

extracts will be analyzed by inductive coupled plasma (ICP) spectrophotometric analysis

(Jones Jr et al., 1991; Kalra, 1998) at UMass Soil and Plant Tissue Laboratory. Lettuce

growth parameters will be used for evaluating the consequences of different fertilizer

regimes and their combination on lettuce growth and nutrient management through

cultivars selection.

Pest will be managed by using certified organic or conventional herbicides, fungicides or

insecticides as required to bring about control. During the growing season, appearance of

diseases symptoms and occurrences will be carefully monitored and diseases severity will

be evaluated for each vegetables at a scale of 0-9 scale indicating 0 being no visible

symptoms and 9 being severe symptoms.

Summary

Assess the effect between mineral nutrient density in crops and cultivar selection by

elevating nutrient contents in the medium in which the plants grow.

Introduction

Mineral elements are required for human body to maintain good health. Plants are the

main sources for these elements. Fresh fruits and vegetables are high in vitamins but are

15

aften low in essential minerals (Ashmead, 1982). Plants like Brassica juncea cultivated in

hydrophonics condition contains high levels of nutritionally important minerals such as

Cr, Fe, Mn, Se, and Zn (Elless et al., 2000).

Critical functions in human body are mainly conducted by minerals. Calcium,

phosphorus, and magnesium are required for constructing and maintaining bones

(Anonymous, 1989). Diet with enough calcium helps in maintaining healthy bones and

reduces risk of osteoporosis (Anonymous, 2000). In addition, calcium is required in

blood clotting (Karll, 2000; Krause and Mahan, 1984), and phosphorus and magnesium

are essential in energy metabolism. Iron is a crucial part of hemoglobin and myoglobin

(Anonymous, 1989; Krause and Mahan, 1984), and is required for carrying oxygen in the

blood and muscles (Krause and Mahan, 1984). Anemia is caused by iron deficiency

(Krause and Mahan, 1984).

Deficiency of trace elements like zinc, copper, and selenium has a positive correlation

with risk of cancer (Abdulla and Gruber, 2000; Chan et al., 1998). A number of chronic

cardiovascular diseases are shown to be correlated with magnesium and selenium

(Brown and Arthur, 2007; Fox et al., 2001), and diabetes with zinc (Thompson and

Godin, 1995).

The results of the study suggest that it is possible to improve the dietary intake of local

dwelling elders by increasing consumption of fruits, vegetables and calcium-rich foods

(Bernstein et al., 2002). A study in vitro revealed that vegetables such as kale, celery,

collard, Chinese cabbage, and soybean sprout contained high levels of dialyzable calcium

(20-39%) compared to milk powder, which contains 25 mg Ca/100 g (Kamchan et al.). A

study on individuals age 65 and older reported that calcium is required for skeletal

16

maintenance and that supplemental intakes to a total in the range of 1300-1700 mg

Ca/day stop age-related bone loss and reduce fracture risk (Heaney, 2001).

Magnesium is the fourth most abundant cation in the body. It is believed that more than

300 enzymatic reactions are involved with magnesium. The recommended dietary intakes

(RDI) for magnesium are about 30 mg/day for adults. Though magnesium deficiency is

rare in healthy people, but diabetes, kidney diseases, hypertension, and coronary artery

diseases may induce magnesium depletion (Wahlqvist and Darmadi-Blackberry, 2002).

Green vegetables, some legumes (beans and peas), nuts and seeds, and whole and

unrefined grains are good sources of magnesium (USD-ARS, 2003). Eating lot of green

vegetables, whole grains and legumes will help meet your dietary need for

magnesium(USD-ARS, 2003).

Dark green leafy vegetables are good sources of iron, especially sixty percent of non-

heme irons are found in fruits, vegetables, grain, and nut. Recommended dietary intakes

of iron are 10 mg/day for a child, 12 mg/day for a man, and 15 mg/day for a woman

(Baynes and Bothwell, 1990).

An experiment conducted on butter head lettuce reported that plants grown with high Fe

levels (10 mg/L) had notable tip burn incidence but no bolting was observed (Chow et al.,

1999). The results also indicated that high Fe could be beneficial in producing desired

head size. In accordance with another experiment revealed tip burn increased with

nitrogen supply and was related to an increase in head size (Brumm and Schenk, 1992).

Fresh leafy vegetables are major sources of minerals for recommended dietary intakes in

the recent times. Lettuce has been an important vegetable crop with high market value,

17

and its nutritional characteristics have been studied throughout the world (Ashkar and

Ries, 1970; Chow et al., 1999).

The objective of the experiment will be to determine if the nutrient densities of selected

vegetable crops can be increased through increasing the nutrient contents in the medium

in which the plants grow.


Materials

Six lettuce cultivars will be used for this experiment. The six cultivars will be taken from

the eighteen cultivars based on nutritional requirement and growth observes in the

experiment above. Three cultivars of each group will be selected as modern and heritage.

Two fertilizer regimes with elevating concentration will be selected for this study. One

fertilizer regime will be chemical fertilizer, and another regime will be organic fertilizer

with varying nutrient concentration in solution.

Methods

The seedlings of lettuce cultivars will be grown in the Bowditch greenhouse at UMass

Amherst. Seeds of those cultivars will be collected from the professional seeds growers.

Heritage type of seeds will be collected from certified organic seeds producer (Seed of

Change Seeds Co., Spicer, MN 56288) and modern type of seeds were collected from

another successful seeds producer (Johnny Seeds Co., Winslow, ME 04901). All seeds

will be planted in peat moss medium for raising seedlings. For best germination rate, the

optimum temperature will be maintained of 68oF (20oC). After four weeks from seeding,

18

same sized seedlings will be transplanted to the 6˝̋ round pot filled with peat moss media

(MetroMix 360, SunGro Horticulture, Vancouver, Canada).

