Impact of Future Climate Change on Wheat Production: A Simulated Case for China’s Wheat System

The impact of intra-annual temperature fluctuations on agricultural temperature extreme events and attribution analysis in mainland China

Daily temperature variations, which tend to exhibit non-constant and non-linear patterns, are often characterized by intra-annual fluctuations that cause severe and frequent extreme temperature events that have an enormous impact on agricultural production. However, the quantitative relationship between intra-annual temperature fluctuations and extreme agricultural temperatures remains unclear. We aimed to investigate intra-annual temperature fluctuation changes based on daily meteorological data in nine agricultural regions across China from 1960 to 2022 and quantify the impact of temperature fluctuations on extreme agricultural temperatures during crop growth periods. Moreover, an attribution analysis of intra-annual temperature fluctuations was performed using climate indicators. Main results showed: (1) intra-annual temperature fluctuations in each region exhibited a certain decrease, and the spatial distribution showed a significant decreasing trend from north to south. (2) Intra-annual temperature fluctuations have moderately exacerbated extreme agricultural hot and cold events during growth periods, which have brought serious challenges to agriculture owing to advances in phenology and unsynchronized rain heat compared to climate warming. The proportion of positive correlations between temperature fluctuations and extreme temperatures was much larger than that of the negative correlations in nearly all of China (percentage of stations: 20.5 %), and the negative correlation was concentrated only in southern China (percentage of stations: 3.7 %). (3) Hydrothermal coupling and elevation moderately affected intra-annual temperature fluctuations. Average temperature, relative humidity, and elevation had negative correlations with intra-annual temperature fluctuations, the correlation coefficients (R) were - 0.62, -0.42 and - 0.12, respectively; however, reference crop evapotranspiration (ET0) exhibited a positive correlation (R: 0.29), and all reached highly significant levels (P < 0.01). Climate indicators mainly affected intra-annual temperature fluctuations in eastern China. Specifically, the El Niño-Southern Oscillation (ENSO), unstable Asia Polar Vortex, and increased Western Pacific Subtropical High have enhanced temperature fluctuations. The deepened East Asian Trough and Arctic Oscillation of the negative phase weakened the intra-annual temperature fluctuations. This investigation highlights the crucial function of temperature fluctuation in intensifying extreme temperature occurrences and provides a more reasonable scientific foundation for extreme event prediction and agricultural planning.

Modelling nitrogen management in hybrid rice for coastal ecosystem of West Bengal, India

Hybrid rice requires adequate nitrogen (N) management in order to achieve good yields from its vegetative and reproductive development. With this backdrop, a field experiment was conducted at Regional Research Station (Coastal Saline Zone), Bidhan Chandra Krishi Viswavidyalaya, Kakdwip, West Bengal (India) to record growth and yield performance of hybrid rice (cv. PAN 2423) under varied N-fertilizer doses. A modelling approach was adopted for the first time in hybrid rice production system under coastal ecosystem of West Bengal (India). In the present study, the Agricultural Production Systems Simulator (APSIM) model was calibrated and validated for simulating a hybrid rice production system with different N rates. The APSIM based crop simulation model was found to capture the physiological changes of hybrid rice under varied N rates effectively. While studying the relationship between simulated and observed yield data, we observed that the equations developed by APSIM were significant with higher R² values (≥0.812). However, APSIM caused an over-estimation for calibrate data but it was rectified for validated data. The RMSE of models for all the cases was less than respective SD values and the normalized RMSE values were ≤20%. Hence, it was proved to be a good rationalized modelling and the performance of APSIM was robust. On the contrary, APSIM underestimated the calibrated amount of N (kg ha^-1) in storage organ of hybrid rice, which was later rectified in case of validated data. A strong correlation existed between the observed and APSIM-simulated amounts of N in storage organ of hybrid rice (R² = 0.94** and 0.96** for the calibration and validation data sets, respectively), which indicates the robustness of the APSIM simulation study. Scenario analysis also suggests that the optimal N rate will increase from 160 to 200 kg N ha^-1 for the greatest hybrid rice production in coming years under elevated CO₂ levels in the atmosphere. The APSIM-Oryza crop model had successfully predicted the variation in aboveground biomass and grain yield of hybrid rice under different climatic conditions.

