Coffee cropmonitoring draft


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Coffee cropmonitoring draft

  1. 1. Coffee-crop monitoring using sensor networks in Karnataka Rahul Bhargava, 10th June 2014 Monitoring for precision agriculture involves the procurement and maintenance of sensing hardware, and software and processes for re- cording, collating and analysing data. A partnership for interpretation of data is anticipated and may result following consultations with plantation personnel and extension experts. Following settling on the hardware, support software and systems can be put together and this proposed sequence of decision mak- ing motivates the presentation of curated options below, hardware followed by software, to present possibilities before entering into consultations 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
  2. 2. Coffee crop monitoring Coffee is one of the most valuable primary commodities worldwide. Traditionally, the crop has been cultivated on small (<50 ha) farms where repeated hand picking is the standard harvesting procedure.1 1 Herwitz et al. Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support. doi:10.1016/j.compag.2004.02.006 The major coffee growing regions in India are the districts of Chikmagalur, Coorg, and Hassan in Karnataka, Wynad, Idduki and Nelliampathys in Kerala and Pulneys, Shevroys, Anamalais and Nilgiris in Tamil Nadu.2 2 upload/agns/pdf/coffee/Annex-E.2. pdf Agronomy and plant physiology Covers soil, land, water, shade and weed management for increasing the productivity of various coffee varieties under different agro- climatic conditions. • Soil management for soil and water conservation, including micro irrigation3. 3 htmls/ccri_agronomy.htm. Drip irriga- tion was found to be beneficial in the Cauvery by Chickmagalur Research Station. Four litres of water per day for around a hundred days during the dry period from November to May resulted in yield increases of up to 24 percent with a cost benefit ratio of [1:5]. How- ever, high initial investment, regular maintenance etc. makes it unsuitable for 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 ppm twice between August and September enhances 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 and curtailing biennial bearing in coffee. Harvesting and post-harvest Coffee blossoms do not appear and develop uniformly throughout a plantation. The resulting fruit thus tends to ripen at different times, with spatial and temporal trends that are difficult to track and predict (Wormer, 19646; Cannell, 19757) 6 Wormer, T.M., 1964. The growth of the coffee cherry. Annals of Botany 27, 47–55. Quoted below 7 Cannell, M.G.R., 1975. Crop physiolo- gical aspects of coffee bean yields: a review. Journal of Coffee Research 5, 7–20. Summarises existing information on coffee crop physiology emphas- ising whole-plant physiology and characteristics 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 follows which ends when the berry is about 17 weeks old. Thereafter, a small loss 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 when ripening begins, the fresh weight of the berry increases little while the dry weight increases regularly. In this period dry weight is laid down mainly in the beans which attain their final dry weight when the berry is still green. During ripening of the berry (which is in fact ripening of the pulp) the fresh weight of the beans drops slightly due to loss of water. Both fresh weight and dry weight of the pulp (including parchment) increase considerably during ripening by approximately 2
  3. 3. 121 per cent. and 106 per cent. respectively. Annals of Botany (1964) 28 (1): 47-55 Due to variations on individual trees as well as in different sections of a field, mechanical harvesting yields a mixture of un- ripe, ripe, and overripe fruit in varying proportions (Reddy and Srinivasan, 19798; Cannell, 1985). Ripe fruit has the highest value, fol- 8 Reddy, G.S.T., Srinivasan, C.S., 1979. Variability for flower production, fruit set and fruit drop in some varieties of Coffea arabica L. Journal of Coffee Research 9, 27–34. lowed by overripe and then unripe. To maximize value, crop ripeness stage is a main consideration of harvest managers (Watson, 19809; 9 Watson, A.G., 1980. The mechanisation of coffee production. In: Proceedings of the Ninth International Coffee Research Conference, London, pp. 681–686. Willson, 199910). Managers typically rely on repeated manual cherry 10 Willson, K.C., 1999. Coffee, Cocoa and Tea. Crop Production Science in Horticulture Series No. 8, CABI Publishing, Oxford, UK. counts made by field scouts and taken on a few sample branches within each field. Without removing the fruit, the scouts visually sort cherries on each branch by ripeness category to estimate field-level percentages. • Post harvest practices, development and evaluation of machinery and production of value added products from coffee waste. • Pesticide, residues, and microbial / mycotoxin contamination in coffee. • Water