soora naresh kumar | INDIAN AGRICULTURAL RESEARCH INSTITUTE, NEW DELHI, INDIA (original) (raw)

Papers by soora naresh kumar

Soil and Tillage Research

Acta Physiologiae Plantarum, 2022

Alex Ruane, Sonali McDermid, Nicholas Hudson, Cynthia Rosenzweig, L. R. Ahuja, Saseendran S. Anap... more Alex Ruane, Sonali McDermid, Nicholas Hudson, Cynthia Rosenzweig, L. R. Ahuja, Saseendran S. Anapalli, Jakarat Anothai, Senthold Asseng, Dumont Benjamin, Federico Bert, Patrick Bertuzzi, Virendra S. Bhatia, Marco Bindi, Ian Broad, Davide Cammarano, Ramiro Carretero, Uran Chung, Giacomo De Sanctis, Thanda Dhliwayo, Frank Ewert, Roberto Ferrise, Thomas Gaiser, Guillermo Garcia, Sika Gbegbelegbe, Vellingiri Geethalakshmi, Edward Gerardeaux, Richard Goldberg, Brian Grant, Edgardo Guevara, Holger Hoffmann, Huanping Huang, Flavio Barbosa Justino, Asha S. Karunaratne, Ann-Kristin Koehler, Soora Naresh Kumar, Arunachalam Lakshmanan, Xiaomao Lin, Qunying Luo, Graciela Magrin, Yuji Masutomi, Theodoros Mavromatis, Greg McLean, Santiago Meira, Monoranjan Mohanty, Marco Moriondo, Lamyaa Negm, Francesca Orlando, Isik Ozturk, Zhiming Qi, Johanna Ramarohetra, Helene Raynal, Gabriel Rodriguez, Vaishali Sharda, Lu Shuo, Ward Smith, Afshin Soltani, K.Srinivas, Dillip Kumar Swain, Fulu Tao, Kindie Tesf...

In this paper, the climate change scenarios of A2 and B2 for 2070-2100 time scale (denoted as 208... more In this paper, the climate change scenarios of A2 and B2 for 2070-2100 time scale (denoted as 2080) for several key locations of India and its impact on rice and wheat crops based on regional climate model (PRECIS) were described. The PRECIS projects an increase in temperature over most parts of India especially in the IGP (Indo-Gangetic Plains), the region that presently experiences relatively low temperatures. Extreme high temperature episodes and rainfall intensity days are projected to become more frequent and the monsoon rainfall is also projected to increase. Rabi (mid Nov-March) season is likely to experience higher increase in temperature which could impact and hence become threat to the crops which really require low temperature for their growth. Climatic variability is also projected to increase in both A2 and B2 scenarios. All these projected changes are likely to reduce the wheat and rice yields in Indo-Gangetic plains of India. It is likely that there will be more numbe...

Global change biology, Mar 7, 2016

A potato crop multi-model assessment was conducted to quantify variation among models and evaluat... more A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States) input management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with inter-annual variability, and predictions for all agronomic variables were significantly different from one model to another (p < 0.001). Uncertainty averaged 15% higher for low- versus high- input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as com...

Open Data Journal for Agricultural Research, 2018

Global change biology, 2019

Wheat grain protein concentration is an important determinant of wheat quality for human nutritio... more Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32-multi-model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low-rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO . Introducing genotypes adapted to warmer temperatures (and also considering changes in CO and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by -1.1 percentage points, representing a relative change of -8.6%. Climate change adaptation...

Global Change Biology

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under wa... more Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2 o C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 o C and 2.0 o C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multiclimate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by-2.3% to 7.0% under the 1.5 o C scenario and-2.4% to 10.5% under the 2.0 o C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall and global atmospheric CO 2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2 o C on wheat production are therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.