Alfalfa-grass mixtures reduce greenhouse gas emissions and net global warming potential while maintaining yield advantages over monocultures

Improving forage productivity with lower greenhouse gas (GHG) emissions from limited grassland has been a hotspot of interest in global agricultural production. In this study, we analyzed the effects of grasses (tall fescue, smooth bromegrass), legume (alfalfa), and alfalfa-grass (alfalfa + smooth bromegrass and alfalfa + tall fescue) mixtures on GHG emissions, net global warming potential (Net GWP), yield-based greenhouse gas intensity (GHGI), soil chemical properties and forage productivity in cultivated grassland in northwest China during 2020-2021. Our results demonstrated that alfalfa-grass mixtures significantly improved forage productivity. The highest total dry matter yield (DMY) during 2020 and 2021 was obtained from alfalfa-tall fescue (11,311 and 13,338 kg ha^-1) and alfalfa-smooth bromegrass mixtures (10,781 and 12,467 kg ha^-1). The annual cumulative GHG emissions from mixtures were lower than alfalfa monoculture. Alfalfa-grass mixtures significantly reduced GHGI compared with the grass or alfalfa monocultures. Furthermore, results indicated that grass, alfalfa and alfalfa-grass mixtures differentially affected soil chemical properties. Lower soil pH and C/N ratio were recorded in alfalfa monoculture. Alfalfa and mixtures increased soil organic carbon (SOC) and soil total nitrogen (STN) contents. Importantly, alfalfa-grass mixtures are necessary for improving forage productivity and mitigating the GHG emissions in this region. In conclusion, the alfalfa-tall fescue mixture lowered net GWP and GHGI in cultivated grassland while maintaining high forage productivity. These advanced agricultural practices could contribute to the development of climate-sustainable grassland production in China.

Assessing the sensitivity of alfalfa yield potential to climate impact under future scenarios in Iran

Alfalfa is a major forage crop in Iran. To quantify the impact of climate change on its yield and water application for irrigation in Iran, the SSM-iCrop2 simulation model and two GCMs of IPSL and HadGEM were used under RCP4.5 and RCP8.5 for the 2050s. Despite increased temperatures, alfalfa forage yield will increase in most of the regions across the country due to acceleration of spring regrowth, a higher number of cuttings, increased incident and received photosynthetically active radiation because of increased growing season length due to increased temperatures, and positive effect of CO₂ on photosynthesis and radiation use efficiency. Changes in climatic conditions have had a significant impact on alfalfa net irrigation water, and the sum of net irrigation water has a direct relationship with alfalfa yield. Due to increased temperature, changes in rainfall, and improved concentration of atmospheric CO₂, the forage yield of alfalfa will fluctuate highly under all climatic scenarios. The highest increase and decrease in the average yield using the HadGEM model under RCP8.5 was 32 and - 33%, respectively. The average net irrigation water of alfalfa increased by 36% in the HadGEM model under RCP8.5 and decreased by - 41% in the IPSL model under RCP8.5. Therefore, to improve alfalfa yield in Iran in the future, strategies compatible such as high temperature-tolerant cultivars may be the most reasonable approaches.

Modeling the Impact of Future Climate Change Impacts on Rainfed Durum Wheat Production in Algeria

The predicted climate change threatens food security in the coming years in Algeria. So, this study aims to assess the impact of future climate change on a key crop in Algeria which is rainfed durum wheat. We investigate the impact of climate change on rainfed durum wheat cultivar called Mexicali using AquaCrop crop model and the EURO-CORDEX climate projections downscaled with the ICHEC_KNMI model under RCP 4.5 and RCP 8.5. A delta method was applied to correct the incertitudes present in the raw climate projections of two experimental sites located in Sétif and Bordj Bou Arreridj (BBA)’s Eastern High plains of Algeria (EHPs). AquaCrop was validated with a good precision (RMSE = 0.41 tha−1) to simulate Mexicali cultivar yields. In 2035–2064, it is expected at both sites: an average wheat grain yield enhances of +49% and +105% under RCP 4.5 and RCP 8.5, respectively, compared to the average yield of the baseline period (1981–2010), estimated at 29 qha−1. In both sites, in 2035–2064, under RCP 4.5 and RCP 8.5, the CO2 concentrations elevation has a fertilizing effect on rainfed wheat yield. This effect compensates for the negative impacts induced by the temperatures increase and decline in precipitation and net solar radiation. An increase in wheat water productivity is predicted under both RCPs scenarios. That is due to the water loss drop induced by the shortening of the wheat-growing cycle length by the effect of temperatures increase. In 2035–2064, early sowing in mid-September and October will lead to wheat yields improvement, as it will allow the wheat plant to benefit from the precipitations increase through the fall season. Thus, this early sowing will ensure a well vegetative development and will allow the wheat’s flowering and grain filling before the spring warming period.

Simulation of Wheat Response to Future Climate Change Based on Coupled Model Inter-Comparison Project Phase 6 Multi-Model Ensemble Projections in the North China Plain