pollution emanating from wet processing of coffee. Weed management Another important and costly aspect of coffee production and harvest is 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-rowalleys generally difficult to negotiate, field interiors are not readily viewed or mapped from the ground. Large weeds in the form of grasses and vines can significantly slow the harvesting process, and thus adversely 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 of generations without leaving the plant, unlike those on annual crops where the pest must move elsewhere after the plant dies. Others may be permanently associated with coffee and have a narrow host range, but their populations increase to damaging levels under certain favourable conditions, e.g. antestia and the Lyonetiid moths (Leucoptera spp.). Those that feed upon the berries, such as the berry borer (Hypothenemus hampei), may be more easily controlled in areas with a defined flowering period rather than in those that 3
  4. 4. experience intermittent rainfall throughout the year, with continuous availability of berries. Insect pests rarely kill the tree, but those that do, such as stem borers, may have a permanent effect on the plantation, as it can be difficult to re-establish bearing trees in the gap left by a dead tree. Leaf retention is essential for maximization of coffee yields, and lowlevel but continuous loss of leaves due to leaf-feeding insect pests and Homoptera – which literally drain the plant of nutrients – can contribute to physiological dieback if they are not controlled.11 11 Waller, J. M.; Bigger, M.; Hillocks, R. J.. Coffee Pests, Diseases and Their Management. Wallingford, Oxon, GBR: CABI Publishing, 2007. p 36. Chikmagalur has a Plant Pathology Division at the Central Coffee Research Institute, Coffee Research Station, that concentrates on management of diseases through cultural, chemical and biological methods12. Periodic surveys of plantations are undertaken, for 12 htmls/ccri_plant_path.htm advisories on possible disease outbreaks, prior to making disease control recommendations, and training growers, plantation managers and extension personnel. Current programs address integrated disease management of coffee leaf rust disease13, updating disease control recommendations 13 Plantvax 20 EC and Bayleton 25 EC are being recommended against leaf rust disease. An alkaline Bordeaux mix- ture for spraying is being recommended for 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 substantial quantities of nutrients lost to harvest. Motivation for monitoring “India cultivates all of its coffee under a well-defined two-tier mixed shade canopy, comprising evergreen leguminous trees. Nearly 50 different types of shade trees are found in coffee plantations. Shade trees prevent soil erosion on a sloping terrain; they enrich the soil by recycling nutrients from deeper layers, protect the coffee plant from seasonal fluctuations in temperature, and play host to diverse flora and fauna.14 14 coffee-regions-india.html “Coffee plantations in India are essential spice worlds too: a wide variety of spices and fruit crops like pepper, cardamom, vanilla, orange and banana grow alongside coffee plants.” 1. Integrated pest management is preferred, using techniques such as targeted treatment of pest outbreaks, and managing crop en- vironment away from conditions favouring pests, to spraying of insecticides which has often proven to be counter-productive, as the predators of the pests are more sensitive than the pests themselves. 4
  5. 5. Factors Arabica Robusta Soils Deep, fertile, rich in organic matter, well drained and slightly acidic (pH 6.0–6.5) Same as Arabica Slopes Gentle to moderate slopes Gentle slopes to fairly level fields Elevation 1000–1500m 500–1000m Aspect North, East and North– East aspects Same as Arabica Temperature 15◦C–25◦ C ; cool, equable 20◦C–30◦ C; hot, humid Relative humidity 70–80% 80–90% Annual rainfall 1600–2500 mm 1000–2000 mm Blossom showers March– April (25–40mm) February –March (25–40 mm) Backing showers 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 with planning surface runoff. For successful production, a free draining soil with a minimum depth of 3 feet (1 m) is required. Coffee will not tolerate water-logging or ‘wet feet’.15 15 ae938e/ae938e03.htm 3. Testing pH is particularly important for coffee. A pH of 5 or 6 is ideal, lower pH affects yield. Dolomite, Calcium Magnesium Carbonate, 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 predation overall. For reference, ideal conditions are highlighted for Arabica, from the literature. Arabica coffee prefers a cool temperature with an optimum daily temperature of 68◦ to 75◦F (20◦ to 24◦C). Temperatures greater than 86◦F (30◦C) cause plant stress leading to a cessation of photosynthesis. Mean temperatures of less than 59◦F (15◦C), limit plant growth and are considered suboptimal. As Arabica coffee is susceptible to frost damage, use of shade trees will 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