Two different fertilizer regimes will be selected for nutrient sources of lettuce cultivars.

The elevating fertilizer regimes will be tested if the nutrient densities of the lettuce crop

increases through cultivar selection and nutrient management. Two fertilizer regime will

be Jack’s 20-10-10 Peat-Lite commercial fertilizers (Jack’s Professional Fertilizers, J.R.

Peters, Inc., Allentown, PA) and organic fertilizer (Pure Blend Pro Grow 3-1.5-4,

Botanicare, Tempe, AZ) with varying concentration of Ca for this experiment. The goal

of the application of different fertilizer regimes with varying concentration is to

determine the nutrient densities of the lettuce through cultivar selection and nutrient

management. The lettuces will be grown in the greenhouse for about 4-5 weeks from

transplanting to marketable size.

Each regime of fertilizer will be divided into three treatment groups based on varying

internal nutrient concentration. The first fertilizer regime will be contained N, P, K,

and micronutrient composite from a Jack’s 20-10-10 Peat-Lite commercial fertilizers

with varying Ca (200, 300, 400 ppm) as CaCl2. Another fertilizer regime will be obtained

from organic fertilizer with varying amount of Ca (200, 300, 400 ppm) as CaCl2. Three

treatments of each group of fertilizer regime will be tested for this study. Therefore six

treatments will be selected in two groups of fertilizer regimes. The treatment will be

applied in one day interval at 100 ml/plant for first week then at 200 ml/plant until

harvest.

At harvest, growth parameters including plant height, plant size and color, and fresh

weights of plant will be recorded. Oven-dry weights of plant will be recorded afterwards.

19

Portions of dry plant sample of leaves will be ground to pass a 30-mesh screen and sub

sampled and stored in plastic containers for elemental analysis of N, P, K, Ca, Mg, Cu,

Zn, Fe, Mn and Cr accumulated by lettuce leaves. Kjeldhal N will be determined by

acid-digestion and posterior determination by auto analyzer (BRAN+LUEBBE, method

G-188-97, BRAN+LUEBBE, Norderstedt, Germany). Pulverized samples (0.5 g) will be

ashed at 500oC for 12 h in a muffle furnace and the ash will be dissolved in 10% HCl

solution prepared in deionized H2O. For P, K, Ca, Mg, Cu, Zn, Fe, Mn and Cr, the ash

extracts will be analyzed by inductive coupled plasma (ICP) spectrophotometric analysis

(Jones Jr et al., 1991; Kalra, 1998) at UMass Soil and Plant Tissue Laboratory. Lettuce

growth parameters will be used for evaluating the consequences of different fertilizer

regimes and their combination on lettuce growth and nutrient management through

cultivars selection.

Pest will be managed by using certified organic or conventional herbicides, fungicides or

insecticides as required to bring about control. During the growing season, appearance of

diseases symptoms and occurrences will be carefully monitored and diseases severity will

be evaluated for each vegetables at a scale of 0-9 scale indicating 0 being no visible

symptoms and 9 being severe symptoms.

20

Assess the effect of organic and conventional soil fertility practices on mineral

accumulation in vegetables in field experiment.

Introduction

Organic farming differs from conventional farming mainly tillage methods, crop rotation,

fertilizer applications, and pest control methods. Organically grown vegetables have

greater market values than conventional farms. Synthetic chemical fertilizers and

pesticides uses in intensive agriculture may cause serious impact on public health and the

environment (Pimentel et al., 2005). Integrated pest and nutrient management systems

and certified organic agriculture may reduce reliance on agrochemical inputs as well as

make agriculture environmentally and economically sound (Pimentel et al., 2005).

Applications of compost in vegetable crop production systems have been shown better

yield and fruit quality responses a compared with those obtained from standard vegetable

21

crop commercial practices (Stoffella et al., 2001). The impact of organic production

practices on soil quality revealed that there was 22% more organic carbon (1257 kg/ha)

and 20% more total N (970 kg/ha) on organic farm than conventional farm (Liebig et al.,

1999). The findings of the study also reported that soils of organic farms had soil pH

closer to neutral, lower bulk density, and higher available water-holding capacity,

microbial biomass C and N, and soil respiration compared with conventional farms

(Liebig et al., 1999). Ultimately, organic farming resulted better in maintaining soil

productivity and reducing soil erosion than conventional farming (Reganold et al., 1987).

It has been believed that by applying good organic composts supplemented with lower

amount of chemical fertilizers, high crop production and maintenance, or even increasing

soil fertility can be achieved.

The objective of the study will be to determine if the nutrient densities of selected

vegetable crops can be increased through soil fertility practices (e.g., organic vs

conventional fertilizers; different fertilizer used).


Materials

Eighteen different lettuce cultivars will be used in this study. Nine heritage and nine

modern cultivars will be used for this experiment. Two regimes of organic fertilizer and

one conventional fertilizer regime will be used for this study. One kind of organic

fertilizer regime will be obtained from individual nutrients sources providing nitrogen,

phosphorus, and potassium requirements of crops; and other kind of organic fertilizer

regime will be obtained from compost source providing those nutrients. Fertilizer for

22

individual nutrients will be included soybean meal for nitrogen, colloidal rock phosphate

for the phosphorus, mined potassium sulfate for the potassium. These materials are used

commonly by organic growers in the region. The compost will be collected from the

University of Massachusetts Amherst office of waste management, which produce

compost from dinning commons food waste and yard waste from the Amherst campus.

Conventional fertilizer will be obtained from a commercial fertilizers (10-10-10 all

purpose) providing nutrient requirements of crops.

Methods

The experiment will be conducted at UMass field experiment station. Eighteen different

cultivars of lettuce will be grown in the field at UMass Amherst field experiment station.

