Agro-ecological Zones Of India Research Articles

Genetic diversity analysis and heterotic grouping of Indian white maize inbred lines using combining ability and SNP markers

AbstractMaize (Zea mays L.) is a versatile crop with high genetic yield potential and various uses. While yellow maize is primarily used for animal feed, white maize is preferred as a food by rural and tribal populations in India. However, white maize landraces suffer immensely in terms of low yield. Heterotic grouping is an excellent method to develop hybrids with increased yield potential in maize. The heterotic grouping of 78 white maize inbred lines was performed using combining ability and molecular diversity analysis. The lines were crossed with two testers, and the resulting hybrids were evaluated for grain yield at three locations representing different agroecological zones in India. The combining ability analysis based on specific combining ability effects on mean grain yield was used to classify the inbred lines into heterotic groups (HG‐A: 18 inbreds; HG‐B: 33 inbreds). Additionally, marker‐based clustering using 62,470 single nucleotide polymorphisms (SNPs) generated through genotyping by sequencing was also employed to determine the genetic relationships among these lines. The combining ability information was superimposed on marker‐based clustering data to obtain the heterotic grouping information, and two distinct HGs with 7 (HG‐1) and 18 inbred lines (HG‐2) were developed. The results of this study will contribute to the development of high‐performing white maize hybrids through the efficient utilization of clear‐cut and well‐defined HGs. Hence, the use of SNP markers along with the combining ability of inbred lines is a useful method for heterotic grouping and understanding of genetic relationships of white maize.

Exploring the genetic diversity ofAegle marmelos(L.) Correa populations in India

AbstractBael is an important sub-tropical fruit crop in family Rutaceae that is widely distributed throughout South-East Asia. For local communities, the nutritious composition of its fruits and leaves offers tremendous economic and social possibilities to exploit. However, its underutilized status, as well as man-made threats to its natural habitat, make it imperative to implement concrete strategies for its cultivation and conservation. To fully grasp the ability of this adaptable fruit tree for human health and environmental well-being, it is necessary to characterize the genetic diversity. The goal of this study was to use morphological (13 quantitative traits), biochemical (9 attributes) and molecular (10 SRAP primers) characterization to evaluate 24 bael genotypes from two agroecological zones of India. Fruit and pulp weight ranged from 79.0– to 1478.8 g and 15.0– to 894.3 g with mean values of 448.67 and 233.3 g, respectively. Traits such as fruit, pulp, and seed weight (g), fruit length (cm) and width (cm), number of fruits per tree, number of seeds per fruit, shell weight (g) and shell thickness (mm) recorded highly significant differences. High phenol (11.65–24.38 mg GAE/g fw) and flavonoid (12.32–74.63 mg CE/g fw) content was observed in fruit pulp indicating significant antioxidant potential of this fruit. Several morphological and biochemical characters were found to have significant positive correlations. Principal component analysis revealed that first five components contributed 96.76% to total variation. Hierarchical cluster analysis separated the populations into two distinct clusters, while analysis of molecular variance (AMOVA) using SRAP markers revealed that 70% of the total marker variation was due to interpopulation variance, while 30% was attributed to intrapopulation.

Molecular Fingerprinting and Phytochemical Investigation of Syzygium cumini L. from Different Agro-Ecological Zones of India

Syzygium cumini L. (ver Jamun; BlackBerry) is a native, evergreen multipurpose tree species of India. Besides being a fruit tree and for agroforestry in different regions, it is medicinally important too. This study aimed to determine genetic diversity using molecular and phytochemical markers in sixteen genotypes of Indian S. cumini from different agro-ecological zones. The present study used a combination of ISSR markers and the HPLC technique to explore these genotypes. The results showed a wide genetic diversity range based on the similarity coefficient values observed in S. cumini sixteen accessions from different sites. Four primary phenolic acids were discovered in all the accessions; caffeic acid (CA) was found in high concentrations. The intraspecific association between molecular and phytochemical characteristics was the primary goal of this investigation. By employing gene-specific markers for the route of secondary metabolites (polyphenols) production, it further investigated the progressive research of diversity analysis of polyphenol content in S. cumini accessions, which may also expand its nutraceutical and pharmaceutical utilization.