  6. 6. is preferable. Steeper slopes present a major erosion risk and re- quire terracing or special management such as contour furrows or preferably grass strips. A slight slope will improve air drainage and reduce damage from frost. Do not plant coffee at the bottom of 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 bottom third of a slope as it will be colder and sometimes waterlogged. 7. Coffee requires adequate water during the growing and cropping period, however it also requires a dry stress period followed by sufficient rain or irrigation to promote uniform flowering and a good fruit set. Many plantings suffer from moisture stress at the time of year when they need adequate water for growth and cropping. Unless regular rain is received, young newly planted trees should be irrigated (or hand watered at least twice a week if irrigation is not available) to ensure establishment. Locating coffee plantings near a water supply for possible irrigation as well as for processing of cherry is desirable. Water requirements can be reduced by use of suitable, well-established shade trees and mulch. 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 and CHemical industry gically similar growth stages of all mono- and dicotyledonous plant species. Phenological development stages of plants to play important role in agricultural planning research (eg phytopathology and plant breeding), so but in applied botanical sciences. They are used in the agricultural industry (eg agricultural met- eorology, timing of fertilization or pesticide application, agricultural insurance)18. 18 startseite/veroeffentlichungen/ bbch-codes.html 6
  7. 7. 00 05 09 10 20 19/33 21/90 23/93 25/94 29/97 DryCseed SeedCradical protrusion andChooking Emergence Cotyledons unfolded FirstCpairCofC primaryCbranchesC visible 9CorCmoreCleafCpairs unfolded/Branch elongation,C30Cnodes presentCinCbranches
  8. 8. 51 59 71 79 77 60 57Inflorescenceybudsyswellingyinyleafyaxils Closedyflowersyvisible Elongatedyclosedypetals Firstyfloweryopen Berryygrowthybeginning Fruitsyareydarkygreen Fruitymature
  9. 9. 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 skin removed. Cutting (orthotropic, mononodal, 60 mm long, two half trimmed leaves). Stump with bulky nodes and no buds visible 1 Beginning of seed imbibition, bean swollen, whitish, no radicle visible. Cutting planted in rooting media, no shoots visible, no callus visible 2 Seed imbibition complete, bean whitish, small swelling vis- ible at one end of bean where the embryo is located. Callus formation begins on cuttings. Bud burst start on stumps 5 Seed radicle protrusion and hooking. Shoot and root formation on the cuttings. Green, rounded buds visible on the stumps 6 Elongation of radicle, formation of root hairs and lateral roots on 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. The cuttings present roots 6-7 cm. long and shoots with 1-2 nodes. Stumps show sprouts with first leaf initials. 1: Leaf development on main shoot of the young plant, and branches of the coffee tree 10 Cotyledons completely unfolded. First pair of true leaves separ- ating on shoot or first pair of true leaves separating on branch of the coffee tree 11 first leaf pair unfolded, not yet at full size. Leaves are light green or bronze 12 2 leaf pairs unfolded, not yet at full size. Leaves are light green or bronze 13 3 leaf pairs unfolded, not yet full size. The third leaf pair from apex is dark green 14 4 leaf pairs unfolded. The fourth leaf pair from apex is dark green 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 the field) 20 First pair of primary branches are visible 21 10 pair of primary branches visible 22 20 pair of primary branches visible 23 30 pair of primary branches visible 2{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
  10. 10. 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: Inflorescence emergence 51 Inflorescence buds swelling in leaf axils 53 Inflorescence buds burst and covered by brown mucilage; no flowers visible 57 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 open 61 10% of flowers open 63 30% of flowers open 65 50% of flowers open 67 70% of flowers open 69 90% of flowers open 7: Development of fruit 70 Fruits visible as small yellowish berries 71 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% of final size. 8: Ripening of fruit and seed 81 Beginning of change of fruit coloration from pale green to yellow 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