Seeds of those cultivars will be collected from the professional seed producers. Heritage

type of seeds will be collected from certified organic seeds producer (Seed of Change

Seeds Co., Spicer, MN) and modern type of seeds will be collected from another

successful seeds producer (Johnny Seeds Co., Winslow, ME). Both types of seed will be

planted in mixed soil (soil with peat moss 1:1) at Bowditch greenhouse. For best

germination of seeds soil temperature will be maintained of 68oF (20oC). At 4 weeks of

age tomato seedlings will be transplanted in UMass field experiment station.

23

Therefore, three different regimes of fertilizer will be chosen for this experiment. Two

will be organic fertilizer regimes and one convention fertilizer regime. One group of

organic regime will be obtained from some individual sources mentioned above, another

group of organic regime will be obtained from compost sources collected from UMass

Amherst office of waste management, and a conventional fertilizer regime will be

obtained from a 10-10-10 all purpose commercial fertilizer. The compost will be

analyzed for its nutrients contents before application. The reason for the use of different

fertility regimes is to find out the higher nutrient densities in plants, growth and soil

fertility management practices. The fertilizer will be applied based on the nutrient

requirement of the crops according to the management guide (Rosen and Eliason, 2005).

The organic fertilizer regime will be applied at the rate of 20 ton/acre during soil

preparation in one time as basal dose. The conventional fertilizer regime will be applied

at the rate of 100 Ib/acre before transplant in one time as basal dose. In addition, 100 Ib

CaSO4 /acre will be added during land preparation for calcium.

Soil samples will be taken after plant harvest for N, P, K, Mg, and Ca measurement to

determine the effect of the treatment on soil nutrient availability. A soil testing method

proposed by Morgan will be used to extract the soil available nutrients (Morgan, 1941).

Nitrogen will be assessed distillation and titration of NH3 in solution (Bradstreet, 1965);

P will be determined by colorimetry (blue molybdophosphoric acid method) (Olsen and

Dean, 1965); Ca and Mg will be determined by atomic absorption spectrometry; and K

by atomic emission spectrometry (Lierop, 1976; Thomas et al., 1967).

24

At harvest, growth indices including plant height, plant size, leaf color, leaf sizes, and

fresh weights of whole plant will be recorded. Oven dry weights of whole plants will be

recorded afterwards.

Dry leaves sample will be grounded to pass a 30-mesh screen for tissue nutrient analysis

of N, P, K, Ca, Mg, Cu, Zn, Fe, Mn and Cr. Kjeldhal N will be determined by acid-

digestion and posterior determination by auto analyzer (Bran+luebbe method G-188-97,

Bran+luebbe, Norderstedt, Germany). Pulverized samples (0.5 g) will be ashed at 500oC

for 12 h in a muffle furnace and the ash will be dissolved in 10% HCl solution prepared

in deionized H2O. For P, K, Ca, Mg, Cu, Zn, Fe, Mn and Cr, the ash extracts will be

analyzed by inductive coupled plasma (ICP) spectrophotometric analysis (Jones Jr et al.,

1991; Kalra, 1998) at UMass Soil and Plant Tissue Laboratory. Lettuce growth

parameters will be used for evaluating the consequences of different fertilizer regimes

and their treatment on nutrient management through cultivars selection and soil fertility.

Pest and disease symptoms will be managed by using certified organic herbicides and

fungicides or insecticides to bring about control. The severity of diseases will be

evaluated using a scale of 0-9 indicating 0 being no visible symptoms and 9 being severe

symptoms.

Assessment of the genetic purity and genetic diversity among cultivars of lettuce

using molecular markers in the greenhouse experimentation.

Introduction

Molecular markers are having uses as an effective tool for efficient selection of desired

agronomic traits. Molecular markers can facilitate tomato breeding by means of marker

25

assisted selection (MAS) to improve agronomical important characteristics such as yield,

fruit quality, and disease resistance. Molecular markers such as RFLP (Restriction

fragment length polymorphism) (Ooijen et al., 1994; Sandbrink et al., 1995), RAPD

(Random amplification of polymorphic DNA) (Qian et al., 2001; Stevens et al., 1995),

ISSR (Inter simple sequence repeat) (Joshi et al., 2000; Zietkiewicz et al., 1994), AFLP

( Amplified fragment length polymorphism) (Vos et al., 1995), and Microsatellite

polymorphism (Panaud et al., 1996) have been developed in tomato and other crops since

last decade. However, RFLP uses breeding purposes is limited because it requires the use

of radioactivity and is laborious. RAPD, ISSR and AFLP markers either identify only

dominant alleles or are sensitive to PCR amplification conditions.

Microsatellites or Simple Sequence Repeats (SSRs) are short (mostly 2-4 bp) tandem

repeats of DNA sequences. The variation or polymorphism of SSRs are a result of

polymerase slippage during DNA replication (Levinson and Gutman, 1987). SSR

markers are becoming the preferred molecular markers in crop breeding because of their

properties of genetic co-dominance, high reproducibility and multi allelic variation. They

are the most practical markers for genomic mapping, variety identification and marker-

assisted selection. In lettuce, some microsatellite markers have been used

(Areshchenkova and Ganal, 1999; Smulders et al., 1997), but the number of SSR markers

are available for molecular breeding is still few and only a limited number of SSR

markers have been mapped to the tomato genome (Areshchenkova and Ganal, 1999;

Broun and Tanksley, 1996).

26

The objectives of the present study will be to assess the genetic similarities, variation, and

purity among Lactuca sativa accessions in the USDA collection; and to develop and

characterize the more SSRs markers for lettuce.


