Mitigation of nitrous oxide emission through fertigation and ‘N’ inhibitors – A sustainable climatic crop cultivation in tomato

The Impact of Climate Change on Groundwater and Crop Yield in Asia: A Comprehensive Review

“…The temperate climate zone continues to shift towards higher latitudes due to global climate change, which affect the distribution of climate suitability of major crops in Asia like rice, cotton, wheat and maize. [10]. According to the research study [41] on the impact of climate change on cotton yield in the region of Xingiang, China, based on one-sided suitability assessments, leading to potential biases when optimizing cotton planting spatial distribution and adaptability.…”

“…Due to climate change and excessive groundwater extraction, groundwater-related issues have resulted in saltwater intrusion into coastal aquifers and groundwater-related problems in several low-lying countries [4,5]. Climate change has led to a declining number of extreme cold events [6] together with an increase in the number of heatwaves [7], droughts, and excessive rainfall [8][9][10] that can significantly impact global food production [11]. Crop models are commonly used to develop effective adaptation strategies for maintaining stable grain production under future climate change.…”

“…Machine learning algorithms can incorporate indices such as ECEs and CPDs, as well as genotype by management by environment interactions, and may require less parameterization compared to process-based models. Numerous studies have utilized machine learning or deep learning algorithms [12][13][14][15][16][17][18][19][20][21][22], to forecast groundwater level and crop yield with satisfactory performance [8][9][10][11]. Yang et al [23] trained CNN with high-resolution UAV images to predict the yield of rice, and the results obtained were far better than the statistical model based on vegetation index, whereas [24,25] used the convolutional LSTM to predict the variation of meteorological factors and then predicted the growth stage of crops.…”

“…Diverse combinations of factors that impact the daily uptake of nitrate such as potential crop evapotranspiration, irrigation water, and the quantity of injected fertilizer were examined as inputs for the model. In [10], the five innovative hybrid algorithms: Ant, Firefly, MOE, GWO, and Particle Swarm Optimization (PSO) were integrated with the random forest (RF) algorithm for the purpose of mapping groundwater nitrate concentrations in the coastal multi-aquifers of the Mekong Delta.…”