Sesame (Sesamum indicum L.) was studied for its distribution and diversity in India using DIVAGIS. Grid maps were generated for diversity analysis of the eight quantitative traits viz., plant height, inter-node length, leaves per plant, number of flowers per plant, number of capsules per plant, number of seeds per capsule, seed weight and seed yield. The results indicated that diverse accessions for all these traits can be sourced from Maharashtra, Gujarat and Madhya Pradesh (partly covering Chattisgarh) states and these states are diversity rich pockets for sesame germplasm in India.
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G Anuradha, S Sivaramakrishnan, Farzana, B Spandana, N Sivaraj, G John Prasanna R

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145IntroductionSesame (Sesamum indicum L.) family Pedaliaceae,is an important source of edible oil and iswidely used as one of the ingredients in foodproducts especially in bakery foods and animalfeed. Sesame germplasm has tremendousvariability. Efficient and systematic exploitationof this diversity is the key to any cropimprovement program. This, however, requiresas a first step, the assessment of geneticdiversity and population structure of the speciesunder consideration. DIVA-GIS, a GeographicInformation System (GIS) is designed to mapthe range of distribution of species in whichone is interested (Hijmans et al. 2000). GIS hasbeen successfully used in identifying areas ofrich diversity in various parts of the world.DIVA-GIS is a software tool for the analysis ofdiversity and it enables us to understand andcomprehend the distribution of diversity on thegeographical scale and also helps in identifyinggaps in collection.Materials and methodsThe experiment was carried out during lateKharif 2008–09. The experimental materials weresown in simple Randomised Block Design with60 × 10 cm spacing in three replications atCollege Farm, College of Agriculture, AcharyaN.G. Ranga Agricultural University,Rajendranagar, Hyderabad. RecommendedDiversity analysis of sesame germplasm using DIVA-GISB Spandana, N Sivaraj1, G John Prasanna Rao2, G Anuradha, S Sivaramakrishnan & FarzanaJabeen3Institute of Biotechnology (IBT),Acharya N.G. Ranga Agricultural University, Hyderabad-500 030, India.E-mail: spandanabandila@gmail.comReceived 07 December 2011; Revised 10 April 2012; Accepted 26 June 2012AbstractSesame (Sesamum indicum L.) was studied for its distribution and diversity in India using DIVA-GIS. Grid maps were generated for diversity analysis of the eight quantitative traits viz., plantheight, inter-node length, leaves per plant, number of flowers per plant, number of capsules perplant, number of seeds per capsule, seed weight and seed yield. The results indicated that diverseaccessions for all these traits can be sourced from Maharashtra, Gujarat and Madhya Pradesh(partly covering Chattisgarh) states and these states are diversity rich pockets for sesamegermplasm in India.Keywords: DIVA-GIS, germplasm, India, mapping, Sesamum indicum1National Bureau of Plant Genetic Resources (NBPGR), Hyderabad, India.2Directorate of Rice Research (DRR), Hyderabad-500 030, India.3Department of Genetics and Plant breeding (ANGRAU), Hyderabad-500 030, India.Journal of Spices and Aromatic CropsVol. 