Materials

Plant material

Eighteen lettuce cultivars will be used for this experiment. Nine will be modern and nine

will be heritage lettuce cultivars. The reason for choosing these plant cultivars for

assessing the similarities and variation among cultivars are using in the previous

experiment. All cultivars and its parental lines will be collected from the U.S. National

Plant Germplasm System (NPGS) at North Central Region Plant Introduction Station in

Ames, IA, USA; and heritage cultivars line will be collected from a commercial source

(Seed of Change Seeds Co. Inc, Spicer, MN). All purposes commercial fertilizer of

peters professional 20-20-20 TE formula will be used to grow lettuce. The rate of the

fertilizer will be used at1 g/L, and additional CaSO4 will be added in the media at 1g/pot

for Ca.

Methods

Genomic DNA Isolation

The heritage and modern seeds of the cultivars will be grown in the greenhouse with a

day temperature of 24 ± 3oC and a night temperature of 18 ± 3oC in the Bowditch

27

greenhouse at University of Massachusetts Amherst. One-month-old seedlings will be

transplanted to the pots where individual of each cultivar will randomly be selected and

numbered. Regular irrigation, fertilization, staking and crop protection measures will be

adopted and purity visual evaluation will be conducted based on the main important

morphological characters throughout the growth period. Total genomic DNA of the 18

lines will be isolated from young leaves following the method described by (Liu et al.,

2003; Yu and Pauls, 1994) with some modifications. Leaves will be collected and

immediately frozen in liquid nitrogen and stored at -70°C until use. For each sample, four

fresh leaf obtained by punching leaves with the cap of a 1.5-ml Eppendorf tube, will put

into 400 μl of DNA extraction buffer (200 mM Tris–HCl, pH 7.4, 250 mM of NaCl, 25

mM of EDTA, pH 8.0, 0.5% SDS) and homogenized with a plastic pestle (Mandel

Scientific Company Ltd.). Then 400 μl of 24:1 chloroform/isopropyl alcohol will be

added to the homogenized solution, vortexed and left at room temperature for 30 min.

The homogenate will spun in a micro centrifuge at a speed of 10,500 rpm for 2 min and

350 μl of the supernatant were transferred into a new Eppendorf tube. For DNA

precipitation, an equal volume (350 μl) of isopropanol will be added to the tube that will

left at room temperature for 5 min and then spun at 11,000 rpm for 5 min. Then, the DNA

pellet will be air-dried at room temperature for 30 to 60 min before it will be dissolved in

200 μl of water at 4 °C overnight. The supernatant will be collected after micro

centrifugation at 1,300 rpm for 2 min, yielding about 25 ng/μl of DNA.

Search of DNA sequences and primer design

28

A list of about 1,000 asteraceae microsatellites (the majority were L. sativa) showing the

GenBank database accession numbers with their motifs, and the number of repeats will

kindly provided by Andreas Matern, Cornell University, Ithaca, New York. The entire

DNA sequence for each accession is searched, retrieved from the GenBank database and

verified for the presence of SSRs. If the SSR is not at, or very close to, either the 5′ or 3′

end, the sequence is collected. Prior to primer design, all the saved DNA sequences will

be analyzed using the program DNASIS (Hitachi America Ltd., San Bruno, Cal.) for

homologous sequences. Each sequence will be compared with the rest of the DNA

sequences. If homologous sequences are found, only one unique sequence will kept for

primer design while the rest of the homologous DNA sequences will be eliminated

because of their redundancy. PCR primers (forward and reverse) flanking the repeat

sequence will be designed using the computer program GENE RUNNER (Hastings

Software, Inc., N.Y.). The core parameters used in the primer design include the

following: (1) the primer length is between 18 bp and 25 bp, (2) the percentage of GC is

between 35% and 60%, (3) the Tm of the primers is over 40 °C which will be calculated

using Tm = 59.9 + 0.41 (%G+C) – (675/primer length) based on the standard PCR

conditions at a salt concentration of 50 mM (Sharrocks, 1994), and (4) the predicted PCR

products range from 100 to 350 bp in length with a preference of between 100 bp and 250

bp. In addition, the primer internal structures, such as hairpin loops, possible primer

dimers, length of single base pair run at the 3′ end and the number of short repeats (such

as CT, GA etc.) will also be taken into consideration. When two or more SSRs are

located in the same DNA sequence but are at different sites, two flanking primers are

29

designed separately for each of the SSRs. All designed oligonucleotides will be

synthesized commercially by Sigmagenosys, Incorporated.

SSR primers will be obtained from Operon Technologies Inc. (Alameda, CA) and tested.

Single DNA molecular marker system, SSR, will be used to test seed genetic purity. SSR

primers will be obtained from OperonTechnologies Inc., SSR-PCR will be performed in

PTC-100 thermocycler (MJ Research Inc., USA) according to the protocol of (Williams

et al., 1990) and (Zietkiewicz et al., 1994) respectively. The SSR amplification products

will be separated and detected according to the reported methods (Liu et al., 2007a).

The oligonucleotide primers for SSR analysis will be synthesized by Invitrogen Biotech

(Shanghai) Co., China, according to the reported sequences of microsatellite markers (He

et al., 2003). The SSR-PCR reactions will be performed and products will be detected

according to the reported protocol (Liu et al., 2007a) .

