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A long-term experiment was conducted during kharif seasons of2013 to 2020 at AICRP on Agrometeorology, VNMKV, Parbhani, to study the crop-weather relationship of soybean grown under four environments (27th SMW, 28th SMW, 29th SMW and 30th SMW) with three soybean varieties (MAUS-158, MAUS-71, and JS-335). Results indicated that soybean yield was significantly highest in (1541.4 kg ha-1) in the early sown crop, and it decreased with delay in sowing with the lowest yield (803.8 kg ha-1). Among the cultivars, MAUS-158 produced significantly the highest yield (1321.3 kg ha-1). Correlation analysis between weather parameters during different phases with the yield revealed that the vegetative and grain formation period of soybean were found to be the most sensitive to weather parameters, as the correlation coefficients with most of the weather parameters. Rainfall, number of rainy days, humidity and soil moisture had favorable effects while temperatures and sunshine duration had negative effects on the yield of soybean in the Marathwada region. Individual weather parameters during 50% flowering to maturity period could explain 40 to 55% variation in the soybean yield while the multiple regression developed all weather parameters during grain formation to physiological maturity period could explain up to 82% variation which could be used the predict the soybean yield in Marathwada region. [ABSTRACT FROM AUTHOR]

Agriculture is significantly impacted by the variability in weather patterns, imposing substantial constraints on farmers’ ability to make informed tactical and strategic decisions regarding their crops. Seasonal climate projections have shown potential for informing agricultural decisions, but the actual adoption of climate information by farmers has been relatively slow and limited. The present study was conducted with the objective of investigating the characteristics of adopters, the communication network, and the level of farmer’s satisfaction concerning the adoption and continued use of Agromet Advisories Services (AAS). Two semi-arid districts, namely Kurnool and Anantapur in Andhra Pradesh, were purposively selected, wherein 280 farmers constituted the sampling frame. In this study, social network analysis (SNA) was conducted to examine the peer-to-peer communication patterns, while importance-performance analysis (IPA) was employed to evaluate farmer’s satisfaction, contributing to the continued adoption of AAS. The findings revealed that with regard to personality and communication characteristics, farmers were in the low category for their ability to cope with uncertainties and risk and even for their information-seeking behavior. Furthermore, the results showed farmers to be highly satisfied with the overall adoption of AAS. However, the IPA matrix revealed that among the nine attributes, the credibility of the forecasts needed refinement to promote sustained adoption. Excessive emphasis was placed on attributes such as the frequency of forecasts, which could be channeled into other initiatives. Peer-to-peer communication emerged as a crucial strategy in the adoption of AAS. Governments, non-governmental organizations, and extension functionaries should make a concerted effort to enhance the continued adoption of AAS by involving local stakeholders in sharing and participating in climate information production, forming farmer’s groups, and focusing on farmers’ literacy toward AAS. [ABSTRACT FROM AUTHOR]

Black gram is a widely grown pulse crop in Asia, prized for its nutritional value and compatibility with various cropping systems. However, the occurrence of powdery mildew, Erysiphe polygoni DC disease poses a significant challenge to black gram production, resulting in potential yield losses in Tamil Nadu. Over a six-year period, spanning from 2017-2018 to 2022-2023, field experiments were conducted during the rabi season at the black soil farm of the Agricultural Research Station in Kovilpatti, Tamil Nadu. The primary objective was to evaluate the incidence of powdery mildew in black gram and establish a statistical model by correlating it with weather variables. Notably, observations of disease index were most frequent during the flowering and pod development stages of the crop. Among the eleven weather parameters considered in the study, maximum temperature, afternoon relative humidity, and sunshine hours emerged as the key contributors to explaining the variation in the disease index. Further, a beta regression model was developed using these selected variables to predict powdery mildew incidence in black gram. [ABSTRACT FROM AUTHOR]

The paper contributes to the growing literature highlighting the significance of assessing risk and vulnerability, micro-level perceptions and adaptation decision-making in building resilience of farm communities to climate change in dryland region of India. To select a region for grassroots enquiry, spatial differential in risk to climate change was assessed in Rajasthan, using IPCC AR5 framework. Among the highly vulnerable and risky districts, Bikaner district was selected for elicitation of micro-level imperatives. Rising atmospheric temperature, inter-seasonal displacements of rainfall and recurrence of extreme events were perceived by the farmers resulting in resource degradation, production risks and erosion of households' socio-economic dynamics. As risk preventive measures, suitable adjustment in agricultural practices, natural resource management, shift to off-farm activities and other relief measures were adopted by the farmers. Farmer's choice of adaptation was influenced by several climatic, socio-economic and infrastructural & institutional factors in varying degree. Moreover, several financial, economic, infrastructural and informational bottlenecks to adaptations were reported during household survey and FGDs. The results suggest that capturing grassroots evidence is crucial for directing locally tailored adaptation strategies, along with the improving deficiencies in the developmental pathways for climate-resilient agriculture. [ABSTRACT FROM AUTHOR]

