Climate Change Impact on Agriculture and Food Security

Research on the impact of climate change on agriculture and food security is important, especially in the agricultural economies, not only to know the severity of impact but also the policies to be adapted to halt climate change and the technology to be used to mitigate the impact of climate change. The study was conducted in Kapiri Mposhi district of Central Province in Zambia to find out the impact of climate change on agriculture and food security. The objectives of study include to know the intensity of climate change and its impact on area under cultivation, late sowing of seed and damage of seed due to lack of water, fertilizer absorption reduction, food shortage, livestock, and productivity. The chapter also focuses on the sources of credit to the farmers.

Adaptation Potential of Current Wheat Cultivars and Planting Dates under the Changing Climate in Ethiopia

Global warming poses a severe threat to food security in developing countries. In Ethiopia, the primary driver of low wheat productivity is attributed to climate change. Due to the sparsity of observation data, climate-related impact analysis is poorly understood, and the adaptation strategies studied so far have also been insufficient. This study adopted the most popular DSSAT CERES-Wheat model and the ensemble mean of four GCMs to examine the quantitative effects of adjusted sowing dates and varieties on wheat yield. The two new cultivars (Dandaa and Kakaba), with reference to an old cultivar (Digelu), were considered for the mid-century (2036–2065) and late-century (2066–2095) under RCP 4.5 and RCP 8.5 climate scenarios. The results showed that the Dandaa cultivar demonstrates better adaptation potential at late sowing with a yield increase of about 140 kg/ha to 148 kg/ha for the mid- and late-century under RCP4.5. However, under RCP 8.5, Kakaba demonstrates higher adaptation potential with a yield gain for early sowing of up to 142 kg/ha and 170 kg/ha during the mid- and late-century, respectively. Late sowing of the Dandaa cultivar is recommended if GHG emissions are cut off at least to the average scenario, while the Kakaba cultivar is the best option when the emissions are high. The adaptation measures assessed in this study could help to enhance wheat production and adaptability of wheat to the future climate.

Performance Evaluation of the WOFOST Model for Estimating Evapotranspiration, Soil Water Content, Grain Yield and Total Above-Ground Biomass of Winter Wheat in Tensift Al Haouz (Morocco): Application to Yield Gap Estimation

The main goal of this investigation was to evaluate the potential of the WOFOST model for estimating leaf area index (LAI), actual evapotranspiration (ETa), soil moisture content (SM), above-ground biomass levels (TAGP) and grain yield (TWSO) of winter wheat in the semi-arid region of Tensift Al Haouz, Marrakech (central Morocco). An application for the estimation of the Yield Gap is also provided. The model was firstly calibrated based on three fields data during the 2002–2003 and 2003–2004 growing seasons, by using the WOFOST implementation in the Python Crop simulation Environment (PCSE) to optimize the different parameters that provide the minimum difference between the measured and simulated LAI, TAGP, TWSO, SM and ETa. Then, the model validation was performed based on the data from five other wheat fields. The results obtained showed a good performance of the WOFOST model for the estimation of LAI during both growing seasons on all validation fields. The average R2, RSME and NRMSE were 91.4%, 0.57 m2/m2, and 41.4%, respectively. The simulated ETa dynamics also showed a good agreement with the observations by eddy covariance systems. Values of 60% and 72% for R2, 0.8 mm and 0.7 mm for RMSE, 54% and 31% for NRMSE are found for the two validation fields, respectively. The model’s ability to predict soil moisture content was also found to be satisfactory; the two validation fields gave R2 values equal to 48% and 49%, RMSE values equal to 0.03 cm3/cm3 and 0.05 cm3/cm3, NRMSE values equal to 11% and 19%. The calibrated model had a medium performance with respect to the simulation of TWSO (R2 = 42%, RSME = 512 kg/ha, NRMSE = 19%) and TAGP (R2 = 34% and RSME = 936 kg/ha, NRMSE = 16%). After accurate calibration and validation of the WOFOST model, it was used for analyzing the gap yield since this model is able to estimate the potential yield. The WOFOST model allowed a good simulation of the potential yield (7.75 t/ha) which is close to the optimum value of 6.270 t/ha in the region. Yield gap analysis reveals a difference of 5.35 t/ha on average between the observed yields and the potential yields calculated by WOFOST. Such difference is ascribable to many factors such as the crop cycle management, agricultural practices such as water and fertilization supply levels, etc. The various simulations (irrigation scenarios) showed that early sowing is more adequate than late sowing in saving water and obtaining adequate grain yield. Based on various simulations, it has been shown that the early sowing (mid to late December) is more adequate than late sowing with a total amount of water supply of about 430 mm and 322 kg (140 kg of N, 80 kg of P and 102 kg of K) of fertilization to achieve the potential yield. Consequently, the WOFOST model can be considered as a suitable tool for quantitative monitoring of winter wheat growth in the arid and semi-arid regions.

Impact assessment of climate change on groundnut yield of middle Gujarat region

The impact of projected climate change on groundnut (cv. Robut 33-1 and GG-2) yield have been studied for Anand station of middle Gujarat Agro-climatic region using PRECIS output of A2 scenario and base line data. Yield simulation study was performed by PNUTGRO (DSSAT v4.5) model. The field experiment data on groundnut cv. Robut 33-1 and GG-2 during the years 2008 to 2011 have been used to calibrate and validate the model. The weather condition as projected by A2 scenario (2070-2100) showed that there will be 13.7% higher rainfall as compared to base line (1961-90). The mean maximum and minimum temperature will be higher to the tune of 3.6 and 5.1 °C as compared to their base temperature of 19.1 and 29.8 °C respectively. Nearly 21 and 31% pod yield reduction was noted in Robut 33-1 and GG-2 as compared to their base yield during projected period. Highest yield reduction was recorded in late sowing (15th July) and cv. GG-2 and lowest yield reduction was noted in timely sowing (D1) and cv. Robut 33-1. Under projected period. 7.0 to 16.0% yield benefited by adaptation strategies, viz, fifteen days earlier shifting of sowing with one pre sowing irrigation and Application of organic manure instead of chemical fertilizer.

