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Coffee-crop monitoring using sensor networks inKarnatakaRahul Bhargava, [email protected] June 2014
Monitoring for precision agriculture involves the procurement andmaintenance of sensing hardware, and software and processes for re-cording, collating and analysing data. A partnership for interpretationof data is anticipated and may result following consultations withplantation personnel and extension experts.
Following settling on the hardware, support software and systemscan be put together and this proposed sequence of decision mak-ing motivates the presentation of curated options below, hardwarefollowed by software, to present possibilities before entering intoconsultations with experts.
Contents
Coffee crop monitoring 2
Agronomy and plant physiology 2
Harvesting and post-harvest . . . . . . . . . . . . . . . . . . . . 2
Weed management . . . . . . . . . . . . . . . . . . . . . . . . . 3
Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Motivation for monitoring . . . . . . . . . . . . . . . . . . . . . 4
BBCH-scale 6
Aerial vehicles for collecting data 11
Research platforms and capabilities . . . . . . . . . . . . . . . 11
Tea crop monitoring by Tea Board & National Remote Sensing Centre 13
Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Precipitation in Karnataka districts of interest 15
Chikmagalur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Kodagu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Hassan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Evapotranspiration 20
Leaf Area Index 20
Coffee crop monitoring
Coffee is one of the most valuable primary commodities worldwide.Traditionally, the crop has been cultivated on small (<50 ha) farmswhere repeated hand picking is the standard harvesting procedure.1 1 Herwitz et al. Imaging from an
unmanned aerial vehicle: agriculturalsurveillance and decision support.doi:10.1016/j.compag.2004.02.006
The major coffee growing regions in India are the districts ofChikmagalur, Coorg, and Hassan in Karnataka, Wynad, Idduki andNelliampathys in Kerala and Pulneys, Shevroys, Anamalais andNilgiris in Tamil Nadu.2 2 http://www.fao.org/fileadmin/user_
upload/agns/pdf/coffee/Annex-E.2.
Agronomy and plant physiology
Covers soil, land, water, shade and weed management for increasingthe productivity of various coffee varieties under different agro-climatic conditions.
• Soil management for soil and water conservation, including microirrigation3. 3 http://www.chickmagalur.nic.in/
htmls/ccri_agronomy.htm. Drip irriga-tion was found to be beneficial in theCauvery by Chickmagalur ResearchStation. Four litres of water per day foraround a hundred days during the dryperiod from November to May resultedin yield increases of up to 24 percentwith a cost benefit ratio of [1:5]. How-ever, high initial investment, regularmaintenance etc. makes it unsuitablefor large areas.
• Improving fertilizer use efficiency through fertigation.
• Weather models for predicting pest and disease outbreaks.
• Enhancing yield by stimulating flower induction4. Plant growth
4 Mepiquat Chloride at 1000 ppmtwice between August and Septemberenhances the yield of arabica coffee
regulators increase crop yield with a cost benefit ratio of 1:45.
5 Planofix ( 0.025%) Harmonal (0.025% )
• Identification of highly physiologically efficient cultivars.
• Hormonal manipulation to increase the crop production andcurtailing biennial bearing in coffee.
Harvesting and post-harvest
Coffee blossoms do not appear and develop uniformly throughout aplantation. The resulting fruit thus tends to ripen at different times,with spatial and temporal trends that are difficult to track and predict(Wormer, 1964
6; Cannell, 19757) 6 Wormer, T.M., 1964. The growth of
the coffee cherry. Annals of Botany 27,47–55. Quoted below7 Cannell, M.G.R., 1975. Crop physiolo-gical aspects of coffee bean yields: areview. Journal of Coffee Research 5,7–20. Summarises existing informationon coffee crop physiology emphas-ising whole-plant physiology andcharacteristics influencing yield.