Analysing the SPAD dynamics of water-stressed vs. well-watered sesame (Sesamum indicum L.) accessions and establishing their relationship with seed yield.

The chlorophyll content is susceptible to deficit moisture stress and may affect the plant yield. Leaf chlorophyll content is directly related to tolerance and higher productivity under deficit moisture stress (WS). The SPAD meter is an excellent tool for rapid analysis of crop chlorophyll content. Therefore, establishing a relationship between leaf chlorophyll content and seed yield is crucial in sesame, particularly under deficit moisture stress. Seeds of 37 sesame genotypes with checks were used in this study. These genotypes were mostly landraces, adapted to different agro-ecological zones in India. The selected genotypes were evaluated under well water (WW) and deficit moisture stress (WS) conditions. The SPAD readings were recorded ten (10) times each at every seven days intervals from the juvenile/first bud (30-35 days after sowing) to ripening/ physiological maturity (95-100 days after sowing) stage. This study aimed to identify the association between leaf SPAD readings (recorded at 7-days interval) and seed yield of sesame genotypes. The analysis of variance revealed the presence of significant variation in SPAD readings due to treatment (WW and WS), genotypes, and their interaction effects. The SPAD readings at all stages were positively correlated with seed yield in both WW and WS. High values of correlation coefficients were observed at 52 (r: 0.672) and 59 (r: 0.655) DAS under WS; whereas at 59 (r: 0.960), 66 (r: 0.972) and 73 (r: 0.974) DAS under WW at one percent significance level (p<0.01), which coincided with the mid-bloom stage of the sesame crop. The best-fit multiple regression model revealed that the dependence of sesame seed yield is significantly influenced by SPAD reading at 52 DAS under WS and 59 to 73 DAS under WW. Both these models provide a good fit with the chi-squared test, which compares the predicted and observed yield.

Agroforestry Suitability for Planning Site-Specific Interventions Using Machine Learning Approaches

Agroforestry in the form of intercropping, boundary plantation, and home garden are parts of traditional land management systems in India. Systematic implementation of agroforestry may help achieve various ecosystem benefits, such as reducing soil erosion, maintaining biodiversity and microclimates, mitigating climate change, and providing food fodder and livelihood. The current study collected ground data for agroforestry patches in the Belpada block, Bolangir district, Odisha state, India. The agroforestry site-suitability analysis employed 15 variables on climate, soil, topography, and proximity, wherein the land use land cover (LULC) map was referred to prescribe the appropriate interventions. The random forest (RF) machine learning model was applied to estimate the relative weight of the determinant variables. The results indicated high accuracy (average suitability &gt;0.87 as indicated by the validation data) and highlighted the dominant influence of the socioeconomic variables compared to soil and climate variables. The results show that &gt;90% of the agricultural land in the study area is suitable for various agroforestry interventions, such as bund plantation and intercropping, based on the cropping intensity. The settlement and wastelands were found to be ideal for home gardens and bamboo block plantations, respectively. The spatially explicit data on agroforestry suitability may provide a baseline map and help the managers and planners. Moreover, the adopted approach can be hosted in cloud-based platforms and applied in the different agro-ecological zones of India, employing the local ground data on various agroforestry interventions. The regional and national scale agroforestry suitability and appropriate interventions map would help the agriculture managers to implement and develop policies.