Fall armyworm, Spodoptera frugiperda (J. E. Smith) is a polyphagous and highly destructive invasive insect pest of many crops. It was recently introduced into India and widely reported in almost all parts of India. Development of a temperature-based phenology model for predicting its rate of development and distribution will help in understanding the establishment and further spread of introduced invasive insect pests. Development, survival and reproduction parameters of S. frugiperda at six constant temperature conditions (15, 20, 25, 27, 30 and 35°C) were investigated and further validated with data generated under fluctuating temperature conditions. The estimated lower developmental threshold temperatures were 12.1°C for eggs, 11°C for larvae, 12.2°C for pupae, 15.13°C for males and 12.66°C for females. Degree-day (DD) requirements for the development of the different stages of S. frugiperda were 50, 250 and 200 DD for egg, larva and pupa, respectively. The best-fitted functions were compiled for each life stage to yield a phenology model, which was stochastically simulated to estimate the life table parameters. The developed phenology model predicted temperature ranges between 27 and 30°C as favourable for S. frugiperda development, survival and reproduction. The results revealed that maximum net reproductive rate (215.66 females/female/generation) and total fecundity (981.08 individuals/female/generation) were attained at 30°C constant temperature. The mean length of generations decreased from 74.29 days at 15°C to 38.74 days at 30°C. The maximum intrinsic rate of increase (0.138 females/female/day) and shortest doubling time (4.9 days) were also observed at 30°C. Results of simulated life table parameters showed high temperature-dependent development of S. frugiperda and complete development within all the tested constant temperature ranges (15–35°C). Simulated life table parameters for predicting risk indices of S. frugiperda in India indicated a significant increase in activity indices and establishment risk indices with a higher number of generations during future (2050 and 2070) climatic change scenarios compared to present conditions. Our results indicate that India will be highly suitable for the establishment and survival of S. frugiperda in future time periods. [ABSTRACT FROM AUTHOR]

The evaluation of climatic change impact on maize grain and biomass yield under different N management practices through a well-calibrated and validated APSIM model in Vertisol of central India has been made. Climate scenarios were derived from seven global climate models (GCM) for two representative concentration pathways (RCPs), i.e. RCP4.5 and RCP8.5, and two-time slices, i.e. 2050 and 2080. The five N scenarios, namely N0%, N50%, N100%, N150%, and 100% organic, were studied in different climatic scenarios. The probability of exceedance showed that N0%, N50%, N100%, N150%, and 100% organic treatments have a 50% chance of yield greater than 1.0, 3.40, 4.20, 4.45 and 3.84 t ha-1, respectively. The average reduction of maize yield was -44.4, -20, -19.7 - 17.9 and 22.5 per cent in N 0%, N 50%, N 100%, N 150%, 100% organic, respectively under RCP4.5 over the baseline period (1980-2010). For RCP8.5, the average reduction of maize yield in N 0%, N 50%, N 100%, N 150%, 100% organic was 41.2, 21.2, 20.8 20.6 and 23.1 per cent, respectively. Simulation results suggested that a higher decrease of maize yield in 100 per cent organic treatments than inorganic treatments is due to variability in N uptake. [ABSTRACT FROM AUTHOR]

Physiology of green gram is highly sensitive to fluctuations in the thermal environment. Abnormally high temperatures during pod setting to pod development stage induces reduction in pod setting, non-healthy development and early maturity of grain which results in yield decline. We evaluated the effect of elevated temperatures in a Temperature Gradient Tunnel (TGT) on phenology, physiology and crop performance of green gram cultivars at semi-arid climate of Indian Punjab (Ludhiana). Five green gram cultivars were grown in TGT chambers in a factorial randomized block design with varying level of elevated temperatures (+3.3° C to 5.2° C) for two consecutive kharif seasons (2015-2016). The results reveal that the phenological stages of green gram, were advanced under elevated temperature within the TGT compared to open / ambient condition by 12-13 days. Maximum influence was observed in pod formation and pod maturity stages. With rise in temperatures by 3.3 to 5.2°C in TGT over ambient condition, the plant height increased but the number of branches per plant and the total above ground biomass as well as grain yield decreased consistently. It was found that with 1 oC increase in average seasonal temperature, the grain yield decreased by 75 kg ha-1. On the other hand, the harvest index was in general lower inside TGT chamber implying adverse influence of elevated temperature on biomass production although the partitioning of biomass was more efficient inside the TGT as evident from increase in harvest index. There was strong negative correlation of elevated temperature (inside TGT) with different yield attributes like 1000 seed weight, number of seeds per pod and number of pods per plant. Among the five green gram cultivars, ML-2037 was the most tolerant while cv. SML-1811 was the most susceptible to elevated temperature condition. In general, the grain yield decreased linearly with gradual increase in temperature. Average seasonal temperature of 29-30 oC may be considered as the favourable thermal conditions for the green gram crop in semi-arid conditions of Punjab. However, the future thrust will be to create more temperature gradients in the lower side so that the critical temperature threshold limits for optimum yield of green gram can be ascertained more accurately. [ABSTRACT FROM AUTHOR]