In Kenya the coffee berry stays in the ‘pin-head’ stage for approxim-ately 6–8 weeks after flowering. A period of rapid growth followswhich ends when the berry is about 17 weeks old. Thereafter, a smallloss of fresh weight seems to occur while the dry weight remains con-stant for about two weeks. At this stage the beans have attained their fi-nal size but dry matter can be as low as 9 per cent. Until the time whenripening begins, the fresh weight of the berry increases little while thedry weight increases regularly. In this period dry weight is laid downmainly in the beans which attain their final dry weight when the berryis still green. During ripening of the berry (which is in fact ripeningof the pulp) the fresh weight of the beans drops slightly due to lossof water. Both fresh weight and dry weight of the pulp (includingparchment) increase considerably during ripening by approximately
2
121 per cent. and 106 per cent. respectively. Annals of Botany (1964) 28
(1): 47-55 http://aob.oxfordjournals.org/content/28/1.toc
Due to variations on individual trees as well as in differentsections of a field, mechanical harvesting yields a mixture of un-ripe, ripe, and overripe fruit in varying proportions (Reddy andSrinivasan, 1979
8; Cannell, 1985). Ripe fruit has the highest value, fol- 8 Reddy, G.S.T., Srinivasan, C.S., 1979.Variability for flower production, fruitset and fruit drop in some varietiesof Coffea arabica L. Journal of CoffeeResearch 9, 27–34.
lowed by overripe and then unripe. To maximize value, crop ripenessstage is a main consideration of harvest managers (Watson, 1980
9;
9 Watson, A.G., 1980. The mechanisationof coffee production. In: Proceedings ofthe Ninth International Coffee ResearchConference, London, pp. 681–686.
Willson, 199910). Managers typically rely on repeated manual cherry
10 Willson, K.C., 1999. Coffee, Cocoaand Tea. Crop Production Sciencein Horticulture Series No. 8, CABIPublishing, Oxford, UK.
counts made by field scouts and taken on a few sample brancheswithin each field. Without removing the fruit, the scouts visually sortcherries on each branch by ripeness category to estimate field-levelpercentages.
• Post harvest practices, development and evaluation of machineryand production of value added products from coffee waste.
• Pesticide, residues, and microbial / mycotoxin contamination incoffee.
• Water pollution emanating from wet processing of coffee.
Weed management
Another important and costly aspect of coffee production and harvestis weed proliferation. Weed eradication, which is required to main-tain crop yield, poses significant production and environmental costs.With crop heights generally exceeding 2m and between-rowalleysgenerally difficult to negotiate, field interiors are not readily viewedor mapped from the ground. Large weeds in the form of grassesand vines can significantly slow the harvesting process, and thusadversely affect the overall schedule.
Pathology
Coffee is a perennial crop that remains in the field for many years.This allows some insects to maintain an uninterrupted succession ofgenerations without leaving the plant, unlike those on annual cropswhere the pest must move elsewhere after the plant dies. Othersmay be permanently associated with coffee and have a narrow hostrange, but their populations increase to damaging levels undercertain favourable conditions, e.g. antestia and the Lyonetiid moths(Leucoptera spp.). Those that feed upon the berries, such as theberry borer (Hypothenemus hampei), may be more easily controlledin areas with a defined flowering period rather than in those that
3
experience intermittent rainfall throughout the year, with continuousavailability of berries. Insect pests rarely kill the tree, but thosethat do, such as stem borers, may have a permanent effect on theplantation, as it can be difficult to re-establish bearing trees in thegap left by a dead tree. Leaf retention is essential for maximizationof coffee yields, and lowlevel but continuous loss of leaves due toleaf-feeding insect pests and Homoptera – which literally drain theplant of nutrients – can contribute to physiological dieback if they arenot controlled.11 11 Waller, J. M.; Bigger, M.; Hillocks,
R. J.. Coffee Pests, Diseases and TheirManagement. Wallingford, Oxon, GBR:CABI Publishing, 2007. p 36.
Chikmagalur has a Plant Pathology Division at the Central CoffeeResearch Institute, Coffee Research Station, that concentrates onmanagement of diseases through cultural, chemical and biologicalmethods12. Periodic surveys of plantations are undertaken, for 12 http://www.chickmagalur.nic.in/
htmls/ccri_plant_path.htmadvisories on possible disease outbreaks, prior to making diseasecontrol recommendations, and training growers, plantation managersand extension personnel.
Current programs address integrated disease management ofcoffee leaf rust disease13, updating disease control recommendations 13 Plantvax 20 EC and Bayleton 25 EC
are being recommended against leafrust disease. An alkaline Bordeaux mix-ture for spraying is being recommendedfor prevention
and developing a spray schedule against coffee diseases.
Nutrients
Water and nutrient availability are key production factors for coffee,as for most other crops. Fertilizer is required to replace substantialquantities of nutrients lost to harvest.