Simulation modeling of rice genotypes of yield and yield attributes at different nitrogen levels and different dates of transplanting using CERES 3.5 v for eastern Uttar Pradesh

The present investigation was carried out at Agrometeorological Instructional Farm of Narendra Deva University of Agriculture & Technology, Kumarganj, Faizabad (U.P.) during Kharif season of 2005-06 to investigate the CERES v 3.5 model validations for rice at different dates of transplanting and different genotypes. Treatment consisted of three genotypes, viz., Sarjoo-52, NDR-359 and Pant Dhan-4, two dates of transplanting, viz., July 5, 2005 and July 25, 2005 & three nitrogen levels, viz., 80 kg/ha, 120 kg/ha and 160 kg/ha. The experiment was laid out in Randomized Block Design (RBD). From the response of simulation model it is observed that accuracy of simulated value decrease with late sowing in all the genotypes. Among the varieties the Pant Dhan-4 was found to have maximum closeness to observed value followed by Sarjoo-52 and NDR-359 at all nitrogen level for Biomass (gm/m2). Grain yield predication at 120 kg N level was found closest in Pant Dhan-4 and Sarjoo-52, while in NDR­-359 shows the better closeness at 160 kg N in both dates of transplanting. In the weight/grain (gm) 120 kg nitrogen level was found to have highest accuracy of (100%), i.e., no difference between observed and predicted value in both transplanting dates and nitrogen level.

Exogenous application of moringa leaf extract improves growth, biochemical attributes, and productivity of late-sown quinoa

Quinoa (Chenopodium quinoa Willd.) has gained significant popularity among agricultural scientists and farmers throughout the world due to its high nutritive value. It is cultivated under a range of soil and climatic conditions; however, late sowing adversely affects its productivity and yield due to shorter growth period. Inorganic and organic phyto-stimulants are promising for improving growth, development, and yield of field crops under stressful environments. Field experiments were conducted during crop cultivation seasons of 2016–17 and 2017–18, to explore the role of inorganic (hydrogen peroxide and ascorbic acid) and organic [moringa leaf extract (MLE) and sorghum water extract (sorgaab)] phyto-stimulants in improving growth and productivity of quinoa (cultivar UAF-Q7). Hydrogen peroxide at 100 μM, ascorbic acid at 500 μM, MLE at 3% and sorgaab at 3% were exogenously applied at anthesis stage of quinoa cultivated under normal (November 21st and 19th during 2016 and 2017) and late-sown (December 26th and 25th during 2016 and 2017) conditions. Application of inorganic and organic phyto-stimulants significantly improved biochemical, physiological, growth and yield attributes of quinoa under late sown conditions. The highest improvement in these traits was recorded for MLE. Application of MLE resulted in higher chlorophyll a and b contents, stomatal conductance, and sub-stomatal concentration of CO2 under normal and late-sowing. The highest improvement in soluble phenolics, anthocyanins, free amino acids and proline, and mineral elements in roots, shoot and grains were observed for MLE application. Growth attributes, including plant height, plant fresh weight and panicle length were significantly improved with MLE application as compared to the rest of the treatments. The highest 1000-grain weight and grain yield per plant were noted for MLE application under normal and late-sowing. These findings depict that MLE has extensive crop growth promoting potential through improving physiological and biochemical activities. Hence, MLE can be applied to improve growth and productivity of quinoa under normal and late-sown conditions.

Performance and yield stability of doubled haploid population of wheat (Triticum aestivum L.) under high temperature regime.

India, the second most populated country and the largest wheat producer worldwide, is vulnerable to global warming especially heat stress. In the present investigation, the doubled haploid population derived from PBW343/IC252478 cross was characterized for various phenotypic and morpho-physiological traits and subjected to stability analysis under heat stress conditions. These lines were planted on a single location i.e., Agricultural farm of Rajendra Prasad Central Agricultural University, India for two successive seasons 2017/2018 and, 2018/2019 under three different sowing dates (Controlled or timely, late and, very late sown conditions). Here, the location preferred for this study was because it represents a hotspot for wheat production and the major constraint for the wheat grower is inclining heat stress. The alpha lattice design was used for the current investigation with three replicates. The overall objective of this study was to identify the ideal double haploid lines for heat-stressed conditions. The results revealed that heat stress had a significant adverse impact on all considered traits contributed to overall yield losses of about 50%. Stability measurements, and genotype × environment interaction (GGE), were useful tools to determine the ideal lines for late sowing (heat stressed condition) and very late sowing condition (terminal heat stress). Therefore, in the ranking of genotypes for both mean yield and stability performance across the six environments, DH 71, DH 150, DH 64, DH 138, DH 98, DH 84, DH 62, DH 104, DH 74, DH 3, DH 104, DH 107 & DH 156 were ranked closest to ideal genotype, these were highly adapted, most stable, heat tolerant and high yielding lines indicating them as the most desirable genotypes out of 167 lines studied. Hence, the physiological traits SPAD index (Soil plant analysis development) and Canopy temperature (CT) can be used effectively to screen out the line for heat tolerance. In addition, the stable wheat genotypes identified could be used in the future wheat breeding programs.