Indian Central Research Institute for Dryland Agriculture

Hyderabad, India

Indian Central Research Institute for Dryland Agriculture

Hyderabad, India

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Chavan S.B.,Central Agroforestry Research Institute | Rao G.R.,Indian Central Research Institute for Dryland Agriculture | Keerthika A.,Indian Central Arid Zone Research Institute
Indian Journal of Ecology | Year: 2015

Studies on measuring CO2, CH4, and N2O fluxes from five agroforestry systems viz., teak, jatropha, pongamia, simaruba and leucaena were conducted at CRIDA, Hyderabad during June-August, 2013 in semi-arid alfisols. The fluxes were measured at weekly interval using closed static chamber technique and gas chromatography method. The highest mean soil CO2 emission observed in jatropha (5644.11 kg ha-1yr-1). teak (4422.90 kg ha-1yr-1) and simamba (4673.58 kg ha-1yr-1), whereas, lower values were recorded in pongamia (4575.28 kg ha-1yr-1) followed by leucaena (2556.94 kg ha-1yr-1). Observations regarding mean uptake in methane showed that in jatropha (8.57 kg ha-1yr-1) and Simaruba (7.37 kg ha-1yr-1) recorded higher values than pongamia (4.02 kg ha-1yr-1) and Teak (3.40 kg ha-1yr-1). The leucaena system (3.50 kg ha-1yr-1) was net emitter of methane as compared with other systems. Highest N2O fluxes during measurement period were observed in simaruba (140.62 kg ha-1yr-1), leucaena (123.96 kg ha-1yr-1) and pongamia (76.26 kg ha-1yr-1). In present study, temperature was most limiting factors than soil moisture among ail the agroforestry systems and produced better fit polynomial models with fluxes of gases. This study gives an idea of successive potential values of GHGs in agroforestry systems to compare with carbon sequestration abilities of these systems.


Sharma B.R.,International Water Management Institute | Rao K.V.,Indian Central Research Institute for Dryland Agriculture | Vittal K.P.R.,Indian Central Arid Zone Research Institute | Ramakrishna Y.S.,Indian Central Research Institute for Dryland Agriculture | Amarasinghe U.,International Water Management Institute
Agricultural Water Management | Year: 2010

A detailed district and agro-ecoregional level study comprising the 604 districts of India was undertaken to (i) identify dominant rainfed districts for major rainfed crops, (ii) make a crop-specific assessment of the surplus runoff water available for water harvesting and the irrigable area, (iii) estimate the efficiency of regional rain water use and incremental production due to supplementary irrigation for different crops, and (iv) conduct a preliminary economic analysis of water harvesting/supplemental irrigation to realize the potential of rainfed agriculture. A climatic water balance analysis of 225 dominant rainfed districts provided information on the possible surplus runoff during the year and the cropping season. On a potential (excluding very arid and wet areas) rainfed cropped area of 28.5 million ha, a surplus rainfall of 114 billion m3 (Bm3) was available for harvesting. A part of this amount of water is adequate to provide one turn of supplementary irrigation of 100 mm depth to 20.65 Mha during drought years and 25.08 Mha during normal years. Water used in supplemental irrigation had the highest marginal productivity and increase in rainfed production above 12% was achievable even under traditional practices. Under improved management, an average increase of 50% in total production can be achieved with a single supplemental irrigation. Water harvesting and supplemental irrigation are economically viable at the national level. Net benefits improved by about threefold for rice, fourfold for pulses and sixfold for oilseeds. Droughts have very mild impacts on productivity when farmers are equipped with supplemental irrigation. © 2009 Elsevier B.V. All rights reserved.


Rakshit S.,Directorate of Sorghum Research | Rakshit A.,Indian Central Research Institute for Dryland Agriculture | Patil J.V.,Directorate of Sorghum Research
Journal of Genetics | Year: 2012

Most traits of interest to medical, agricultural and animal scientists show continuous variation and complex mode of inheritance. DNA-based markers are being deployed to analyse such complex traits, that are known as quantitative trait loci (QTL). In conventional QTL analysis, F 2, backcross populations, recombinant inbred lines, backcross inbred lines and double haploids from biparental crosses are commonly used. Introgression lines and near isogenic lines are also being used for QTL analysis. However, such populations have major limitations like predominantly relying on the recombination events taking place in the F 1 generation and mapping of only the allelic pairs present in the two parents. The second generation mapping resources like association mapping, nested association mapping and multiparent intercross populations potentially address the major limitations of available mapping resources. The potential of multiparent intercross populations in gene mapping has been discussed here. In such populations both linkage and association analysis can be conductted without encountering the limitations of structured populations. In such populations, larger genetic variation in the germplasm is accessed and various allelic and cytoplasmic interactions are assessed. For all practical purposes, across crop species, use of eight founders and a fixed population of 1000 individuals are most appropriate. Limitations with multiparent intercross populations are that they require longer time and more resource to be generated and they are likely to show extensive segregation for developmental traits, limiting their use in the analysis of complex traits. However, multiparent intercross population resources are likely to bring a paradigm shift towards QTL analysis in plant species. © 2012 Indian Academy of Sciences.