Motivation for monitoring
“India cultivates all of its coffee under a well-defined two-tier mixedshade canopy, comprising evergreen leguminous trees. Nearly 50
different types of shade trees are found in coffee plantations. Shadetrees prevent soil erosion on a sloping terrain; they enrich the soil byrecycling nutrients from deeper layers, protect the coffee plant fromseasonal fluctuations in temperature, and play host to diverse floraand fauna.14 14 http://www.indiacoffee.org/
coffee-regions-india.html“Coffee plantations in India are essential spice worlds too: a widevariety of spices and fruit crops like pepper, cardamom, vanilla,orange and banana grow alongside coffee plants.”
1. Integrated pest management is preferred, using techniques suchas targeted treatment of pest outbreaks, and managing crop en-vironment away from conditions favouring pests, to spraying ofinsecticides which has often proven to be counter-productive,as the predators of the pests are more sensitive than the peststhemselves.
4
Factors Arabica Robusta
Soils Deep, fertile, rich inorganic matter, welldrained and slightlyacidic (pH 6.0–6.5)
Same as Arabica
Slopes Gentle to moderateslopes
Gentle slopes to fairlylevel fields
Elevation 1000–1500m 500–1000mAspect North, East and North–
East aspectsSame as Arabica
Temperature 15◦C–25
◦ C ; cool,equable
20◦C–30
◦ C; hot, humid
Relativehumidity
70–80% 80–90%
Annualrainfall
1600–2500 mm 1000–2000 mm
Blossomshowers
March– April (25–40mm) February –March (25–40
mm)Backingshowers
April–May (50–75 mm)well distributed
March–April (50–75 mm)well distributed
Table 1: Growing conditions
2. Growing coffee is water intensive. Terrain maps may assist withplanning surface runoff. For successful production, a free drainingsoil with a minimum depth of 3 feet (1 m) is required. Coffee willnot tolerate water-logging or ‘wet feet’.15 15 http://www.fao.org/docrep/008/
ae938e/ae938e03.htm3. Testing pH is particularly important for coffee. A pH of 5 or 6
is ideal, lower pH affects yield. Dolomite, Calcium MagnesiumCarbonate, is added as a pH buffer and as a magnesium source.As is lime, Calcium Oxide or Calcium hydroxide, to the soil.16 16 Ibid.
4. Arabica is the more sensitive species to invertebrate predationoverall. For reference, ideal conditions are highlighted for Arabica,from the literature. Arabica coffee prefers a cool temperaturewith an optimum daily temperature of 68
◦ to 75◦F (20
◦ to 24◦C).
Temperatures greater than 86◦F (30
◦C) cause plant stress leadingto a cessation of photosynthesis. Mean temperatures of less than59
◦F (15◦C), limit plant growth and are considered suboptimal. As
Arabica coffee is susceptible to frost damage, use of shade treeswill reduce the incidence.
5. Ideal rainfall for Arabica coffee is greater than 47 to 60 inches(1200 to 1500 mm) per year
6. An easterly or southern facing aspect with a slope less than 15%
5
is preferable. Steeper slopes present a major erosion risk and re-quire terracing or special management such as contour furrows orpreferably grass strips. A slight slope will improve air drainageand reduce damage from frost. Do not plant coffee at the bottomof a slope or in shallow dips where cold air can pool, as frost dam-age is more likely here. Usually it is best not to plant the bottomthird of a slope as it will be colder and sometimes waterlogged.
7. Coffee requires adequate water during the growing and croppingperiod, however it also requires a dry stress period followed bysufficient rain or irrigation to promote uniform flowering anda good fruit set. Many plantings suffer from moisture stress atthe time of year when they need adequate water for growth andcropping. Unless regular rain is received, young newly plantedtrees should be irrigated (or hand watered at least twice a weekif irrigation is not available) to ensure establishment. Locatingcoffee plantings near a water supply for possible irrigation as wellas for processing of cherry is desirable. Water requirements canbe reduced by use of suitable, well-established shade trees andmulch.
BBCH-scale
Biologische Bundesanstalt, Bundessortenamt und CHemische Indus-trie17. The BBCH scale is a system for a uniform coding of phenolo- 17 Federal Biological Research Centre,
Federal Office of Plant Varieties andCHemical industry
gically similar growth stages of all mono- and dicotyledonous plantspecies.
Phenological development stages of plants to play importantrole in agricultural planning research (eg phytopathology and plantbreeding), so but in applied botanical sciences.