There is a global concern about the effects of climate change driven shifts in species phenology on crop pests. Using geographically and temporally extensive data set of moth trap catches and temperatures across the cotton growing states of India, we predicted the phenology of cotton pink bollworm Pectinophora gossypiella (Saunders). Our approach was centered on growing degree days (GDD), a measure of thermal accumulation that provides a mechanistic link between climate change and species' phenology. The phenology change was predicted by calculating absolute error associated with DD and ordinal date, an alternative predictor of phenology, for peak moth abundance. Our results show that GDD outperformed the ordinal dates in predicting peak moth abundance in 6 out of 10 selected locations. Using established thresholds of 13.0/34.0 °C, mean DD accumulated between the consecutive moth peaks across different years were estimated at 504.05 ± 4.84. Seven generations were determined for pink bollworm in a cropping season, the length of which varied between 35 and 73 days in response to temperature. Pink bollworm population reached its peak during third generation which can be the target for management actions. The study provides essential information for developing pink bollworm management strategies under climate change. [ABSTRACT FROM AUTHOR]

Globally, agriculture is recognized as a highly vulnerable sector to climate change and risks from climatic aberrations pose an imminent danger to the food security and sustainability of livelihoods. To bring robustness in climate adaptation planning, evaluation of resilience across homogenous regions is essential for developing and scaling suitable location-need-context specific interventions and policies that build the resilience of the agricultural system. In this paper, we present an analysis and discussion of multi-scalar and multi-indicator assessment, by profiling resilience across agro-climatic zones of India, based on the development of a Climate-Resilient Agriculture Index embracing environmental, technological, socio-economic, and institutional and infrastructural dimension. A total of 26 indicators, spread across these four dimensions, were employed to purport inter- and intra-agro-climatic zone differentials in the level of resilience. Among the zones, it was found that West Coast Plains & Ghats and Tans-Gangetic Plains had the highest degree of resilience to manage climate risks. Most of the districts lying within Eastern Himalayan Region, Middle Gangetic Plains, Eastern Plateau & Hills, and Western Dry Region had a lower degree of resilience. The study places greater emphasis on deciphering region-specific drivers and barriers to resilience at a further disaggregated scale for improving rural well-beings. It is construed that devising action plans emphasizing awareness, preservation of natural resources, diversification, building physical infrastructure, strengthening of grass-root institutions, and mainstreaming climate adaptation in the developmental policy is crucial for climate-resilient pathways. [ABSTRACT FROM AUTHOR]

Soybean is an important crop, and physiologically, it is photosensitive in nature and therefore, is likely to be highly affected by the atmospheric brown clouds (ABCs) which reduce PAR (Photosynthetically Active Radiation) availability, and moisture stress conditions those may prevail as a consequence of climate change scenario. Therefore, the impact of reduced natural PAR was evaluated on its determinate (DT; cv. JS-93-05), semi-determinate (SDT; cv. JS-335) and indeterminate (IDT; cv. Kalitur) genotypes. For simulating the reduced PAR condition, three different shapes of structures, viz., rectangular-cuboid, octagonal-dome and hemispherical-dome with shade-net covering were initially tested to check the uniformity of PAR availability inside the structure and the last one was found better. The light saturation point (LSP) was found to be 800, 1200 and 1000 PAR µmol m-2s-1 in case of DT, SDT and IDT genotypes, respectively. Under reduced PAR and restricted irrigation condition, the photosynthetic rate was 20.8, 21.9 and 28.9 µmol m-2s-1 in case of DT, SDT and IDT cultivars, respectively, while their seed yields were 151.3, 238.7 and 264.2 kg ha-1 indicating better source-sink relations of the IDT cultivar. Therefore, it is projected that IDT cultivars are likely to be popular under futuristic scenarios of low PAR availability and water scarcities. [ABSTRACT FROM AUTHOR]

Energy fluxes and canopy microclimate of wheat grown on the edaphically stressed shallow basaltic soil at Baramati, India were studied during 2014-15.The crop was grown with optimum irrigation, applied at frequent intervals, resulting in a low seasonal Bowen ratio (H/LE: Sensible heat flux/Latent heat flux) value of 0.23. The diurnal average flux rate for H during various phenophases varied between 2.2 and 16.2 Wm-2 and had a seasonal mean of 11.0 Wm-2. LE exchange rates varied between 44.2 and 56.8 Wm-2 and the seasonal mean was 49.0 Wm-2.Evapo-transpiration (ET) of wheat in the location under standard growing condition was estimated at 312 mm.However, the crop could actually evapotranspire water in the range of 187-248 mm,as measured through an eddy covariance based protocol, even though it received about 410 mm of water through irrigation and rainfall. Canopy condition were interpreted through hyperspectra based indices, viz. NDVI and LSWI which indicated atleast two instances of stress, one around maximum tillering and the other between anthesis and dough stages.Net primary production and yield during the 105 day long growing season were 558 g C m-2 and 3.3 t ha-1, respectively and the productivity gap could be minimized by addressing the major edaphic limitations, i.e. low soil volume and high seepage losses. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]