PCR amplification and product electrophoresis

PCR reactions will be performed in 96-well plates using either the Perkin Elmer

GeneAmp PCR system 9600 (PE Biosystems) or the TECHNE Genius themal cycler

(Techne Ltd., U.K.) with the same amplification program. Each 10-μl reaction mixture

contained about 25 ng of lettuce genomic DNA, 0.3 μM of forward and reverse primers,

300 μM of each dNTP, 1 μl of 10 × PCR buffer containing 100 mM of Tris–HCl, pH 8.3,

500 mM of KCl, and 1 unit of Taq DNA polymerase. The PCR amplification conditions

will be programmed as one cycle of denaturation at 94 °C for 2 min, followedby 35-

30

cycles amplification with a 25 s denaturing at 94 °C, a 25 s annealing at the Tm (Tm

varies for the individual primers) and a 25 s extension at 68 °C. After PCR amplication,

the products will be mixed with 3 μl of stop buffer (97% deionized formamide, 0.3%

each bromophenol blue and xylene cyanol FF and 10 mM of EDTA, pH 8.0) and then

denatured at 94 °C for 5 min in a PCR machine. Four micro litres of each denatured PCR

product will be used for fragment separation on a DNA sequencing gel

(6% polyacrylamide, 8 M urea and 1 × TBE buffer) running at a constant power of 55 W

for 2–2.5 h, using an S2 sequencing-gel apparatus (GIBCO BRL). A 1-kb-plus DNA size

marker will also be loaded along with the samples for each run to estimate the fragment

sizes of the separated DNA fragments. After each run, the gel was placed in 10% glacial

acetic-acid fixation solution for 20 min with gentle shaking, silver-stained for 30 min and

then immediately developed in a 3% sodium carbonate solution according to the DNA

silver-staining kit (Promega).

Nomenclature of SSR markers

The nomenclature of the SSR markers will be based on the method described by (Yu et

al., 2000). The SSR name will be prefixed with LS standing for L. sativa, followed by the

repeat motif in lowercase and a number starting from 001 for each distinct repeat motif.

For example, LSaat001 and LSaat002 re-present, respectively, the SSR markers at two

different loci with the same repeat motif “aat”. For the imperfect or compound repeats,

such as (AAG)3T(TGA)7, only the motif with the highest repeat number, in this case

TGA, is used. When two or more different repeats such as the SSR locus

31

(CT)12(GATA)12(AT)2(AC)10 have the same number of repeats, the repeat motif at the

5′ end is used. Thus, the SSR name for (CT)12(GATA)12(AT)2(AC)10 is designated as

LSct rather than LSgata. This SSR nomenclature system can be applied to any newly

developed microsatellites and provides a simple way to track SSR loci for use in a

breeding program.

Genetic analysis

All 18 genotypes from different geographic origins will be used to screen the SSR

primers for PCR amplification and product-length polymorphism. For primers that

produced the expected fragments after PCR reactions, the number of alleles will be

recorded and the polymorphism information content (PIC) of an SSR locus will be

calculated as described by (Saal and Wricke, 1999):

PIC= 1-∑i=1

K

pi2

where pi is the frequency of the ith allele out of the total number of alleles at an SSR

locus, and k is the total number of different alleles for that locus. For phylogenetic

analysis, only the data for the polymorphic SSR loci are entered for all DNA samples,

and a “1” or “0” is used if an allele is present or absent for a genotype, respectively. The

data will be analyzed using the computer program TREECON (Van de Peer and De

Wachter 1994). The genetic-distance estimation will be based on the method described

by (Nei and Li, 1979). All 18 different lettuce genotypes will be clustered based on the

estimated genetic distance, and the phylogenetic tree topology was inferred with the

clustering method of the Unweighted Pair Group Method Using Arithmetic Average

(UPGMA).

32

Summary

Literature Cited

Abdulla, M.and P. Gruber. 2000. Role of diet modification in cancer prevention. Biofactors. 12: 45-51.

Anonymous. 1989. Committee on Diet and Health. Food and Nutrition Board. National Research Council. Minerals. , p. 347-366. In: Diet and health: implecations for reducing chronic disease risk. National Academy Press, Washington, DC.

Anonymous. 2000. U.S. Department of Health and Human Services. Healthy People 2010. 2nd edition. Objectives for Improving Health (Part B: Focus Areas 15–28). Vol. II. Objective 19–11., Washington, DC: U.S. Government Printing Office.

Anonymous. 2005. Plants lose their value. Food Magazine 68 (Jan/Mar):1.

Anonymous. 2006. Meat and dairy: where have the minerals gone. Food Magazine 72 (Jan/Mar):10.

Areshchenkova, T.and M.W. Ganal. 1999. Long tomato microsatellites are predominantly associated with centromeric regions. Genome. 42: 536-544.

Ashkar, S.A.and S.K. Ries. 1970. Lettuce tipburn as related to nutrient imbalance and nitrogen composition, Michigan State University. Dept. of Horticulture.

Ashmead, H. 1982. Chelated mineral nutrition in plants. In D. W. Ashmead, Animals and man (pp. xi±xv). Springfield, IL: C.C. Thomas.

Ayoub, A.T. 1998. Extent, severity and causative factors of land degradation in the Sudan. Journal of Arid Environments. 38: 397-409.

Barker, A.V. 1975. Organic vs. inorganic nutrition and horticultural crop quality. HortScience. 10: 50-53.

Baynes, R.D.and T.H. Bothwell. 1990. Iron Deficiency. Annual Review of Nutrition. 10: 133-148.

Benbrook, C.and C. Scientist. 2009. The Impacts of Yield on Nutritional Quality: Lessons from Organic Farming. HortScience. 44: 12-14.

Benbrook, C., X. Zhao, J. Yáñez, N. Davies, and P. Andrews. 2008. New evidence confirms the nutritional superiority of plant-based organic foods. The Organic Center,

33

http://www.organic-center.org/reportfiles/Nutrient_Content_SSR_Executive_Summary_FINAL.pdf.

Bernstein, M.A., M.E. Nelson, K.L. Tucker, J. Layne, E. Johnson, A. Nuernberger, C. Castaneda, J.O. Judge, D. Buchner, and M.F. Singh. 2002. A Home-Based Nutrition Intervention to Increase Consumption of Fruits, Vegetables, and Calcium-Rich Foods in Community Dwelling Elders. Journal of the American Dietetic Association. 102: 1421-1427.