They are used in the agricultural industry (eg agricultural met-eorology, timing of fertilization or pesticide application, agriculturalinsurance)18. 18 http://www.jki.bund.de/en/
startseite/veroeffentlichungen/
bbch-codes.html
6
00 05
09 1020
19/33
21/90 23/93 25/94 29/97
DryCseed
SeedCradicalprotrusionandChooking
EmergenceCotyledonsunfolded
FirstCpairCofCprimaryCbranchesCvisible
9CorCmoreCleafCpairsunfolded/Branchelongation,C30CnodespresentCinCbranches
51
59
71
79
77
60
57Inflorescenceybudsyswellingyinyleafyaxils Closedyflowersyvisible
Elongatedyclosedypetals Firstyfloweryopen
Berryygrowthybeginning Fruitsyareydarkygreen
Fruitymature
Growth stage Code Description
0: Germination,vegetative propagation
0 Dry seed (11-12% moisture content), beige color if parch-ment present or bluish-green if parchment and silver skinremoved. Cutting (orthotropic, mononodal, 60 mm long, twohalf trimmed leaves). Stump with bulky nodes and no budsvisible
1 Beginning of seed imbibition, bean swollen, whitish, no radiclevisible. Cutting planted in rooting media, no shoots visible, nocallus visible
2 Seed imbibition complete, bean whitish, small swelling vis-ible at one end of bean where the embryo is located. Callusformation begins on cuttings. Bud burst start on stumps
5 Seed radicle protrusion and hooking. Shoot and root formationon the cuttings. Green, rounded buds visible on the stumps
6 Elongation of radicle, formation of root hairs and lateral rootson seeds and cuttings.
7 Hypocotyl with cotyledons breaking through the seed coat.Cuttings have formed shoots and branched roots.
9 Emergence: Seeds have emerged from soil and show the hy-pocotile with cotyledons still enclosed in the parchment. Thecuttings present roots 6-7 cm. long and shoots with 1-2 nodes.Stumps show sprouts with first leaf initials.
1: Leaf development onmain shoot of the youngplant, and branches ofthe coffee tree
10 Cotyledons completely unfolded. First pair of true leaves separ-ating on shoot or first pair of true leaves separating on branchof the coffee tree
11 first leaf pair unfolded, not yet at full size. Leaves are lightgreen or bronze
12 2 leaf pairs unfolded, not yet at full size. Leaves are light greenor bronze
13 3 leaf pairs unfolded, not yet full size. The third leaf pair fromapex is dark green
14 4 leaf pairs unfolded. The fourth leaf pair from apex is darkgreen and has reached full size
1{5–8} Stages continues till...19 9 or more leaf pairs unfolded
2: Formation of branches(only for plants in thefield)
20 First pair of primary branches are visible21 10 pair of primary branches visible22 20 pair of primary branches visible23 30 pair of primary branches visible2{4–8} Stages continues till...29 90 or more pairs of primary branches visible
3: Branch elongation
31 10 nodes present in the branch(es)
9
Table 3 – continued
Growth stage Code Description
32 20 nodes present in the branch(es)3{3–8} Stages continues till...39 90 or more nodes present in the branch(es)
5: Inflorescenceemergence
51 Inflorescence buds swelling in leaf axils53 Inflorescence buds burst and covered by brown mucilage; no
flowers visible57 Flowers visible, still closed and tightly join, borne on multi-
flowered inflorescence (3-4 flowers per inflorescence)58 Flowers visible, untight, still closed, petals 4-6 mm long and
green (dormant stage)59 Flowers with petals elongated ( 6-10 mm long), still closed and
white color.
6: Flowering
60 First flowers open61 10% of flowers open63 30% of flowers open65 50% of flowers open67 70% of flowers open69 90% of flowers open
7: Development of fruit
70 Fruits visible as small yellowish berries71 Fruit set: Beginning of berry growth. Fruits have reached 10%
of final size (pinheads).73 Fruits are light green and contents are liquid and crystalline.
Fruits have reached 30% of final size (fast growth).75 Fruits are light green and its contents are liquid and crystalline.
Fruits have reached 50% of final size.77 Fruits are dark green and its contents are solid and white.
Fruits have reached 70% of final size.79 Fruits are pale green and its contents are solid and white.
Physiological maturity is complete. Fruits have reached 90% offinal size.
8: Ripening of fruit andseed
81 Beginning of change of fruit coloration from pale green toyellow or red
85 Increase in intensity (variety-specific), yellow or red, fruit color;fruit not yet ready for picking.
88 Fruit is fully ripe color and ready for picking.89 Overripe; beginning of darkening or drying; fruits stay on the
tree or abscission begins.