  11. 11. Table 3 – continued Growth stage Code Description 9: Senescence 90 Shoots have completed their development; the plant appears of an intense dark green color, leaves are of normal size and harvest locates at the bottom part of the plant. 93 Older leaves change its color from deep green to yellow with red spots, and fall specially at harvesting time. 94 The foliage changes to a pale green color. Defoliation is observed on the bottom part of the main stem and lower branches. 97 The production zone has moved towards the upper parts in the main shoot and outer parts of branches, leaves are of smaller size than normal, strong defoliation is observed on the bottom and inner part of the plant, some dead branches are observed at the bottom. 98 The production zone is limited to a very few branches on the top of the shoot and a very few nodes on the tip of these branches, and the plant is heavily defoliated. A high-degree of senescence has been reached. 90% or more of the harvest completed. 99 Post harvest or storage treatments Table 3: BBCH-scale, coffee., J Arcila-Pulgarín et 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 wiki/Main_Page server (SUMO)20 uses industry standard sensors for temperature, 20 wiki/SUMO air pressure, humidity and wind speed/direction as well as more specialized sensors as infrared/visible light radiation, particle concentration or ionizing radiation. (a) Ground station. Laptop, a bi-directional modem, a standard RC transmitter and battery chargers (b) Ground modem. 2.4GHz Digi XBee Series 121 21 Communication options, semiconductors-and-actives/ communication?page=2 2. Ardupilot UAV platform for controlling autonomous multicopters, fixed-wing aircraft, traditional helicopters and ground rovers. 11
  12. 12. Stage Description 0 Germination / sprouting / bud development 1 Leaf development (main shoot) 2 Formation of side shoots / tillering 3 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) / heading 6 Flowering (main shoot) 7 Development of fruit 8 Ripening or maturity of fruit and seed 9 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 Scheme FruitRipening Senescence Germ sprouting Leaves Inflorescen ce Flowering Side shoots Rosettes Plantparts Figure 1: Subdivision of the developmental cycle of coffee plants 3. Flying capabilities. Flight controllers compared22 22 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 flight control boards. Self Leveling Ability to let go of the pitch and roll stick on the transmitter and have the copter stay level. Care Free The pilot can control the copter as if it is pointing in its original direction as the orientation of the copter changes. Altitude Hold Ability to hover a certain distance from the ground without having to manually adjust the throttle. Position Hold Ability to hover at a specific location. Return Home Ability to automatically return to the point where the copter initially took off. 12
  13. 13. Waypoint Navigation Ability to set specific points on a map that copter will follow as part of a flight plan. Board Opensource Gyrostabilised Selfleveling Carefree Altitudehold Positionhold Returnhome Waypointnavigation ArduCopter APM 2.5 AutoQuad Hobbyking KK2.1.5 MultiWii Pro 2.0 w/GPS Pixhawk 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 Observation_Applications_ Agriculture_Tea_Management.html Research Organisation. “A pilot study was carried out in Bagdogra area of North Bengal to address the Remote Sensing and GIS (Geographic Information System) capability in tea area development using multispectral and multi-resolution satellite data supported by ground intelligence to address 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 area development 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, an Research and Development component [is part of the] project, apart from operations and capacity building, [involving]. • remote estimation of green leaf yield, 13
  14. 14. • forecasting of some pests and diseases, • surface hydrology and drainage planning Objectives Major objectives include, • Mapping of tea growing areas (major, medium and small) using high-resolution Indian satellite data. • Analysis of detailed tea garden land-use and mapping. • Geo-referencing of tea garden maps with respect to satellite data and creation of spatial garden database. • Analysis of canopy density of the shade trees using Cartosat-1 satellite data and mapping to characterize optimal, high or low density classes. • Identification of degraded tea areas for uprooting and re-plantation. • Generation of fine quality Digital Elevation Model (DEM) using Cartosat-1 satellite stereo pair. • Use of Cartosat-1 DEM for generation of potential surface water flow 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 and infrastructure of Tea gardens. • Development of comprehensive web-enabled GIS and MIS for the Tea gardens to establish network between Tea Board, Tea Research Institutes and Tea Gardens for better management and also to provide technical support to Tea gardens. Outputs • Geographically referenced hard- and soft-copy digital maps (in cadastral scale24) of all the tea gardens at section- [level resolution] 24 (of a map or survey) shows the extent, value, and ownership of land, especially for taxation. including small growers, most of [whom] are unregistered [with the] tea board. • Updated information on garden land-use, shade tree density, gap areas, garden areas affected by river bank erosion, changes in the river course. 14