Morphological and nutritional diversity among accessions of marvel grass (Dichanthium annulatum(Forssk.) Stapf) and development of a core collection

AbstractDichanthium annulatumis one of the dominant grasses of India, North Africa, Southeast Asia, China, Australia, Fiji, New Guinea, Cuba, Haiti and Puerto Rico. This drought-tolerant grass is an excellent fodder in mixed pastures. Developing varieties with improved quality and tolerance to various abiotic stresses is hampered due to its apomictic nature. Germplasm collection, characterization, genetic diversity analysis and core subset development followed by selection for desirable traits seems to be the most plausible breeding tool for developing new cultivars. In the present study, 498 genotypes collected from different agro-ecological zones in India were included. Genotypes were characterized for various metric and non-numeric traits; and the nutritional parameters. Agglomerative clustering analysis, using the Euclidean distance method, showed 14 distinct clusters. High variability was recorded for green forage yield, quantitative traits and nutritive quality parameters. A core subset of 50 accessions was identified, which captured most of the morphological and nutritional variability present in the total germplasm. Clustering of genotypes was observed to be related to the climatic conditions of the place of collection. High genetic variability observed for various morphological traits as well as forage yield indicated that these genotypes or subset of genotypes can be evaluated in different abiotic stress conditions such as salt, light and moisture stress for the identification of suitable varieties for the respective areas. Variability was attributed to inter-generic, inter-specific crossing together with the occasional presence of sexual plants in nature.

Genetic diversity and population structure of &lt;i&gt;Heteropogon contortus&lt;/i&gt; L. germplasm collected from diverse agro-climatic regions in India and development of a core germplasm set

Heteropogon contortus, an important constituent of major grasslands of India, Australia and many countries in Africa, Asia and the Americas, is important for pasture and grassland productivity. Hence genetic improvement of the grass needs attention. A genetic variability study, including development of a core subset, was carried out by evaluating 235 accessions collected from different agro-ecological zones of India. The study, based on 16 metric and 14 non-metric traits along with 8 nutritional parameters, indicated that considerable genetic variability existed among the germplasm and selection could result in identification of suitable types for target environments. Clustering and subclustering was performed to select 35 accessions to form a core subset. The statistical analysis indicated that the core subset captured almost all the variability present in the entire germplasm. The study will help researchers to focus future studies on this core subset in developing genetic improvement programs.

Efficacy of machine learning techniques in predicting groundwater fluctuations in agro-ecological zones of India

In the 21st century, groundwater depletion is posing a serious threat to humanity throughout the world, particularly in developing nations. India being the largest consumer of groundwater in the world, dwindling groundwater storage has emerged as a serious concern in recent years. Consequently, the judicious and efficient management of vital groundwater resources is one of the grand challenges in India. Groundwater modeling is a promising tool to develop sustainable management strategies for the efficient utilization of this treasured resource. This study demonstrates a pragmatic framework for predicting seasonal groundwater levels at a large scale using real-world data. Three relatively powerful Machine Learning (ML) techniques viz., ANFIS (Adaptive Neuro-Fuzzy Inference System), Deep Neural Network (DNN) and Support Vector Machine (SVM) were employed for predicting seasonal groundwater levels at the country scale using in situ groundwater-level and pertinent meteorological data of 1996–2016. ANFIS, DNN and SVM models were developed for 18 Agro-Ecological Zones (AEZs) of India and their efficacy was evaluated using suitable statistical and graphical indicators. The findings of this study revealed that the DNN model is the most proficient in predicting seasonal groundwater levels in most AEZs, followed by the ANFIS model. However, the prediction ability of the three models is ‘moderate’ to ‘very poor’ in 3 AEZs [‘Western Plain and Kutch Peninsula’ in Western India, and ‘Deccan Plateau (Arid)’ and ‘Eastern Ghats and Deccan Plateau’ in Southern India]. It is recommended that groundwater-monitoring network and data acquisition systems be strengthened in India in order to ensure efficient use of modeling techniques for the sustainable management of groundwater resources.