21 (2) : 145–150 (2012)         Indian Society for Spiceswww.indianspicesociety.in/josac/index.php/josac146 Spandana et al.agronomic practices and prophylactic measureswere adopted.Assessment of diversity in sesame germplasm andgeographical distribution using DIVA-GISCharacterization data recorded on the sixtyaccessions of sesame such as plant height,internode length, leaves plant-1, number offlowers plant-1, number of capsules plant-1,number of seeds capsule-1, seed yield and seedweight was subjected to DIVA-GIS analysis. Toknow the spatial distribution and assessmentof variability DIVA-GIS version 7.1.6, was used.Geographical coordinates of the collection sitesfrom various parts of India were also obtainedusing Garmin 12 Global Positioning System(GPS). India shape file was used for plottingthe georeferenced points using the layer menuon the software. Point- to- grid option using‘simple’ method on the “Analysis Menu” andthe output variables “Diversity and Statistics”were selected for getting the output files. Underdiversity, Shannon diversity index was pickedand for the statistics, coefficient of variation wasselected. Grid maps on the diversity, andcoefficient of variation were generated forvarious traits recorded on the sesamegermplasm.Shannon Diversity IndexDIVA-GIS can calculate a number of differentdiversity indices for each grid cell. Shannondiversity index was selected for diversity indexanalysis. The formula for the index taken isgiven below.Shannon H’ = –∑ pi ln pini – number of individuals in the i-th classpi – proportional abundance of the i th class =ni / NResults and discussionSesame germplasm (60 accessions) was collectedby National Bureau of Plant Genetic Resources,New Delhi was used for studying the variability.The germplasm accessions originated from eightIndian states covering Gujarat (8), HimachalPradesh (1), Madhya Pradesh (24), Nagaland(1), Punjab (92), Rajasthan (8) and UttarPradesh (3). The geographical coordinates ofthe sesame collection sites, accession identityand the plant traits used for DIVA-GIS analysisare provided in Table 1. The collection sites weremapped using DIVA-GIS (Fig.1).Fig 1. DIVA-GIS map showing geographicalorigin of sesame germplasm used in thestudyObservations on eight traits viz., plant height,internode length, leaves plant-1, number offlowers plant-1, number of capsules plant-1,number of seeds capsule-1, seed yield and seedweight were recorded. All quantitativecharacters exhibited variability evident by highCV observed in most of the traits studied. Thehigh CV observed among morphologicalcharacters is an indication of the level ofdiversity within the populations of sesamefound growing in these habitats. Moderatelylow CV values were observed for internodelength and for test seed weight.Diversity Analysis (Shannon diversity index)Grid maps were generated for diversity analysisof the eight quantitative traits (Fig. 2, 3 & 4)indicated that diverse accessions for all thesetraits can be sourced from Maharashtra,Gujarat and Madhya Pradesh (partly coveringChattisgarh) states of India. However, highlydiverse sesame germplasm accessions for leavesplant-1 was sourced from Maharashtra and147Sesame diversity analysisTable 1.Observations on the plant traits used as input in the DIVA-GIS to assess the geographical distribution of diversity in SesamegermplasmAcc IdStateLatitudeLongitudecapsules/PlantInternodeleaves/Flowers/SeedSeedSeeds/plantheightlengthPlantplantweightyieldcapsuleIC14163Gujarat21.667773.519555.425.23.2103.550.03.026.940.8IC43169Gujarat22.80473.618323.223.84.243.225.32.63.61259.4IC43171Gujarat22.902872.383128.021.03.639.635.62.93.6637.3IC43177Gujarat23.001774.013570.626.44.2105.671.02.34.528.2IC43179Gujarat23.594570.851647.824.63.568.238.62.924.7752.4IC43181Gujarat22.655871.592656.823.54.0125.457.02.98.4530.4IC43185Gujarat24.187470.406943.226.63.667.841.62.45.3677.0IC43217Gujarat23.742772.234938.223.63.255.239.22.65.253.0IC96079Himachal