Boodley, J.W., S.E. Newman, D.W. Jackson, E. Plaster, C.C. Sheaffer, K.M. Moncada, R. Emmons, M. Loehrlein, H.E. Reiley, and C.L. Shry Jr. 1996. The commercial greenhouse, 3rd edition. Delmar Publishers, Albany, NY.

Bradstreet, R.B. 1965. The Kjeldahl method for organic nitrogen (1965) London, UK: Academic Press.

Broun, P.and S.D. Tanksley. 1996. Characterization and genetic mapping of simple repeat sequences in the tomato genome. Molecular and General Genetics MGG. 250: 39-49.

Brown, K.M.and J.R. Arthur. 2007. Selenium, selenoproteins and human health: a review. Public Health Nutrition. 4: 593-599.

Brumm, I.and M. Schenk. 1992. Influence of Nitrogen Supply on the Occurence of Calcium Deficiency in Field Grown Lettuce. p. 125-136.

Buol, S.W. 1995. Sustainability of soil use. Annual Review of Ecology and Systematics. 26: 25-44.

Cakmak, I. 2009. Enrichment of fertilizers with zinc: An excellent investment for humanity and crop production in India. Journal of Trace Elements in Medicine and Biology. 23: 281-289.

Cavagnaro, P., S.-M. Chung, M. Szklarczyk, D. Grzebelus, D. Senalik, A. Atkins, and P. Simon. 2009. Characterization of a deep-coverage carrot ( Daucus carota L.) BAC library and initial analysis of BAC-end sequences. Molecular Genetics and Genomics. 281: 273-288.

Chan, S., B. Gerson, and S. Subramaniam. 1998. The role of copper, molybdenum, selenium, and zinc in nutrition and health. Clinics in laboratory medicine. 18: 673.

Chow, K.K., L. Meng-Wei, and H.L. Choo. 1999. Effects of Nutrient Composition on Butterhead Lettuce (Lactuca sativa L. cv. Panama) Grown in Deep Flow Technique for the Tropics. Acta Horticulturae: 135-146.

Curley, J.and G. Jung. 2004. RAPD-Based Genetic Relationships in Kentucky Bluegrass: Comparison of Cultivars, Interspecific Hybrids, and Plant Introductions. Crop Sci. 44: 1299-1306.

34

http://www.organic-center.org/reportfiles/Nutrient_Content_SSR_Executive_Summary_FINAL.pdf

http://www.organic-center.org/reportfiles/Nutrient_Content_SSR_Executive_Summary_FINAL.pdf

Darnton-Hill, I., P. Webb, P.W.J. Harvey, J.M. Hunt, N. Dalmiya, M. Chopra, M.J. Ball, M.W. Bloem, and B. de Benoist. 2005. Micronutrient deficiencies and gender: social and economic costs. Am J Clin Nutr. 81: 1198S-1205.

Davis, D.R. 2009. Declining Fruit and Vegetable Nutrient Composition: What Is the Evidence? HortScience. 44: 15-19.

Dobermann, A., P.C.S. Cruz, and K.G. Cassman. 1996. Fertilizer inputs, nutrient balance, and soil nutrient-supplying power in intensive, irrigated rice systems. I. Potassium uptake and K balance. Nutrient Cycling in Agroecosystems. 46: 1-10.

Elless, M.P., M.J. Blaylock, J.W. Huang, and C.D. Gussman. 2000. Plants as a natural source of concentrated mineral nutritional supplements. Food Chemistry. 71: 181-188.

Fox, C., D. Ramsoomair, and C. Carter. 2001. Magnesium: its proven and potential clinical significance. Southern Medical Journal. 94: 1195-1201.

Guenther, P.M., B.P. Perloff, and T.L. Vizioli. 1994. Separating fact from artifact in changes in nutrient intake over time. Journal of the American Dietetic Association. 94: 270-275.

He, C. He, Poysa, V. Poysa, Yu, and K. Yu. 2003. Development and characterization of simple sequence repeat (SSR) markers and their use in determining relationships among Lycopersicon esculentum cultivars. TAG Theoretical and Applied Genetics. 106: 363-373.

Heaney, R.P. 2001. Calcium Needs of the Elderly to Reduce Fracture Risk. J Am Coll Nutr. 20: 192S-197.

Herencia, J.F., J.C. Ruiz-Porras, S. Melero, P.A. Garcia-Galavis, E. Morillo, and C. Maqueda. 2007. Comparison between Organic and Mineral Fertilization for Soil Fertility Levels, Crop Macronutrient Concentrations, and Yield. Agron J. 99: 973-983.

Hesse, P.R. 1971. A Textbook of Soil Chemical Analysis, Chemical Pub, Co.

Hoagland, D.R.and D.I. Arnon. 1950. The water culture method for growing plants without soil. California Agricultural Experiment Station Circular. 347: 1-32.

Jones Jr, J.B., B. Wolf, and H.A. Mills. 1991. Plant Analysis Handbook. Micro-Macro Publ. Inc., Athens, GA.

Joshi, S.P., V.S. Gupta, R.K. Aggarwal, P.K. Ranjekar, and D.S. Brar. 2000. Genetic diversity and phylogenetic relationship as revealed by inter simple sequence repeat (ISSR) polymorphism in the genus Oryza. TAG Theoretical and Applied Genetics. 100: 1311-1320.

35

Kalra, Y.P. 1998. Handbook of reference methods for plant analysis. CRC Press, Boca Raton.

Kamchan, A., P. Puwastien, P.P.P.P. Sirichakwal, and R. Kongkachuichai. In vitro calcium bioavailability of vegetables, legumes and seeds. Journal of Food Composition and Analysis. 17: 311-320.