Diversity study among Guinea grass (Megathyrsus maximusJacq.) (Poales: Poaceae) genotypes and development of a core germplasm set

AbstractGuinea grass (Megathyrsus maximusJacq.) is an important forage species in vast rangelands/grasslands of India and several tropical countries owing to its high biomass yield, good nutritional quality and wide adaptation. Evaluation of the existing natural variation and selection of desirable genotypes is the most plausible breeding method for this apomictic and polyploid grass. Developing a core sub-set to narrow down the number of germplasm required for future genetic studies is also pertinent. The present study involved characterization of 152 diverseM. maximusgermplasm representing collections from different agro-ecological zones of India as well as those procured from Africa and Brazil; and development of a core sub-set. Nineteen metric, seven non-metric and nine nutritive traits together established the presence of wide variability among the genotypes. Clustering of the genotypes resulted in eight distinct clusters. The largest cluster included genotypes from Ethiopia, north India, north-western India, south India and north-eastern hill region, thus represented the highest diversity. Eleven of the total 26 Ethiopian genotypes clustered together. Non-metric morphological traits effectively differentiated the genotypes, and were associated with nutritional quality also. Genotypes which flowered once in a year showed slightly better crude protein and digestibility. The clusters were further sub-clustered and representatives were selected to develop the core sub-set of 23 genotypes comprising 20 indigenous and three exotic accessions. Comparison of the range of diversity and mean value for traits as obtained in the core sub-set and that in the total germplasm indicated successful capturing of maximum diversity in the core sub-set.

Microsatellite and mitochondrial DNA analyses unveil the genetic structure of native sheep breeds from three major agro-ecological regions of India

Sheep farming has been fundamental to many civilizations in the world and is practiced in India since antiquity. Several thousand years of adaptation to local environmental conditions and selective breeding have evolved 44 sheep breeds in India. They are paramount in terms of economic, scientific, and cultural heritage. Genetic characterization information is imperative for sustainable utilization and conservation of ovine heritage. In this study, the genetic diversity, differentiation, and structure of 11 indigenous sheep breeds from three different agro-ecological zones of India were explored with genomic microsatellite loci and mitochondrial DNA (D loop). The estimated diversity parameters indicated that populations retained high levels of genetic diversity (Na = 8.27 ± 0.17; Ho = 0.65 ± 0.01), which provides an optimistic viewpoint for their survival. However, significant inbreeding was also observed in the nine populations. Moderate genetic differentiation existed among the groups (FST = 0.129 ± 0.012), and most likely clusters existing in the dataset are seven. Phylogenetic clustering was in line with the geographical locations of sheep populations. Mitochondrial sequences revealed high haplotype diversity with the existence of maternal haplogroups A, B, and C, and signals of population expansion. Decreased genetic diversity and unique maternal lineage (C) in endangered Tibetan and Bonpala sheep breed, warrant their immediate scientific management. Overall, the quantitative data reported here on the extant variability, and genetic relationships among the Indian sheep breeds, provide critically important inputs that will be valuable for the decision-making process on their management, both for the conservation of endangered breeds, and formulation of breeding programs to check genetic erosion.

Stability Analyses using Regression and AMMI Models for Seed Yield in Blackgram

Background: Blackgram is an important pulse crop grown in almost all agro ecological zones in India. One of the major limitations of pulse cultivation in India is lack of superior genotypes with better adaptation to local conditions. Hence developing high yielding stable blackgram genotypes becomes a necessity to improve the area and production across the country. With this background, the present study was undertaken to identify stable and superior performing blackgram genotypes over seasons. Methods: The experiment was carried out during kharif 2017, rabi 2017-18, kharif 2018 and rabi 2018-19 at National Pulse Research Centre, Vamban. A total of 21 genotypes were evaluated in randomized block design with two replications in each environment. The data on seed yield was subjected to statistical analysis. The G X E interaction was studied as per Eberhart and Russell model, AMMI model and GGE biplot analyses. Result: In Eberhart and Russell model, the checks VBN 6, VBN 8 and VBN 10 and genotypes VBG 17-019, VBG 17-023 and VBG 17-026 were considered as stable with average response to the environments. In biplot 1 of AMMI analysis, check VBN 8 and genotypes VBG 16-005 and VBG 17-023 were considered as stable with high mean seed yield and less interaction with environment. In biplot 2 of AMMI analysis VBG 16-005 and VBG 007 were less interactive genotypes. GGE biplots indicated that rabi seasons are more informative than kharif seasons to assess the stability of genotypes. This model identified VBG 17-007, VBG 17-024 and VBG 17-030 as ideal genotype with high mean seed yield and stability. It also identified VBG 17-023 as with high mean seed yield and moderate interaction with environment. Based on the results of all models, the genotype VBG 17-023 was considered as stable genotype with high mean seed yield. Hence, the genotype VBG 17-023 can be tested in larger environments to release for general cultivation.

