Food Supply and Security

India's total food grain production in 1950-1951 was low at 50.8 million tonnes, with a population of 361 million. Thus, the food grain production in 1950-1951 was 140.7 kg per person per annum or 0.39 kg per day. Thanks to Indian farmers and agricultural scientists who worked hard to increase the food grain production through new crop varieties and production technologies, along with the supportive policies of the governments that paved the way for the Green Revolution in Indian Agriculture. Achievements of the green revolution further led to achievements in other agricultural and allied sectors like the white revolution with substantial gains from milk production, followed by the yellow revolution with a significant increase in edible oilseed production, and the pink revolution with an increase in meat and poultry production to a significant extent. This chapter mainly discusses where does India stand today in terms of its agriculture when compared to its independence in 1947? As the data for 1947 for most of the indicators is not available, 1951 is considered the base year and compared the various indicators for the year 2021

Responses of Soybean to Water Stress and Supplemental Irrigation in Upper Indo-Gangetic Plain: Field Experiment and Modeling Approach

Understanding better the impacts of extreme dry spell regimes is essential for optimizing water management under a changing and variable climate. Using field experiments and modeling studies, we examined the impacts of dry spells in soybean and identified better management of water resources under varying water-scarce conditions. Field experimental data from soybean (PUSA-2614) experiments (July-Oct 2014; IARI, New Delhi, India) were used to calibrate and validate InfoCrop-Soybean model. This model was used to simulate optimal timing of irrigation under different dry spell scenarios. Results showed that plants subjected to water stress during flowering and vegetative growth stages had significantly lower yields and total dry matter (TDM). Supplemental irrigation significantly increased TDM and yields. InfoCrop-Soybean could simulate plant responses to water stress, at various stages of crop growth, and to supplemental irrigation, with acceptable accuracy. The crop model was further used to simulate impacts of dry spells at different intensities and durations on soybean growth and yields by creating drought scenarios for the New Delhi region using 36 years of weather data (1978–2014). Simulations showed that a 20% reduction in rainfall during any fortnight (every 15th day) of the cropping season does not affect crop yield significantly. However, dry spells (50% reduction in rainfall or more) in August and early September led to reduced yields, while supplemental irrigation during those dry spells could reduce yield losses. We envisage that the results of this study can help better manage water in soybean cultivation under dryland condition

Assessment of impacts of climate change on rice and wheat in the Indo-Gangetic plains

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 number of years with low yields occurs towards the end of the century. Such yield reductions in rice and wheat crops due to climate change are mediated through reduction in crop duration, grain number and grain filling duration. The yield loss will be more in A2 scenario compared to B2. These quantitative estimates still have uncertainties associated with them, largely due to uncertainties in climate change projections, future technology growth, availability of inputs such as water for irrigation, changes in crop management and genotype. These projections nevertheless provide a direction of likely change in crop productivity in future climate change scenarios

Long-term adoption of bed planted conservation agriculture based maize/cotton-wheat system enhances soil organic carbon stabilization within aggregates in the indo-gangetic plains

Sustainability of contemporary crop establishment and management practices is questioned due to soil degradation, higher carbon emission and declining soil productivity. Hence, this study was conducted to address the impacts of conservation agriculture (CA) practices like permanent broad beds (PBB), permanent narrow beds (PNB) and zero tilled flat beds (ZT) with residue retention on soil organic carbon (SOC) protection within aggregates in the Indo-Gangetic Plains (IGP). Compared to conventionally tilled (CT) plots, the total SOC content was ∼27%–33% higher in the CA plots on equivalent mass basis. The soil physical properties, such as soil aggregation and mean weight diameter were considerably improved under the CA practices. The macroaggregates were ∼41, 37% and 27% higher in the PBB with residue (PBB + R), PNB with residue (PNB + R) and ZT with residue (ZT + R) plots (CA plots), respectively, than the CT plots in the surface soil (0–15 cm). The plots under PBB + R had ∼31% higher microaggregates within macroaggregates than the CT plots (24.4 g 100 g−1) soil. An increase in SOC content by ∼72, 55% and 69% was observed in the PBB + R, PNB + R and ZT + R plots over the CT plots in microaggregates within macroaggregates (3.02 Mg ha−1). However, plots under PBB + R, PNB + R and ZT + R had only ∼11, 3% and 23% more SOC within silt + clay fraction, respectively, than CT plots (5.85 Mg ha−1). Thus, SOC stabilization within microaggregates inside macroaggregates was the major mechanism, and not the chemical stabilization within silt + clay, of C sequestration under CA. As aggregate-associated carbon is an ecosystem property that strongly affects organic carbon stabilization, water holding capacity and resistance to erosion, growing maize/cotton–wheat system under PBB + R practice is a viable option for carbon sequestration in the IGP and similar agro-ecologies

Global wheat production with 1.5 and 2.0°C above pre‐industrial warming

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°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 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate 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°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 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°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade

Similar estimates of temperature impacts on global wheat yield by three independent methods

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.<br/

Climate change and coconut plantations in India: Impacts and potential adaptation gains