Karll, E. 2000. Calcium and vitamin D, p. 173-181. In: M.A.F. Singh (ed.). Exercise, nutrition, and the older woman: wellness for women over fifty. CRC Press., Washington, DC.

Kataki, P.K.and S.C. Babu. 2002. Food systems for improved human nutrition: linking agriculture, nutrition, and productivity. Food Products Press, Binghampton, N.Y.

Kong, Q., C. Xiang, and Z. Yu. 2006. Development of EST-SSRs in Cucumis sativus from sequence database. Molecular Ecology Notes. 6: 1234-1236.

Krause, M.V.and L.K. Mahan. 1984. Minerals, p. 144–180. In: Krause and Mahan (eds.). Food, nutrition, and diet therapy. 7th edition. W. B. Saunders Company, Philadelphia, PA.

Lal, R.and B.R. Singh. 1998. Effects of soil degradation on crop productivity in East Africa. Journal of sustainable agriculture (USA).

Levander, O.A. 1990. Fruit and vegetable contributions to dietary mineral intake in human health and disease. HortScience. 25: 1486-1488.

Levinson, G.and G.A. Gutman. 1987. Slipped-strand mispairing: a major mechanism for DNA sequence evolution. Molecular biology and evolution. 4: 203.

Liebig, M.A., J.W. Doran, and A.R.S. Usda. 1999. Impact of organic production practices on soil quality indicators.

Lierop, W. 1976. Digestion procedures for simultaneous automated determination of NH4, P, K, Ca and Mg in plant material. Canadian Journal of Soil Science (Canada).

Liu, L. Liu, Guo, W. Guo, Zhu, X. Zhu, Zhang, and T. Zhang. 2003. Inheritance and fine mapping of fertility restoration for cytoplasmic male sterility in Gossypium hirsutum L. TAG Theoretical and Applied Genetics. 106: 461-469.

Liu, G., L. Liu, Y. Gong, Y. Wang, F. Yu, H. Shen, and W. Gui. 2007a. Seed genetic purity testing of F1 hybrid cabbage (Brassica oleracea var. capitata) with molecular marker analysis. Seed Science and Technology. 35: 477-486.

Liu, L., G. Liu, Y. Gong, W. Dai, Y. Wang, and F.Y.Y. Ren. 2007b. Evaluation of genetic purity of F1 hybrid seeds in cabbage with RAPD, ISSR, SRAP and SSR markers. HortScience 42:724–727.

36

Liu, L.W., Y. Wang, Y.Q. Gong, T.M. Zhao, G. Liu, X.Y. Li, and F.M. Yu. 2007c. Assessment of genetic purity of tomato (Lycopersicon esculentum L.) hybrid using molecular markers. Scientia Horticulturae. 115: 7-12.

Lundegaardh, B.and A. Maartensson. 2003. Organically Produced Plant Foods- Evidence of Health Benefits. Acta Agriculturae Scandinavica. Section B. Soil and Plant Science. 53: 3-15.

Ma, J., R.A. Johns, and R.S. Stafford. 2007. Americans are not meeting current calcium recommendations. Am J Clin Nutr. 85: 1361-1366.

Mayer, A.M. 1997. Historical changes in the mineral content of fruits and vegetables. British Food Journal. 99: 207.

Maynard, D.N., A.V. Barker, P.L. Minotti, and N.H. Peck. 1976. Nitrate accumulation in vegetables. Advances in Agronomy. 28: 71-118.

Morgan, M.F. 1941. Chemical Soil Diagnosis by the Universal Soil Testing System. Bulletin 450 (ARevision of Bulletin 392), Connecticul Agricultural Experiment Station, New Haven.

Nandwa, S.M.and M.A. Bekunda. 1998. Research on nutrient flows and balances in East and Southern Africa: state-of-the-art. Agriculture, Ecosystems & Environment. 71: 5-18.

Nei, M.and W.H. Li. 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences of the United States of America. 76: 5269-5273.

Olsen, S.R.and L.A. Dean. 1965. Phosphorus. pp. 0351049. In: C. A. Black (ed.), Methods of soil analysis. Part 2. Agronomy 9. American Society of Agronomy, Madison. WI. 9.

Ooijen, J.W., J.M. Sandbrink, M. Vrielink, R. Verkerk, P. Zabel, and P. Lindhout. 1994. An RFLP linkage map of Lycopersicon peruvianum. TAG Theoretical and Applied Genetics. 89: 1007-1013.

Panaud, O., X. Chen, and S.R. McCouch. 1996. Development of microsatellite markers and characterization of simple sequence length polymorphism (SSLP) in rice (Oryza sativa L.). Molecular and General Genetics MGG. 252: 597-607.

Pimentel, D., P. Hepperly, J. Hanson, D. Douds, and R. Seidel. 2005. Environmental, Energetic, and Economic Comparisons of Organic and Conventional Farming Systems. BioScience. 55: 573-582.

Qian, W., S. Ge, and D.Y. Hong. 2001. Genetic variation within and among populations of a wild rice Oryza granulata from China detected by RAPD and ISSR markers. TAG Theoretical and Applied Genetics. 102: 440-449.

37

Reganold, J.P., L.F. Elliott, and Y.L. Unger. 1987. Long-term effects of organic and conventional farming on soil erosion. Nature. 330: 370-372.

Richards, C.M., M. Brownson, S.E. Mitchell, S. Kresovich, L. Panella, and A.R.S. USDA. 2004. Polymorphic microsatellite markers for inferring diversity in wild and domesticated sugar beet (Beta vulgaris). Molecular Ecology Notes 4(2):243-245.