Pradesh31.795976.730929.014.32.660.329.32.64.9766.0IC14329Madhya Pradesh20.48281.078633.623.23.882.035.42.65.5563.6IC21705Madhya Pradesh21.618380.880936.026.84.060.037.22.84.1440.6IC23233Madhya Pradesh22.013583.252456.026.64.055.057.22.88.454.0IC23271Madhya Pradesh23.248782.610135.230.44.067.235.82.97.5974.4IC23321Madhya Pradesh20.80475.051141.831.64.074.642.62.85.345.8IC23325Madhya Pradesh25.71977.817846.027.34.068.846.82.94.735.8IC23327Madhya Pradesh24.088677.96652.330.64.011553.62.78.3333.5IC23332Madhya Pradesh23.594580.386919.525.53.548.520.02.852.7750.0IC23335Madhya Pradesh18.999881.473833.224.54.077.634.22.173.8453.4IC23341Madhya Pradesh23.001778.805940.524.23.965.741.42.795.84548.0IC23346Madhya Pradesh24.187480.04151.417.04.051.352.62.062.7526.0IC41932Madhya Pradesh22.952277.126139.427.64.0100.840.22.75.0647.6IC41948Madhya Pradesh22.3178.707117.215.83.850.817.82.62.147.0IC41953Madhya Pradesh21.815975.298130.420.53.872.631.22.72.733.0IC41962Madhya Pradesh22.55776.434455.225.24.0111.256.22.744.8231.9IC41964Madhya Pradesh20.432581.177439.022.54.0125.040.02.92.3455.0IC41966Madhya Pradesh18.802282.017331.021.64.053.231.62.623.743.4IC42200Madhya Pradesh20.48282.412551.423.33.687.852.22.68.0460.2IC52585Madhya Pradesh22.80481.325647.225.83.581.448.82.65.343.2Cont......148 Spandana et al.IC52586Madhya Pradesh23.989881.62242.015.34.268.444.62.66.7762.0IC52592Madhya Pradesh23.248778.361221.515.64.245.521.62.73.562.0IC52593Madhya Pradesh23.742783.4523.221.14.057.823.62.73.658.0IC52599Madhya Pradesh22.853479.843428.025.04.599.029.52.864.355.0IC52600Madhya Pradesh23.545181.720843.427.84.149.244.82.865.876.0IC16225Maharashtra19.889177.916637.022.73.863.837.82.643.747.2IC16236Maharashtra18.604576.681415.519.04.058.016.22.61.9639.7IC16238Maharashtra17.962375.545159.030.24.097.060.42.829.1855.6IC16243Maharashtra19.740976.829732.021.04.057.833.62.43.0347.2IC16248Maharashtra18.357575.495733.018.04.059.634.32.64.6854.6IC16249Maharashtra19.642180.386947.018.04.047.548.03.09.769.0IC16250Maharashtra20.72979.052948.027.04.058.048.72.99.9368.5IC41906Maharashtra20.48276.434467.619.04.079.268.22.67.1740.8IC41910Maharashtra18.703377.027342.225.44.058.643.22.746.759.0IC41911Maharashtra21.074878.756531.022.73.754.231.22.74.5154.0IC41912Maharashtra20.383176.582636.824.64.547.036.82.752.929.4IC41978Maharashtra17.715273.815956.323.84.086.057.32.76.9946.0IC751Maharashtra18.950473.618329.222.83.763.230.62.64.254.6IC20156Nagaland26.163694.418138.022.24.157.639.02.682.0853.4IC16832Punjab31.400675.495754.020.34.273.654.82.73.9143.2IC31379Punjab30.264375.693344.219.83.647.845.22.72.527.2IC14080Rajasthan27.052976.533228.321.84.044.328.72.54.8969.2IC14106Rajasthan26.015475.199349.825.43.865.050.62.94.7536.4IC14135Rajasthan24.236874.211254.629.64.472.655.22.584.743.5IC14155Rajasthan24.977974.062954.227.44.069.654.62.526.0744.8IC14174Rajasthan28.189374.55738.829.03.444.039.22.922.0951.0IC26303Rajasthan25.570872.48247.628.44.696.848.02.65.8947.6IC42965Rajasthan26.608374.952266.428.64.092.267.22.812.1965.6IC42987Rajasthan28.535175.446369.233.24.2151.470.82.911.859IC96098Uttar Pradesh26.064879.695241.422.43.469.642.42.622.370.8IC96109Uttar Pradesh27.448278.805941.424.24.486.242.42.934.0462.2IC96113Uttar Pradesh29.078678.460133.222.93.946.434.42.62.2845.6149and Madhya Pradesh are diversity rich pocketsfor sesame.Coefficient of variationHigh coefficient of variation for plant height(25.0–42.0%) was found in accessions fromMadhya Pradesh, followed by a moderate