Venkateswarlu B.,Indian Central Research Institute for Dryland Agriculture | Prasad J.V.N.S.,Indian Central Research Institute for Dryland Agriculture
Current Science | Year: 2012

Carrying capacity (CC) in the context of Indian agriculture, denotes the number of people and livestock an area can support on a sustainable basis. CC is dynamic in nature, varying from time to time based on utilization of resources, technology application and management. In India, rainfed agriculture occupies nearly 58% of the cultivated area, contributes 40% of country's food production, and supports 40% of the human and 60% of the livestock population. The food grains production has increased several fold in the last four decades. During the last decade (TE 1998-99 to TE 2008-09) the production in coarse cereals, oilseeds and pulses increased by 20%, 16% and 3% respectively, primarily due to the yield gains. There is a need to further increase food production substantially for meeting the requirements of the ever-increasing population. This will put tremendous strain on natural resources which are already under stress due to unsustainable utilization. Continuous decline in groundwater levels, growing deficiency of major and micronutrients, declining factor productivity and looming threat of climate change are some of the issues which will have a bearing on food production in the near future. However, the large realizable yield gaps in many rainfed crops, opportunities to increase yields through rainwater harvesting and recycling, soil fertility improvement, crop diversification and effective dissemination of technologies give a hope that future requirements of food can be met, but it requires substantial resources. This article discusses issues constraining rainfed crop production and possible ways to enhance productivity in a sustainable manner.


Kumar M.,Indian Central Research Institute for Dryland Agriculture | Raghuwanshi N.S.,Indian Institute of Technology Kharagpur | Singh R.,Indian Institute of Technology Kharagpur
Irrigation Science | Year: 2011

The use of artificial neural networks (ANNs) in estimation of evapotranspiration has received enormous interest in the present decade. Several methodologies have been reported in the literature to realize the ANN modeling of evapotranspiration process. The present review discusses these methodologies including ANN architecture development, selection of training algorithm, and performance criteria. The paper also discusses the future research needs in ANN modeling of evapotranspiration to establish this methodology as an alternative to the existing methods of evapotranspiration estimation. © 2010 Springer-Verlag.


Srinivasarao C.,Indian Central Research Institute for Dryland Agriculture | Venkateswarlu B.,Indian Central Research Institute for Dryland Agriculture | Lal R.,Ohio State University | Singh A.K.,Indian Council of Agricultural Research | Kundu S.,Indian Central Research Institute for Dryland Agriculture
Advances in Agronomy | Year: 2013