10
Table 3 – continued
Growth stage Code Description
9: Senescence
90 Shoots have completed their development; the plant appearsof an intense dark green color, leaves are of normal size andharvest locates at the bottom part of the plant.
93 Older leaves change its color from deep green to yellow withred spots, and fall specially at harvesting time.
94 The foliage changes to a pale green color. Defoliation isobserved on the bottom part of the main stem and lowerbranches.
97 The production zone has moved towards the upper parts in themain shoot and outer parts of branches, leaves are of smallersize than normal, strong defoliation is observed on the bottomand inner part of the plant, some dead branches are observedat the bottom.
98 The production zone is limited to a very few branches onthe top of the shoot and a very few nodes on the tip of thesebranches, and the plant is heavily defoliated. A high-degreeof senescence has been reached. 90% or more of the harvestcompleted.
99 Post harvest or storage treatments
Table 3: BBCH-scale, coffee. http://en.wikipedia.org/wiki/BBCH-scale_%28coffee%29, J Arcila-Pulgarínet al.(2002), Application of the extended BBCH scale for the description of the growth stages of coffee(Coffea spp.). Annals of Applied Biology, 141: 19–27. doi:10.1111/j.1744-7348.2002.tb00191.x
Aerial vehicles for collecting data
Research platforms and capabilities
1. Paparazzi UAV Project19. Autopilot system. Small Unmanned Ob- 19 http://wiki.paparazziuav.org/
wiki/Main_Pageserver (SUMO)20 uses industry standard sensors for temperature,20 http://wiki.paparazziuav.org/
wiki/SUMOair pressure, humidity and wind speed/direction as well as morespecialized sensors as infrared/visible light radiation, particleconcentration or ionizing radiation.
(a) Ground station. Laptop, a bi-directional modem, a standardRC transmitter and battery chargers
(b) Ground modem. 2.4GHz Digi XBee Series 121 21 Communication options,
http://www.evelta.com/
semiconductors-and-actives/
communication?page=2
2. Ardupilot UAV platform for controlling autonomous multicopters,fixed-wing aircraft, traditional helicopters and ground rovers.
11
Stage Description
0 Germination / sprouting / bud development1 Leaf development (main shoot)2 Formation of side shoots / tillering3 Stem elongation or rosette growth / shoot development
(main shoot)4 Development of harvestable vegetative plant parts or
vegetatively propagated organs / booting (main shoot)5 Inflorescence emergence (main shoot) / heading6 Flowering (main shoot)7 Development of fruit8 Ripening or maturity of fruit and seed9 Senescence, beginning of dormancy
Table 2: Principal growth stages
0
1
2
3
45
6
7
8
9
0
0
0
0
0
0
0
0
0
0 9
9
9
9
9
9
9
9
9
9
SchemeFrui
tRi
peni
ng
Senescence Germ sprouting
Leaves
Inflorescence
Flowering Side shoots
Roset
tes
Plan
tp
arts
Figure 1: Subdivision of thedevelopmental cycle of coffeeplants
3. Flying capabilities. Flight controllers compared22 22 http://oddcopter.com/
flight-controllers/Gyro Stabilization Ability to easily keep the copter stable and level
under the pilot’s control. This is a standard feature of all flightcontrol boards.
Self Leveling Ability to let go of the pitch and roll stick on thetransmitter and have the copter stay level.
Care Free The pilot can control the copter as if it is pointing in itsoriginal direction as the orientation of the copter changes.
Altitude Hold Ability to hover a certain distance from the groundwithout having to manually adjust the throttle.
Position Hold Ability to hover at a specific location.
Return Home Ability to automatically return to the point wherethe copter initially took off.
12
Waypoint Navigation Ability to set specific points on a map thatcopter will follow as part of a flight plan.
Board Ope
nso
urce
Gyr
ost
abil
ised
Self
leve
ling
Car
efr
ee
Alt
itud
eho
ld
Posi
tion
hold
Ret
urn
hom
e
Way
poin
tna
viga
tion
ArduCopter APM 2.5 4 4 4 4 4 4 4 4
AutoQuad 4 4 4 4 4 4 4
Hobbyking KK2.1.5 4 4 4
MultiWii Pro 2.0 w/GPS 4 4 4 4 4 4 4 4
Pixhawk 4 4 4 4 4 4 4
Table 4: Controller web links,ArduCopter, AutoQuad,Hobbyking, MultiWii, Pixhawk
Tea crop monitoring by Tea Board & National Remote Sensing Centre
A tea plantation monitoring project is being undertaken by an affili-ated institute, the National Remote Sensing Centre23, Indian Space 23 http://www.nrsc.gov.in/Earth_
Observation_Applications_
Agriculture_Tea_Management.htmlResearch Organisation.