CV%range of 14.0–25.0% in Maharashtra. However,low CV% (up to 8.0%) was recorded on sesamegermplasm accessions from other states.Gujarat and Maharashtra recorded low tomoderate CV% for the quantitative trait of inter-node length, which indicated that diversity isless for this trait. Grids with high CV% for thetraits, number of leaves plant-1 (29.0–37.0%) andnumber of flowers plant-1 were stretched inMadhya Pradesh and Maharashtra. Germplasmaccessions augmented from Gujarat, MadhyaPradesh and Maharashtra recorded highestCV% (35.0–44.0%) for number of capsulesplant-1. Accessions with maximum CV (18.0–23.0%) recorded for seeds capsule-1 originatedfrom Maharashtra, while moderate CV valueof 9.0–18.0% was possessed by the germplasmaccessions from Madhya Pradesh. Grid mapgenerated for seed weight indicated a lowerCV% value (2.0–8.0%) for the accessions studied.This indicated less variability among theaccessions. However, maximum CV% valueFig 2. Diversity index for number of capsulesper plant in sesameFig 4. Diversity index for seed yield in sesameFig 3. Coefficient of variation (%) for numberof capsules per plantMadhya Pradesh only. The Shannon diversityindex ranged from 0.55–1.0 for germplasmaccessions sourced from Gujarat, MadhyaPradesh and Maharashtra states. Among thesesame germplasm sourced from eight Indianstates, and based on DIVA-GIS analysis it canbe concluded that Gujarat, Madhya PradeshSesame diversity analysis150(6.0–8.0%) was recorded for Madhya Pradeshcollections. The seed yield recorded the highestCV% (48.0–60.0%) among all the plant traitsstudied.The present study revealed that diversegermplasm accessions of sesame were dispersedall over the eight states (Gujarat, HimachalPradesh, Madhya Pradesh, Nagaland, Punjab,Rajasthan and Uttar Pradesh) but region wherethe diverse genotypes most likely to found areMaharashtra, Madhya Pradesh and Gujarat ashigh diversity indices and CV% were recordedfor all the traits studied. It may be concludedthat Maharashtra, Madhya Pradesh andGujarat states are most suitable for futuregermplasm collection missions. The presentstudy would be the first of its kind in India byintegrating DIVA-GIS for the study of diversityanalysis in sesame.GIS mapping may be effectively used fordocumentation, diversity analysis, identifyinggaps in collection, assessment of loss ofdiversity, developing new strategies forconservation, and sustainable utilization,particularly in the wake of recent internationaldevelopments related to food and nutritionalsecurity. 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Resour.Crop Evol. 56: 115–119.Utpala P. George J K, Saji K V, Srinivasan V,Madan M S, Prem Nath Mathur,Parthasarathy V A 2006 Spatial analy-sis for Piper species distribution inIndia. Pl. Genet. Resour. Newslet.147: 1–5.Varaprasad K S, Sivaraj N, Mohd Ismail &Pareek S K 2007 GIS mapping of selectedmedicinal plants diversity in the South-east Coastal Zone for effective collectionand conservation. In: Advances in Me-dicinal Plants (Eds. Janardhan Reddy K,Bir Bahadur, Bhadraiah B & Rao M L N).Universities Press (India) Private Ltd.pp.69–78.Varaprasad K S, Sivaraj N, Pandravada S R,Kamala V & Sunil N 2008  GIS mappingof Agrobiodiversity in Andhra Pradesh.Proceedings of Andhra Pradesh Acad-emy of Sciences. Special Issue on Plantwealth of Andhra Pradesh. pp 24–33.Spandana et al.

Diversity analysis of sesame germplasm using DIVA-GIS

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Diversity analysis of sesame germplasm using DIVA-GIS

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