The assessment of impact of climate change on coconut, a plantation crop, is challenging. However, the development of a simulation model (InfoCrop-COCONUT) has enabled the process. We present the first simulation analysis of the potential impacts of climate change on coconut productivity in India following two approaches, namely: (i) ‘fixed increase in temperature and CO2, and (ii) scenarios as per PRECIS (Providing Regional Climates for Impact Studies) – a regional climate model. Impact of changed management on coconut productivity in current as well as in future climates is also assessed. Climate change is projected to increase coconut productivity in western coastal region, Kerala, parts of Tamil Nadu, Karnataka and Maharashtra (provided current level of water and management is made available in future climates as well) and also in North-Eastern states, islands of Andaman and Nicobar and Lakshadweep while negative impacts are projected for Andhra Pradesh, Orissa, West Bengal, Gujarat and parts of Karnataka and Tamil Nadu. On all India basis, even with current management, climate change is projected to increase coconut productivity by 4.3% in A1B 2030, 1.9% in A1B 2080, 6.8% in A2 2080 and 5.7% in B2 2080 scenarios of PRECIS over mean productivity of 2000–2005 period. Agronomic adaptations like soil moisture conservation, summer irrigation, drip irrigation, and fertilizer application cannot only minimize losses in majority of coconut growing regions, but also improve productivity substantially. Further, genetic adaptation measures like growing improved local Tall cultivars and hybrids under improved crop management is needed for long-term adaptation of plantation to climate change, particularly in regions that are projected to be negatively impacted by climate change. Such strategy can increase the productivity by about 33% in 2030, and by 25–32% in 2080 climate scenarios. In fact, productivity can be improved by 20% to almost double if all plantations in India are provided with above mentioned management even in current climates. In places where positive impacts are projected, current poor management may become a limiting factor in reaping the benefits of CO2 fertilization, while in negatively affected regions adaptation strategies can reduce the impacts. Thus, intensive genetic and agronomic adaptation to climate change can substantially benefit the coconut production in India

Assessment on vulnerability of sorghum to climate change in India

It is important to analyse the impacts of climate change on target production system. However, it is more important to deduce possible adaptation strategies so that the research and developmental policies can be guided to meet the challenges of climate change. Impacts of climate change on the sorghum production system in India are analysed using InfoCrop-SORGHUM simulation model. In general, impact of climate change is projected to be more on winter crop in central (CZ) and south-central zones (SCZ), while in south-west zone (SWZ) the impacts are likely to be higher on monsoon crop. Climate change is projected to reduce monsoon sorghum grain yield to the tune of 14% in CZ, SWZ and by 2% in SCZ by 2020. Yields are likely to be affected even more in 2050 and 2080 scenarios. Climate change impacts on winter crop are projected to reduce yields up to 7% by 2020, up to 11% by 2050 and up to 32% by 2080. Impacts are projected to be more in SWZ region than in SCZ,Z Z. But, the yield loss due to rise in temperature is likely to be offset by projected increase in rainfall. However, complete amelioration of yield loss beyond 2 °C rise may not be attained even after doubling of rainfall in south-central zone (SCZ) and in central zone (CZ). Results indicate that adaptation strategies like changing variety and sowing date can reduce the vulnerability of monsoon sorghum to about 10%, 2% and 3% in CZ, SCZ,Z WZ regions in 2020 scenario. Adaptation strategies reduced the climate change impacts and vulnerability of winter crop to 1–2% in 2020, 3–8% in 2050 and 4–9% in 2080. This indicates that more low-cost adaptation strategies should be explored to further reduce the net vulnerability of sorghum production system in India

Simulating impacts, potential adaptation and vulnerability of maize to climate change in India

Climate change associated global warming, rise in carbon dioxide concentration and uncertainties in precipitation has profound implications on Indian agriculture. Maize (Zea mays L.), the third most important cereal crop in India, has a major role to play in countryﾒs food security. Thus, it is important to analyze the consequence of climate change on maize productivity in major maize producing regions in India and elucidate potential adaptive strategy to minimize the adverse effects. Calibrated and validated InfoCrop-MAIZE model was used for analyzing the impacts of increase in temperature, carbon dioxide (CO2) and change in rainfall apart from HadCM3 A2a scenario for 2020, 2050 and 2080. The main insights from the analysis are threefold. First, maize yields in monsoon are projected to be adversely affected due to rise in atmospheric temperature; but increased rainfall can partly offset those loses. During winter, maize grain yield is projected to reduced with increase in temperature in two of the regions (Mid Indo-Gangetic Plains or MIGP, Southern Plateau or SP), but in the Upper Indo-Gangetic Plain (UIGP), where relatively low temperatures prevail during winter, yield increased up to a 2.7ﾰC rise in temperature. Variation in rainfall may not have a major impact on winter yields, as the crop is already well irrigated. Secondly, the spatio-temporal variations in projected changes in temperature and rainfall are likely to lead to differential impacts in the different regions. In particular, monsoon yield is reduced most in SP (up to 35%), winter yield is reduced most in MIGP (up to 55%), while UIGP yields are relatively unaffected. Third, developing new cultivars with growth pattern in changed climate scenarios similar to that of current varieties in present conditions could be an advantageous adaptation strategy for minimizing the vulnerability of maize production in India