Soil organic carbon (SOC) is a strong determinant of soil quality and crop productivity, especially in the arid and semiarid environments of the tropics. Drought stress, high temperatures reaching up to 45 °C for 8-10 weeks in a year, coupled with low biomass productivity are common features of dry agroecosystems. India, with only 2.5% of the world's geographical area, is a home to 17% of the global population. Population increased from 361 million in 1951 to 1140 million in 2011, more than threefold increase over 50 years. Productivity levels of rainfed dryland crops are far below those of global average. Thus, increasing productivity of rainfed cropping systems is an urgent task to meet the food demand of an ever-increasing population because 57% of the total arable land area of 141. Mha is under rainfed farming. Yields of important rainfed production systems in long-term manurial experiments under different climate and soil types show declining trends even with adoption of some recommended management practices (RMPs). Some RMPs include diverse crop rotations with legumes, and integrated nutrient management (INM) involving addition of farmyard manure (FYM), use of groundnut shells (GNS) and other crop residues (CRs), green leaf manuring (GLM), etc. These RMPs have been tested in seven long-term experiments of 13-27 years duration established in diverse soils and agroecoregions. These studies, under the auspices of the All India Coordinated Research Project on Dryland Agriculture (AICRPDA), were conducted under diverse soil and climatic conditions, viz., Anantapur and Bengaluru (Alfisol), Solapur and Indore (Vertisol), Sardar Krushinagar (Entisol), and Varanasi (Inceptisol). Seven rainfed cropping system experiments involved major crops of the region including groundnut (Arachis hypogaea), finger millet (Eleusine coracana), winter sorghum (Sorghum bicolor), pearl millet (Pennisetum glaucum), cluster bean (Cyamopsis tetragonoloba), castor (Ricinus communis), soybean (Glycine max), safflower (Carthamus tinctorius), lentil (Lens esculenta), and upland rice (Oryza sativa). Diverse nutrient management treatments assessed included cattle manure, green leaf manure, crop residues, and chemical fertilizers. Common soil fertility management treatments across seven experiments were control (no fertilizer or organics), 100% recommended dose of fertilizers (RDFs), 50% RDF. +. 50% organics, and 100% organics. Maintaining or improving SOC concentration in rainfed dryland agroecosystems is a major agronomic challenge. Yet, the data from long-term experiments show that increasing SOC concentration by C sequestration and stabilization positively affects yields of several crops. Agronomic efficiency of added nutrients and partial factor productivity of crops are maintained or enhanced with INM practices including application of organics in conjunction with chemical fertilizers, but decline with application of only chemical fertilizers because of declining SOC concentration and soil quality with continuous cropping. In comparison with the control, grain yield of all crops are increased significantly with the adoption of INM practices using locally available organic resources. The magnitude of increase in yield (Mgha-1) in respect to control is from: (1)0.78 to 1.03 in groundnut with 50% RDF+FYM4Mgha-1, (2) 0.40 to 1.34 and 0.82 to 3.96 in groundnut and finger millet, respectively, through FYM10Mgha-1+100% NPK in groundnut-finger millet rotation, (3) 0.84 to 3.28 in finger millet through FYM10Mgha-1+100% NPK, (4) 0.61 to 1.19 in winter sorghum through 25kgNha-1 (Leucaena clippings)+25kgNha-1 (urea), (5) 0.43 to 0.81, 0.32 to 0.58 and 0.44 to 0.83 in pear millet, cluster bean, and castor, respectively, through 50% RDN (fertilizer)+50% RDN (FYM), (6) 1.04 to 2.10 and 0.63 to 1.49 in soybean and safflower, respectively, through FYM6Mgha-1+20kgN+13kgPha-1, and (7) 1.08 to 1.95 and 0.48 to 1.04 in rice and lentil, respectively, through 50% N (FYM)+50% RDF treatment. Treatments receiving INM practices also exhibited higher sustainable yield index (SYI) over unfertilized control and sole application of either chemical fertilizers or organic manures. For every Mgha-1 increase in SOC stock in the root zone, there was an increase in grain yield (kgha-1) of 13 for groundnut, 101 for finger millet, 90 for sorghum, 170 for pearl millet, 145 for soybean, 18 for lentil, and 160 for rice. Improved nutrient management practices were identified on the basis of the mean rate of SOC sequestration. The average SOC sequestration rate (kgCha-1year-1) measured with different management treatments were: (1) 570 for 50% RDF+4Mgha-1 GNS, (2) 570-720 for FYM 10Mgha-1+100% NPK, (3) 650 for 25kgNha-1 (sorghum residue)+25kgN (Leucaena clippings), (4) 240 for 50% RDN (fertilizer)+50% RDN (FYM), (5) 790 for FYM6Mgha-1+20kgN+13kg P, and (6) 320 for 100% organic (FYM). The critical level of C input requirements for maintaining SOC at the antecedent level ranged from 1 to 3.5MgCha-1 year-1 and differed among soil type and production system. The critical level of C input was higher in soybean system and lower in winter sorghum system and increased with increase in mean annual temperature from humid to semiarid to arid ecosystems. Thus, RMPs based on locally available organic resources are a win-win situation for improving productivity and SOC sequestration, thus advancing food security and improving the environment. © 2013 Elsevier Inc.


Shanker A.K.,Indian Central Research Institute for Dryland Agriculture | Maheswari M.,Indian Central Research Institute for Dryland Agriculture | Yadav S.K.,Indian Central Research Institute for Dryland Agriculture | Desai S.,Indian Central Research Institute for Dryland Agriculture | And 3 more authors.
Functional and Integrative Genomics | Year: 2014

Among the effects of impending climate change, drought will have a profound impact on crop productivity in the future. Response to drought stress has been studied widely, and the model plant Arabidopsis has guided the studies on crop plants with genome sequence information viz., rice, wheat, maize and sorghum. Since the value of functions of genes, dynamics of pathways and interaction of networks for drought tolerance in plants can only be judged by evidence from field performance, this mini-review provides a research update focussing on the current developments on the response to drought in crop plants. Studies in Arabidopsis provide the basis for interpreting the available information in a systems biology perspective. In particular, the elucidation of the mechanism of drought stress response in crops is considered from evidence-based outputs emerging from recent omic studies in crops. © 2014 Springer-Verlag Berlin Heidelberg.