Roe, N.E. 1998. Compost utilization for vegetable and fruit crops. HortScience: a publication of the American Society for Horticultural Science (USA).

Rosen, C.J.and R. Eliason. 2005. Nutrient management for commercial fruit and vegetable crops in Minnesota. Univ. Minn. Extension Serv. BU-05886.

Saal, B.and G. Wricke. 1999. Development of simple sequence repeat markers in rye (Secale cereale L.). Genome. 42: 964-972.

Sandbrink, J.M., J.W. Ooijen, C.C. Purimahua, M. Vrielink, R. Verkerk, P. Zabel, and P. Lindhout. 1995. Localization of genes for bacterial canker resistance in Lycopersicon peruvianum using RFLPs. TAG Theoretical and Applied Genetics. 90: 444-450.

Schaetzel, T.and R. Sankar. 2000. Effect of micronutrient deficiencies on human health: Its status in South Asia, p. 55-98. In: P.K. Kataki and S.C. Babu (eds.). Food Systems for Improved Human Nutrition. Food Product Press, Binghampton, NY.

Seginer, I.D.O., P. Bleyaert, and M. Breugelmans. 2004. Modelling Ontogenetic Changes of Nitrogen and Water Content in Lettuce. Ann Bot. 94: 393-404.

Sharrocks, A.D. 1994. The design of primers for PCR, p. 5-11. In: T. Weissensteiner, H.G. Griffin, and A.M. Griffin (eds.). PCR technology: current innovations

CRC press Inc.

Sim, S.C., J.K. Yu, Y. Jo, M.E. Sorrells, and G. Jung. 2009. Transferability of cereal EST-SSR markers to ryegrass. Genome. 52: 431-437.

Simko, I. 2008. Development of EST-SSR Markers for the Study of Population Structure in Lettuce (Lactuca sativa L.). J Hered. 100: 256-262.

Smulders, M.J.M., G. Bredemeijer, W. Rus-Kortekaas, P. Arens, and B. Vosman. 1997. Use of short microsatellites from database sequences to generate polymorphisms among Lycopersicon esculentum cultivars and accessions of other Lycopersicon species. TAG Theoretical and Applied Genetics. 94: 264-272.

Stevens, M.R., E.M. Lamb, and D.D. Rhoads. 1995. Mapping the Sw-5 locus for tomato spotted wilt virus resistance in tomatoes using RAPD and RFLP analyses. TAG Theoretical and Applied Genetics. 90: 451-456.

38

Stewart, W.M. 2004. Inorganic nutrient use in the United States: Past and present. Environmental Impact of Fertilizer on Soil and Water ACS Symposium Series 872:151-160.

Stoffella, P.J., M. Ozores-Hampton, N.E. Roe, Y. Li, and T.A. Obreza. 2001. Compost Utilization in Vegetable Crop Production Systems. p. 125-128.

Tan, Z.X., R. Lal, and K.D. Wiebe. 2005. Global soil nutrient depletion and yield reduction. Journal of Sustainable Agriculture. 26: 123-146.

Thomas, R.L., R.W. Sheard, and J.R. Moyer. 1967. Comparison of conventional and automated procedures for nitrogen, phosphorus, and potassium analysis of plant material using a single digestion. Agronomy Journal. 59: 240.

Thompson, K.H.and D.V. Godin. 1995. Micronutrients and antioxidants in the progression of diabetes. Nutrition Research. 15: 1377-1410.

Turan, M.and F. Sevimli. 2005. Influence of different nitrogen sources and levels on ion content of cabbage (Brassica oleracea var. capitata). New Zealand Journal of Crop and Horticultural Science. 33: 241-249.

USD-ARS. 2003. U.S. Department of Agriculture, Agricultural Research Service. USDA National Nutrient Database for Standard Reference, Release 16. Nutrient Data Laboratory Home Page, http://www.nal.usda.gov/fnic/foodcomp. .

Vos, P., R. Hogers, M. Bleeker, M. Reijans, T. Lee, M. Hornes, A. Friters, J. Pot, J. Paleman, and M. Kuiper. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic acids research. 23: 4407.

Wahlqvist, M.L.and I. Darmadi-Blackberry. 2002. Magnesium in human health. Current Therapeutics. 43: 35.

White, P.J., E.E. Bradshaw, M.F.B. Dale, G. Ramsa, J.P. Hammond, and M.R. Broadley. 2009. Relationships between yield and mineral concentrations in potato tubers. HortScience. 44: 6-14.

Williams, J.G.K., A.R. Kubelik, K.J. Livak, J.A. Rafalski, and S.V. Tingey. 1990. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucl. Acids Res. 18: 6531-6535.

Yi, G., J. Lee, S. Lee, D. Choi, and B.-D. Kim. 2006. Exploitation of pepper EST–SSRs and an SSR-based linkage map. TAG Theoretical and Applied Genetics. 114: 113-130.

Yu, K., S.J. Park, V. Poysa, and P. Gepts. 2000. Integration of simple sequence repeat (SSR) markers into a molecular linkage map of common bean (Phaseolus vulgaris L.). J Hered. 91: 429-434.

39

http://www.nal.usda.gov/fnic/foodcomp

Yu, K.and K.P. Pauls. 1994. Optimization of DNA-extraction and PCR procedures for random amplified polymorphic DNA (RAPD) analysis in plants. PCR technology: current innovations. CRC press, Boca Raton, Florida: 193–200.

Zietkiewicz, E., A. Rafalski, and D. Labuda. 1994. Genome fingerprinting by simple sequence repeat (SSR)-anchored polymerase chain reaction amplification. Genomics. 20: 176-183.

40

Documents

people.umass.edupeople.umass.edu/jmeagy/Increasing Nutrient Density of... · Web viewOrganically grown fruits and vegetables might differ from conventionally grown produce due to