“A pilot study was carried out in Bagdogra area of North Bengalto address the Remote Sensing and GIS (Geographic InformationSystem) capability in tea area development using multispectral andmulti-resolution satellite data supported by ground intelligence toaddress precise mapping of the tea gardens with section details,pruning types, shade tree density, garden landuse and gap areas.
“Based upon the encouraging results of the pilot study, [the]Tea Board [..] agreed formally to initiate the project on “Tea areadevelopment and management using Remote Sensing and GIS”.
“The Tea Board will facilitate
• the collection of garden maps and relevant data,
• field surveys and
• interaction with garden managers, and
• validation of results.
“Based on several interactions with tea garden managers, anResearch and Development component [is part of the] project, apartfrom operations and capacity building, [involving].
• remote estimation of green leaf yield,
13
• forecasting of some pests and diseases,
• surface hydrology and drainage planning
Objectives
Major objectives include,
• Mapping of tea growing areas (major, medium and small) usinghigh-resolution Indian satellite data.
• Analysis of detailed tea garden land-use and mapping.
• Geo-referencing of tea garden maps with respect to satellite dataand creation of spatial garden database.
• Analysis of canopy density of the shade trees using Cartosat-1satellite data and mapping to characterize optimal, high or lowdensity classes.
• Identification of degraded tea areas for uprooting and re-plantation.
• Generation of fine quality Digital Elevation Model (DEM) usingCartosat-1 satellite stereo pair.
• Use of Cartosat-1 DEM for generation of potential surface waterflow lines for diversion of flood water.
• Site suitability analysis for new area of tea plantation.
• Monitoring uprooting and re-plantation activities.
• Generation of comprehensive database of natural resources andinfrastructure of Tea gardens.
• Development of comprehensive web-enabled GIS and MIS for theTea gardens to establish network between Tea Board, Tea ResearchInstitutes and Tea Gardens for better management and also toprovide technical support to Tea gardens.
Outputs
• Geographically referenced hard- and soft-copy digital maps (incadastral scale24) of all the tea gardens at section- [level resolution] 24 (of a map or survey) shows the extent,
value, and ownership of land, especiallyfor taxation.
including small growers, most of [whom] are unregistered [withthe] tea board.
• Updated information on garden land-use, shade tree density, gapareas, garden areas affected by river bank erosion, changes in theriver course.
14
• Availability of section-, division-, garden-level detail includingstatic and dynamic attribute information on the desktop for aug-menting informed decision making.
• Near real time acquisition of information across different teagardens through web enabled data sharing.
Outcomes
• Monitoring uprooting and re-plantation especially in the lowyielding areas of old bushes which is the key to long term compet-itiveness of the Indian tea industry.
• Will help [document] small growers enabling them to avail fin-ancial assistance from the Tea Board or from banks and financialinstitutions.
• News flash pertaining to different stakeholders through tea boardportal.
• Long term policy formulation
Year Ara
bica
Rob
usta
Tota
l
2007–08 92,500 169,500 262,000
2008–09 79,500 182,800 262,300
2009–10 94,600 195,000 289,600
2010–11 94,140 207,860 302,000
2011–12 101,500 212,500 314,000
2012–13 98,600 219,600 318,200
2013–14 90,000 190,000 280,000
Table 5: Coffee production intonnes, Coffee Board of India &Karnataka Planters’ Association
Precipitation in Karnataka districts of interest
Chikmagalur
PlaceholderIMD Raingauge Station ListKottigehar toll, Chickmagalur, Mudigere t.o., Aldur, Gonibidu,