Morphological characterization and genetic identity of crop wild relatives of rice (Oryza sativa L.) collected from different ecological niches of India

Crop wild relatives of rice (Oryza sativa L.) are an important reservoir of genes for broadening the genetic base of commercial varieties. India is the centre of genetic diversity of some of the wild as-well-as the cultivated rice species. In order to collect genetic diversity, explorations were undertaken in six states located in different agro-ecological zones of India. Forty-four accessions belonging to four wild species (Oryza rufipogon Griff., Oryza nivara Sharma et Shastry, Oryza officinalis Wall. ex Watt and Oryza sativa L. f. spontanea Roshev.) including two accessions of cultivated rice (Oryza sativa L. subsp. indica Kato) were collected from different ecological niches. The rice accessions were characterized using 28 morphological descriptors, which included 15 qualitative and 13 quantitative traits. Wild rice accessions displayed a broad range of phenotypic variation for plant height, main heading days, days to 50% flowering, flag-leaf length and width, panicle shape and size, peduncle length, awning pattern, awn length and colour, seed length and width, seed length/width ratio and 100-seed weight. Cluster analysis based on Jaccard’s similarity coefficients derived from 28 morphological traits grouped 44 accessions into three clades. DNA sequencing revealed that internal transcribed spacer (ITS) region of 18S–5.8S–28S nuclear ribosomal cistron varied from 574 to 577 bp with mean of 576.1 bp in AA-genome species. GC content was high in ITS region, which varied from 69.57 to 70.36% with mean value of 69.99%. Neighbour-joining phylogenetic tree distinguished Oryza sativa–nivara–rufipogon complex from other species of AA-genome. The wild germplasm characterized in this study could be utilized in the genetic enhancement of cultivated rice.

Climate adaptive crop-residue management for soil-function improvement; recommendations from field interventions at two agro-ecological zones in South Asia

Utilization of biomass energy from various agricultural wastes for local usages and its removal through open burning potentially increase emission of Green House Gases (GHGs), deteriorate air-quality, formation of tropospheric ozone and create trans-boundary health hazards in countries of South East Asia. The effect of common agro-waste management practices in soil quality and agricultural production system over this part of the world is not well documented. In the present three-years long study, spanning over two entirely different agro-ecological zones of India and Bhutan, highlights the impacts of the burning of agricultural waste in soil physio-chemical properties, biological properties and crop production. The current study also focuses on the alternative usage of crop residue to enhance soil organic carbon, soil moisture, soil nutrients and soil biological activity through the application of biochar and raw agricultural waste generated from the field. It was observed that crop residue used as raw mulch and biochar improved the agricultural production up to 36%–64% over the experimental fields of India and Bhutan. The results from the study disseminated among the local farmers and technological support were provided for practicing alternative crop residue management. Nearly 1450–1500 farmers in India and 100–125 farmers in Bhutan have adopted the agro-waste management practices of removal and re-application of agro-wastes in the field. A total of ~26000 t of CO2 emission has been reduced in two intervention sites during the study period. The present action-research helps to propose future guidelines for environmental friendly crop residue utilization and management and simultaneously help to improve agricultural yield along with soil quality.

Evaluation and Identification of Promising Introgression Lines Derived From Wild Cajanus Species for Broadening the Genetic Base of Cultivated Pigeonpea [Cajanus cajan (L.) Millsp.