Global change biology, Nov 28, 2018

A recent innovation in assessment of climate change impact on agricultural production has been to... more A recent innovation in assessment of climate change impact on agricultural production has been to use crop multi model ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e-mean) and median (e-median) often seem to predict quite well. However few studies have specifically been concerned with the predictive quality of those ensemble predictors. We ask what is the predictive quality of e-mean and e-median, and how does that depend on the ensemble characteristics. Our empirical results are based on five MME studies applied to wheat, using different data sets but the same 25 crop models. We show that the ensemble predictors have quite high skill and are better than most and sometimes all individual models for most groups of environments and most response variables. Mean squared error of e-mean decreases monotonically with the size of the ensemble if models are added at random, but has a minimum at usually 2-6 models if bes...

Scientific reports, 2017

The CO2 fertilization effect is a major source of uncertainty in crop models for future yield for... more The CO2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO2] (E-[CO2]) by comparison to free-air CO2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO2] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO2] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO2] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice...

Nature plants, Jan 27, 2017

Nature Plants 3, 17102 (2017); published online 17 July 2017; corrected online 27 September 2017.

Brazilian Journal of Plant Physiology

Experiments were conducted on coconut seedlings to delineate events of photo-oxidative stress dam... more Experiments were conducted on coconut seedlings to delineate events of photo-oxidative stress damage. Studies on chlorophyll fluorescence indicated a clear case of excess light energy under high light conditions causing stress to coconut seedlings raised under coconut palms. Quantum yield of photo-chemistry of leaflets exposed to high light was significantly less than those under shade. Seedlings exposed to high light and then shifted to shade have shown significant improvement in quantum yield. Excess light energy harvested by chlorophyll antenna caused high non-photochemical quenching resulting in production of biologically toxic super oxide, hydrogen peroxide and hydroxyl radicals. It is apparent that photoinhibition of photosynthesis takes place due to i) PSII down regulation and ii) damage to PS II system in initial stages of exposure to excess light and under prolonged exposures inhibition is caused due to iii) chlorophyll bleaching and iv) damage to chloroplast and cell membrane integrity, followed by reduction in photosynthetically active leaf area because of scorching thus reducing canopy photosynthesis. Protein concentration in leaf tissue was higher in seedlings in high light conditions. Three distinct low molecular weight proteins with pI of 4.9, 8.4 and 10.15 having M r less than 20,000 were found in seedlings exposed to high light intensities. Results clearly demonstrate the events that take place at early stage to subsequent cascading effects leading to the scorching and death of leaf and even seedling death under severe conditions.

Nature plants, Jan 3, 2017

This corrects the article DOI: 10.1038/nplants.2017.102.

Nature plants, Jul 17, 2017

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation st... more Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

Nature Climate Change, 2016

Where a licence is displayed above, please note the terms and conditions of the licence govern yo... more Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

Field Crops Research, 2016

Projected global warming and population growth will reduce future water availability for agricult... more Projected global warming and population growth will reduce future water availability for agriculture. Thus, it is essential to increase the efficiency in using water to ensure crop productivity. Quantifying crop water use (WU; i.e. actual evapotranspiration) is a critical step towards this goal. Here, sixteen wheat simulation models were used to quantify sources of model uncertainty and to estimate the relative changes and variability between models for simulated WU, water use efficiency (WUE, WU per unit of grain dry mass produced), transpiration efficiency (Teff, transpiration per kg of unit of grain yield dry mass produced), grain yield, crop transpiration and soil evaporation at increased temperatures and elevated atmospheric carbon dioxide concentrations ([CO2]). The greatest uncertainty in simulating water use, potential evapotranspiration, crop transpiration and soil evaporation was due to differences in how crop transpiration was modelled and accounted for 50% of the total variability among models. The simulation results for the sensitivity to temperature indicated that crop WU will decline with increasing temperature due to reduced growing seasons. The uncertainties in simulated crop WU, and in particularly due to uncertainties in simulating crop transpiration, were greater under conditions of increased temperatures and with high temperatures in combination with elevated atmospheric [CO2] concentrations. Hence the simulation of crop WU, and in particularly crop transpiration under higher temperature, needs to be improved and evaluated with field measurements before models can be used to simulate climate change impacts on future crop water demand.