Seegehali estate, Chickmagalur (Obsy), Tarikere, Koppa balgadi,Narasimharajapur, Sringeri, Balehonnur (Obsy), Malapur, Attigundi,Lakkavalli, Lingada hally ps, Hariharpur, Kalasa , Hirebyle, Bale-honnur, Mudigere r.r.s., Jayapura, C.r.s. Koppa, Kigga, Kamardi,Hunaseghatta, Kalasapur, Sakrepatna, Lingada hally sf, Yammidoddi,
15
Traditional coffee-growing areas
Non-traditional growing areas
North East region
Assam Nagaland
Arunachal Pradesh
MeghalayaManipur
TripuraMizoram
AndhraPradesh
Orissa
Karnataka
TamilNadu
Kerala
16
Hassan
Chikmagalur
Kodagu
17
Post-monsoon estimate ‘13–‘14 Final estimate ‘12–‘13
State/District Ara
bica
Rob
usta
Tota
l
Ara
bica
Rob
usta
Tota
l
KarnatakaChikmagalur 38280 32220 70500 37325 40300 77625
Kodagu 21075 95500 116575 21300 98700 120000
Hassan 19175 11450 30625 18800 13800 32600
Sub total 78530 139170 217700 77425 152800 230225
KeralaWayanad 0 56925 56925 0 53475 53475
Travancore 900 6800 7700 975 7200 8175
Nelliampathis 1100 1550 2650 1100 1450 2550
Sub total 2000 65275 67275 2075 62125 64200
Tamil NaduPulneys 6975 325 7300 6425 255 6680
Nilgiris 1800 4050 5850 1625 3765 5390
Shevroys (Salem) 3875 50 3925 3450 50 3500
Anamalais (Coimbatore) 1300 500 1800 1300 500 1800
Sub total 13950 4925 18875 12800 4570 17370
Non-traditional AreasAndhra Pradesh 6950 60 7010 5890 30 5920
Orissa 440 0 440 310 0 310
Sub Total 7390 60 7450 6200 30 6230
North Eastern Region 130 70 200 100 75 175
Grand Total (India) 102000 209500 311500 98600 219600 318200
Table 6: Production of coffee inmajor states/districts of India(in MT), Coffee Board of Indiahttp://www.indiacoffee.org/
coffee-statistics.html
Malandur health, Kadur, Yegati, Ajjampur, Sivani ps, Bukkambudi,Sigatagere, Panchanhalli, Basur, Ajjampura polic, Ajjampura c.b.s,Birur, Giriyapur, Hirenallur, Shivani rly.stn., Balehonnur p/crs,Burapura, Chandpura.
Kodagu
IMD Rainguage Station ListKurchy/irrupa, Virajpet, Karike, Makuta, Sampaji, Madapur, Kar-
godu, Talakauveri, Naladi, Mundrote, Galibidu, Dabkoda, Balecove,Mercara (Obsy), Mercara, K.ngr/frazerpet, Somwarpet t.o., Ammathy,Napoklu, Pulingoth, Sanivarsanthe, Poonampet ib, Bhagamandala(Hydro), Dubari , Suntikoppa, Hudugur, Srimangala, Bhagamandala,Ponnampet ars, Somwarpet, Kudige, Anekad, Madikere jail, Karada,Avandoor, Maladare forest, Watekolly, Poorlatti, Mallikarjuna, Har-angi, Murnad, Siddapura, Surlabbi, Nagarhole, Karmadu, Murkhal,Thittimatti, Mathigodu fores, Kallahalla, Devamachi, Dabsad, Kudli-pet, Shantahalli.
18
Name of the Region 2012–13
<10 >10 Total
Chikmagalur 14853 1166 16019
Hassan 11228 350 11578
Madikeri 20422 236 20658
Virajpet 22864 253 23117
Total for Karnataka 69367 2005 71372
Kerala 77110 275 77385
Tamil Nadu 15379 343 15722
Total for Traditional Areas 161856 2623 164479
Non Traditional Areas 118402 26 118428
NER Region 8002 9 8011
Grand total 288260 2658 290918
Table 7: Number of hold-ings, Coffee Board of Indiahttp://www.indiacoffee.org/
coffee-statistics.html
Year Quantity, Metric Tonnes
2000 60000
2001 64000
2002 68000
2003 70000
2004 75000
2005 80200
2006 85000
2007 90000
2008 94400
2009 102000
2010 108000
2011 (prov.) 115000
Table 8: Estimated do-mestic coffee consump-tion, Coffee Board of Indiahttp://www.indiacoffee.org/
coffee-statistics.html
Hassan
IMD Rainguage Station ListMaranahalli ttg, Ramnathpuram, Hasti estate, Gendehally, Saklespur,
Alur, Yeslurpet, Kenchammana hte, Ossoor estate, Mallipatna,Sukravarasathy, Ubban estate, Basapatna, Alur (phc), Sakalesh-pur i.b., Kunduru, Ballupet, Arkalgud, C.r.patna, Holenarsipur,Grama , Kattaya, Konalur, Hiresave, Halli mysore, Sriramdevar dam,Ganging/gorur, Shantigama, Sravanabelagola, Halkote, H.n. Pur,Hemavathy reserv, Palya, Belur, Hanbal, Arehalli, Belagodu, Hassan(Obsy), Dudda , Bagur, Nuggehalli, Gandasi, Hassan t.o., Salagama,Hassan rly, Javagal, Udaipura, Hagari , D. Hagge, Bicodu , Dod-dabommanthini, Chananahalli, Arsikere t.o., Banavara, Kanakatte,Halebid, Yelware, Arsikere s.rly., Halebeedu, Hosurodu, Bage estate,
19
Gandigi, K. Hosokte, Koragawalli est, Madvapur, Mastigar estate,Sondanahally est, Y.r.p.gorur.