Pigeonpea [Cajanus cajan (L.) Millsp.], a multipurpose and nutritious grain legume crop, is cultivated for its protein-rich seeds mainly in South Asia and Eastern and Southern Africa. In spite of large breeding efforts for pigeonpea improvement in India and elsewhere, genetic enhancement is inadequate largely due to its narrow genetic base and crop susceptibility to stresses. Wild Cajanus species are novel source of genetic variations for the genetic upgradation of pigeonpea cultivars. In the present study, 75 introgression lines (ILs), derived from crosses involving cultivated pigeonpea variety ICPL 87119 and wild Cajanus cajanifolius and Cajanus acutifolius from the secondary gene pool, were evaluated for yield and yield-attributing traits in diverse environments across locations and years. Restricted maximum likelihood (REML) analysis revealed large genetic variations for days to 50% flower, days to maturity, plant height, primary branches per plant, pods per plant, pod weight per plant, 100-seed weight, and grain yield per plant. Superior ILs with mid-early to medium maturity duration identified in this study are useful genetic resources for use in pigeonpea breeding. Additive main effects and multiplicative interaction (AMMI) analysis unfolded large influence of environment and genotype × environment interaction for variations in yield. A few lines such as ICPL 15023 and ICPL 15072 with yield stability were identified, while a number of lines were completely resistant (0%) to sterility mosaic diseases and/or Fusarium wilt. These lines are novel genetic resources for broadening the genetic base of pigeonpea and bring yield stability and stress tolerance. High-yielding lines ICPL 15010, ICPL 15062, and ICPL 15072 have been included in the initial varietal trials (IVTs) of the All India Coordinated Research Project (AICRP) on pigeonpea for wider evaluation across different agro-ecological zones in India for possible release as variety(ies).

Seasonal (Kharif, Rabi and Zaid) Precipitation, Potential Evapotranspiration and Aridity Index with Respect to Various Agro Ecological Zones of India

Abstract Climate change has very significant impact on livelihoods and food security. The geospatial technology provides a better understanding of various themes related to climate change. This study examined the seasonal (kharif, rabi and zaid) long term (1970-2000) monthly climatic parameters such as precipitation, potential evapotranspiration over the country of India. The seasonal Aridity Index was computed and analyzed with respect to various agro-ecological zones of India. The analysis of long term mean precipitation (mm) during kharif, rabi and zaid season was found to be in the range of (14-7463), (0-914) and (0-1722) respectively. The analyses of the long term mean potential evapotranspiration in all seasons was found notable high in arid/semiarid zones. The Aridity Index during kharif, rabi and zaid seasons was found to be in the range of (0.19-4.27), (0.03-0.73) and (0.01-1.48) respectively. The seasonal Aridity Index in some of the agro-ecological zones of the central India in the arid and semiarid regions was found to be notably low. A concrete plan with synergic approach including integrated watershed management and traditional ecological practices will help to fulfill crop water demand and maintain adequate soil moisture for the present and future crops.

Development of Climate Data Bias Corrector (CDBC) Tool and Its Application over the Agro-Ecological Zones of India

The use of global and regional climate models has been increasing in the past few decades, in order to analyze the future of natural resources and the socio-economic aspects of climate change. However, these climate model outputs can be quite biased, which makes it challenging to use them directly for analysis purpose. Therefore, a tool named Climate Data Bias Corrector was developed to correct the bias in climatic projections of historical and future periods for three primary climatic variables—rainfall, temperature (maximum and minimum), and solar radiation. It uses the quantile mapping approach, known for its efficiency and low computational cost for bias correction. Its Graphical User Interface (GUI) was made to be feasible to take input and give output in commonly used file formats—comma and tab delimited file formats. It also generates month-wise cumulative density function (CDF) plot of a random station/grid to allow the user to investigate the effectiveness of correction statistically. The tool was verified with a case study on several agro-ecological zones of India and found to be efficient.