Vijaya Kumar P.,Indian Central Research Institute for Dryland Agriculture
European Journal of Plant Pathology | Year: 2014

Weather based prediction models for leaf rust were developed using disease severity and weather data recorded at four locations viz. Ludhiana, Kanpur, Faizabad and Sabour of the All India Wheat and Barley Improvement Project. Weeks 7–9 of the crop growing season at Ludhiana, Faizabad and Sabour and weeks 10–12 at Kanpur were identified as critical periods for relating weather variables to disease. Highly significant correlation coefficients were found between disease severity and a greater number of weather variables in these critical 3-week periods than at other times. The correlation coefficients were greatest for the Humid Thermal Ratio (HTR), Maximum Temperature (MXT) and Special Humid Thermal Ratio (SHTR), and these three weather variables were selected as predictor variables. Linear regressions with these predictor variables (individually) during the critical periods, and a multiple regression with MXT and relative humidity (RH), serve as four disease prediction models, with sufficient lead-time to take control measures. Validation of these prediction models with independent disease severity data showed that the regression equation with MXT (Model-1) was the best among the prediction models, with four out of six simulations matching observed disease severity classes and also having lowest residual sum of squares (SSE) value of 2727. Models 4 (multiple regression), 2 (HTR) and 3 (SHTR) with SSE values of 2881, 3092 and 3732, respectively are in order of decreasing accuracy of prediction. The model using MXT can be used to predict the disease severity in the Indo-Gangetic Plains and provide the basis for efficient disease control. © 2014, Koninklijke Nederlandse Planteziektenkundige Vereniging.


Grover M.,Indian Central Research Institute for Dryland Agriculture | Ali S.Z.,Indian Central Research Institute for Dryland Agriculture | Sandhya V.,Indian Central Research Institute for Dryland Agriculture | Rasul A.,Indian Central Research Institute for Dryland Agriculture | Venkateswarlu B.,Indian Central Research Institute for Dryland Agriculture
World Journal of Microbiology and Biotechnology | Year: 2011

Increased incidences of abiotic and biotic stresses impacting productivity in principal crops are being witnessed all over the world. Extreme events like prolonged droughts, intense rains and flooding, heat waves and frost damages are likely to further increase in future due to climate change. A wide range of adaptations and mitigation strategies are required to cope with such impacts. Efficient resource management and crop/livestock improvement for evolving better breeds can help to overcome abiotic stresses to some extent. However, such strategies being long drawn and cost intensive, there is a need to develop simple and low cost biological methods for the management of abiotic stress, which can be used on short term basis. Microorganisms could play a significant role in this respect, if we can exploit their unique properties of tolerance to extremities, their ubiquity, genetic diversity, their interaction with crop plants and develop methods for their successful deployment in agriculture production. Besides influencing the physico-chemical properties of rhizospheric soil through production of exopolysaccharides and formation of biofilm, microorganisms can also influence higher plants response to abiotic stresses like drought, chilling injury, salinity, metal toxicity and high temperature, through different mechanisms like induction of osmo-protectants and heat shock proteins etc. in plant cells. Use of these microorganisms per se can alleviate stresses in crop plants thus opening a new and emerging application in agriculture. These microbes also provide excellent models for understanding the stress tolerance, adaptation and response mechanisms that can be subsequently engineered into crop plants to cope with climate change induced stresses. © 2010 Springer Science+Business Media B.V.


Babita M.,Acharya N.G. Ranga Agricultural University | Maheswari M.,Indian Central Research Institute for Dryland Agriculture | Rao L.M.,Acharya N.G. Ranga Agricultural University | Shanker A.K.,Indian Central Research Institute for Dryland Agriculture | Rao D.G.,Indian Central Research Institute for Dryland Agriculture
Environmental and Experimental Botany | Year: 2010

A study was conducted to analyse the association of osmotic adjustment (OA) with drought tolerance and yield in castor (Ricinus communis L.). Hybrids (GCH4, DCH32 and DCH177) and their respective parents (VP-1, 48-1, LRES17, DCS5, DPC9 and DCS9) were assessed for their osmotic adjustment, leaf water relations, accumulation of compatible solutes in relation to seed yield in response to moisture stress at primary spike development stage. OA increased with increasing stress period up to 33 days and the increase was more rapid in the high OA (HOA) genotypes. HOA genotypes also had higher leaf RWC and ELWRC and maintained higher leaf water potentials (Ψ l) compared to LOA genotypes under water deficit. Genotypes with HOA accumulated greater levels of proline, total soluble sugars (TSS), total free amino acids (FAA) and potassium than those with LOA in response to water deficit. Contribution of TSS was the maximum (61%), compared to FAA (17%), proline (12%) and potassium (2.8%) to the Ψ s at 33 days after imposing water deficit indicating that sugars were the major contributors towards OA in castor leaves. A positive relationship existed between OA of expanded leaf 33 days after imposing stress (r=0.8539) and total seed yield under water-limited conditions in various castor genotypes tested and HOA genotypes had higher total seed yield than genotypes with LOA. Genotype variability exists for OA and it is a heritable trait in castor. Hybrids followed their superior parents in terms of OA. HOA genotypes of castor produced significantly higher seed yield than LOA genotypes. Accumulation of TSS contributed largely to the OA in castor. © 2010 Elsevier B.V.

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