Evapotranspiration
The combination of two separate processes whereby water is lost onthe one hand from the soil surface by evaporation and on the otherhand from the crop by transpiration is referred to as evapotranspira-tion (ET).
Evaporation is the process whereby liquid water is convertedto water vapour (vaporization) and removed from the evaporat-ing surface (vapour removal). Water evaporates from a variety ofsurfaces, such as lakes, rivers, pavements, soils and wet vegeta-tion.http://www.fao.org/docrep/x0490e/x0490e04.htm
Leaf Area Index
Leaf area index (LAI) is the total one-sided area of leaf tissue per unitground surface area. It is a key parameter in ecophysiology, espe-cially for scaling up the gas exchange from leaf to canopy level. Itcharac- terizes the canopyatmosphere interface, where most of the en-ergy fluxes exchange. It is also one of the most difÆcult to quantifyproperly, owing to large spatial and temporal variability. Many meth-ods have been developed to quantify LAI from the ground and someof them are also suitable for describing other structural parameters ofthe canopy.
UAVs can be used by growers of different commodities, regardlessof their crop size and type. Potential applications of this technologyin agriculture include:
• Crop scouting
• Pest distribution mapping
• Crop loss assessment
• Bare soil imagery
• Irrigation and drainage planning
• Yield estimation and monitoring
• Inventory management
• Diagnosis of herbicide injury in crops
• Selection of plants for further breeding
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• Sampling of plant pathogens in the air
• Efficient use of chemicals and pesticides
• Safety and security
• Automation and navigation of ground vehicles
• Academic and extension education.
21
Monthly precipitation at Chikmagalur(mm)
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec2
00
4
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
0
200
400
600
800
1000
Figure 2: Source: http://www.imd.gov.in/section/
hydro/distrainfall/webrain/
karnataka/chikmagalur.txt
22
Average temperature at Chikmagalur (◦C)
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Jan
Feb
Mar
Apr
May Jun
Jul
Aug Se
pO
ctN
ov Dec
23
24
25
26
27
28
29
Figure 3: Chikmagalur averagetemperatures
23
Cloud cover at Chikmagalur
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Jan
Feb
Mar
Apr
May Jun
Jul
Aug Se
pO
ctN
ov Dec
10
20
30
40
50
60
70
80
Figure 4: Chikmagalur cloudcover
24
23.2◦C
29.5◦C
14.00%
84.39%
18.54hpa
29.25hpa
0.00mm
2167mm
0/day
0.738/d
3.55mm
5.4mm
Figure 5: Chikmagalur longterm data, 1901–2002, averagetemperature (Celcius), cloudcover (%), vapour pressure(hpa), precipitation (mm/day),ground frost frequency (perday) and reference crop evapo-transpiration (mm/day).
25
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
02
00
40
06
00
80
01
00
0
Monthly Precipitation at Chikmagalur
Month, 2004–2012
Prec
ipit
atio
n(m
m)
26
Monthly precipitation at Kodagu (mm)
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec2
00
4
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
0
200
400
600
800
1000
1200
1400
Figure 6: Source: http://www.imd.gov.in/section/
hydro/distrainfall/webrain/
karnataka/kodagu.txt
27
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
02
00
40
06
00
80
01
00
01
20
0
Monthly Precipitation at Kodagu
Month, 2004–2012
Prec
ipit
atio
n(m
m)
28
Monthly precipitation at Hassan (mm)
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec2
00
4
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
0
50
100
150
200
250
300
350
400
Figure 7: Source: http://www.imd.gov.in/section/
hydro/distrainfall/webrain/
karnataka/hassan.txt
29
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
01
00
20
03
00
40
0
Monthly Precipitation at Hassan
Month, 2004–2012
Prec
ipit
atio
n(m
m)
30