Integrated Nutrient Management for Improved Cauliflower Yield and Soil Health

ABSTRACTNutrient management in Cauliflower (Brassica oleracea var. botrytis L.) cultivation is in part dependent on the microbial population in the rhizosphere. Fertilizer must be applied to support plant growth and development. Whether fertilizer usage in cauliflower can be reduced needs to be determined. Rhizospheric isolates of cauliflower, obtained from soil around the roots and from their roots, in the low and mid-hills agro-ecological zones of India were tested for their efficacy to support cauliflower productivity. The plant growth–promoting rhizobacteria SB5, SB8, SB10, and SB11 exhibited the best plant growth–promoting traits with antagonism against soilborne pathogens compared to the reference strain Bacillus pumilus (JN559852). Application of SB11 (Bacillus spp.) exhibited the most plant growth–promoting attributes in field trials at 75% N and P and increased yield by 33% over the uninoculated control at 100% N and P. The isolate SB11 exhibited P solubilization, siderophore production, indole acetic acid production, hydrocyanic acid (HCN) production, and antifungal activity that may be developed as a plant growth–promoting rhizobacteria (PGPR) to enhance crop productivity and sustain soil health while saving 25% usage of chemical fertilizers.

Selection of Dwarf and Compact Morphotypes of Sweet Basil for High Density Plantation

Selection of Dwarf and Compact Morphotypes of Sweet Basil for High Density Plantation The experiment was conducted on five accessions of Sweet basil (Ocimum basilicum L.) at the ICAR- Directorate of Medicinal and Aromatic Plants Research (ICAR-DMAPR), Boriavi, Anand, Gujarat (India) for two successive years. Distinct germplasm with variability especially for plant growth characters and essential oil composition in basil are playing important role. Sweet basil is important aromatic plant in India and used as an ingredient of many international traditional aromatic systems. Accessions were identified from germplasm collected from different agro ecological zones of India. The identified accessions were characterized for uniqueness with desirable characters contributing in herbage yield. Among accessions sufficient variations for growth and yield characters were recorded. Rudra-2 was the most dwarf and DOB-4 as semidwarf accessions with early flowering. The accession Sant-1 had closed canopy architecture and DOB-8W was most vigorous type with high biological yield (664 q ha-1). The maximum anethole was in DOB-4 (89.17%) and methyl eugenol in DOB-8W (23.03%). Overall, Rudra-2 and Sant-1 were found unique and superior accessions therefore, can be used further in crop improvement programme and also suggested for commercial cultivation as a new selection for high density plantation.

Remotely sensed high resolution irrigated area mapping in India for 2000 to 2015.

India is among the countries that uses a significant fraction of available water for irrigation. Irrigated area in India has increased substantially after the Green revolution and both surface and groundwater have been extensively used. Under warming climate projections, irrigation frequency may increase leading to increased irrigation water demands. Water resources planning and management in agriculture need spatially-explicit irrigated area information for different crops and different crop growing seasons. However, annual, high-resolution irrigated area maps for India for an extended historical record that can be used for water resources planning and management are unavailable. Using 250 m normalized difference vegetation index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS) and 56 m land use/land cover data, high-resolution irrigated area maps are developed for all the agroecological zones in India for the period of 2000–2015. The irrigated area maps were evaluated using the agricultural statistics data from ground surveys and were compared with the previously developed irrigation maps. High resolution (250 m) irrigated area maps showed satisfactory accuracy (R2=0.95) and can be used to understand interannual variability in irrigated area at various spatial scales.

Role of mould occurrence in aflatoxin build-up and variability ofAspergillus flavusisolates from maize grains across India

The present study was conducted to study the role of mould/fungal occurrence on aflatoxin build-up in maize grains and correlation between toxigenic and genetic variability present among isolates of Aspergillus flavus obtained from maize grain samples. Eighty-six maize samples were collected from farmer's fields from various locations among the four maize growing agro-ecological zones of India. Among the microflora of maize grains studied, Aspergillus was the most predominant mould identified. Location Karnal (Haryana) was most sensitive to mould infection; 56.2% of samples), exhibited >20 μg/kg aflatoxin B1 (AFB1). On the other hand, Begusarai (Bihar) proves to be a less sensitive area for aflatoxin contamination with 90% of samples exhibiting <20 μg/kg AFB1. Varied isolates of A. flavus from grain samples were established in culture media and studied for toxigenic variability. In vitro high level variability (8,116.61-0.21 μg/kg) for aflatoxin production potential was found among these isolates. Random ...