  15. 15. • Availability of section-, division-, garden-level detail including static and dynamic attribute information on the desktop for aug- menting informed decision making. • Near real time acquisition of information across different tea gardens through web enabled data sharing. Outcomes • Monitoring uprooting and re-plantation especially in the low yielding 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 financial institutions. • News flash pertaining to different stakeholders through tea board portal. • Long term policy formulation Year Arabica Robusta Total 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 in tonnes, Coffee Board of India Karnataka Planters’ Association Precipitation in Karnataka districts of interest Chikmagalur Placeholder IMD Raingauge Station List Kottigehar 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
  16. 16. Traditional coffee-growing areas Non-traditional growing areas North East region Assam Nagaland Arunachal Pradesh Meghalaya Manipur Tripura Mizoram Andhra Pradesh Orissa Karnataka Tamil Nadu Kerala 16
  17. 17. Hassan Chikmagalur Kodagu 17
  18. 18. Post-monsoon estimate ‘13–‘14 Final estimate ‘12–‘13 State/District Arabica Robusta Total Arabica Robusta Total Karnataka Chikmagalur 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 Kerala Wayanad 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 Nadu Pulneys 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 Areas Andhra 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 in major states/districts of India (in MT), Coffee Board of India 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 List Kurchy/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
  19. 19. 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 India 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 India coffee-statistics.html Hassan IMD Rainguage Station List Maranahalli 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
  20. 20. 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 on the one hand from the soil surface by evaporation and on the other hand from the crop by transpiration is referred to as evapotranspira- tion (ET). Evaporation is the process whereby liquid water is converted to water vapour (vaporization) and removed from the evaporat- ing surface (vapour removal). Water evaporates from a variety of surfaces, such as lakes, rivers, pavements, soils and wet vegeta- tion. Leaf Area Index Leaf area index (LAI) is the total one-sided area of leaf tissue per unit ground surface area. It is a key parameter in ecophysiology, espe- cially for scaling up the gas exchange from leaf to canopy level. It charac- terizes the canopyatmosphere interface, where most of the en- ergy fluxes exchange. It is also one of the most difÆcult to quantify properly, owing to large spatial and temporal variability. Many meth- ods have been developed to quantify LAI from the ground and some of them are also suitable for describing other structural parameters of the canopy. UAVs can be used by growers of different commodities, regardless of their crop size and type. Potential applications of this technology in 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 20
  21. 21. • 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
  22. 22. Monthly precipitation at Chikmagalur(mm) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2004 2005 2006 2007 2008 2009 2010 2011 2012 0 200 400 600 800 1000 Figure 2: Source: http: // hydro/distrainfall/webrain/ karnataka/chikmagalur.txt 22
  23. 23. 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 Sep Oct Nov Dec 23 24 25 26 27 28 29 Figure 3: Chikmagalur average temperatures 23
  24. 24. 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 Sep Oct Nov Dec 10 20 30 40 50 60 70 80 Figure 4: Chikmagalur cloud cover 24
  25. 25. 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 long term data, 1901–2002, average temperature (Celcius), cloud cover (%), vapour pressure (hpa), precipitation (mm/day), ground frost frequency (per day) and reference crop evapo- transpiration (mm/day). 25
  26. 26. Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 02004006008001000 Monthly Precipitation at Chikmagalur Month, 2004–2012 Precipitation(mm) 26
  27. 27. Monthly precipitation at Kodagu (mm) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2004 2005 2006 2007 2008 2009 2010 2011 2012 0 200 400 600 800 1000 1200 1400 Figure 6: Source: http: // hydro/distrainfall/webrain/ karnataka/kodagu.txt 27
  28. 28. Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 020040060080010001200 Monthly Precipitation at Kodagu Month, 2004–2012 Precipitation(mm) 28
  29. 29. Monthly precipitation at Hassan (mm) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2004 2005 2006 2007 2008 2009 2010 2011 2012 0 50 100 150 200 250 300 350 400 Figure 7: Source: http: // hydro/distrainfall/webrain/ karnataka/hassan.txt 29
  30. 30. Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0100200300400 Monthly Precipitation at Hassan Month, 2004–2012 Precipitation(mm) 30