Global climate change results in more extreme temperature events, which poses a serious threat to wheat production in the North China Plain (NCP). Assessing the potential impact of temperature extremes on crop growth and yield is an important prerequisite for exploring crop adaptation measures to deal with changing climate. In this study, we evaluated the effects of heat and frost stress during wheat sensitive period on grain yield at four representative sites over the NCP using Agricultural Production System Simulator (APSIM)-wheat model driven by the climate projections from 20 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) during two future periods of 2031-2060 (2040S) and 2071-2100 (2080S) under societal development pathway (SSP) 245 and SSP585 scenarios. We found that extreme temperature stress had significantly negative impacts on wheat yield. However, increased rainfall and the elevated atmospheric CO₂ concentration could partly compensate for the yield loss caused by extreme temperature events. Under future climate scenarios, the risk of exposure to heat stress around flowering had no great change but frost risk in spring increased slightly mainly due to warming climate accelerating wheat development and advancing the flowering time to a cooler period of growing season. Wheat yield loss caused by heat and frost stress increased by -0.6 to 4.2 and 1.9-12.8% under SSP585_2080S, respectively. We also found that late sowing and selecting cultivars with a long vegetative growth phase (VGP) could significantly compensate for the negative impact of extreme temperature on wheat yields in the south of NCP. However, selecting heat resistant cultivars in the north NCP and both heat and frost resistant cultivars in the central NCP may be a more effective way to alleviate the negative effect of extreme temperature on wheat yields. Our findings showed that not only heat risk should be concerned under climate warming, but also frost risk should not be ignored.

Assessment of the response of climate variability and price anomalies to grain yield and land use in Northeast China

Evidence revealed that climate change has a significant impact on grain production in China. Northeast China has abundant agricultural resources which can make the maximum contribution to national food security. This study examines the effects of climate variability and price anomalies on grain yield and land use in Northeast China. The analysis showed that different climate variability phase combinations based on Pacific Decadal Oscillation and North Atlantic Oscillation present variations in signals and different magnitude of effects over the study area. The results revealed that land use by total grain crop negatively responds to the increase in price anomalies in Heilongjiang and Jilin Provinces. To assess the impact of climate change on crop yield model, the yield models under dynamically downscaled regional climate models revealed that climate variables significantly contribute to total grain yields. In the near future, minimum temperature (- 0.26 °C under CanESM2-4.5, - 4.42 °C under HadGEM2-ES), maximum temperature (- 2.82 °C under CanESM2-4.5, - 0.84 under HadGEM2-ES), and precipitation (ranged from 3.59 to 11.10%) positively contribute to total grain yields under both models. Overall, analysis showed that climate change has a significant contribution to grain production. In conclusion, the implications for future research and policymakers have been addressed. Particularly, the importance of considering regional differences in adaptation planning in agricultural regions was also considered.

Climate change impact assessment on Northeast China's grain production

The international community is paying more attention to climate change because a consensus has been reached that climate change has an adverse effect not only on the environment but also on agriculture. Therefore, in this study, present and future climate datasets (obtained from general circulation models) including atmospheric carbon concentration were used to assess the impact of climate change on grain production for an important base of China (Northeast). An empirical model has been developed using climate and other additional variables (effective irrigation area, fertilizer, and labor force) to assess the effect of climate change on grain production. The results revealed that maximum temperature is a key climate determinant in grain production of the study area. Atmospheric carbon concentration showed a significant impact on grain outputs in most of the cases. During the analysis, it was observed that precipitation displayed a declining trend while an effective irrigation area showed positive non-significant contribution to grain production. Analysis based on different representative concentration pathways exhibited that maximum temperature may contribute negatively to grain production in the future. Overall, the analysis showed that climate change has a significant contribution to grain production. In conclusion, the implications for future research and policymakers have been addressed. Particularly, the importance of considering regional differences in adaptation planning in agricultural regions was also considered.

Rising Atmospheric Temperature Impact on Wheat and Thermotolerance Strategies

Temperature across the globe is increasing continuously at the rate of 0.15–0.17 °C per decade since the industrial revolution. It is influencing agricultural crop productivity. Therefore, thermotolerance strategies are needed to have sustainability in crop yield under higher temperature. However, improving thermotolerance in the crop is a challenging task for crop scientists. Therefore, this review work was conducted with the aim of providing information on the wheat response in three research areas, i.e., physiology, breeding, and advances in genetics, which could assist the researchers in improving thermotolerance. The optimum temperature for wheat growth at the heading, anthesis, and grain filling duration is 16 ± 2.3 °C, 23 ± 1.75 °C, and 26 ± 1.53 °C, respectively. The high temperature adversely influences the crop phenology, growth, and development. The pre-anthesis high temperature retards the pollen viability, seed formation, and embryo development. The post-anthesis high temperature declines the starch granules accumulation, stem reserve carbohydrates, and translocation of photosynthates into grains. A high temperature above 40 °C inhibits the photosynthesis by damaging the photosystem-II, electron transport chain, and photosystem-I. Our review work highlighted that genotypes which can maintain a higher accumulation of proline, glycine betaine, expression of heat shock proteins, stay green and antioxidant enzymes activity viz., catalase, peroxidase, super oxide dismutase, and glutathione reductase can tolerate high temperature efficiently through sustaining cellular physiology. Similarly, the pre-anthesis acclimation with heat treatment, inorganic fertilizer such as nitrogen, potassium nitrate and potassium chloride, mulches with rice husk, early sowing, presoaking of a 6.6 mM solution of thiourea, foliar application of 50 ppm dithiothreitol, 10 mg per kg of silicon at heading and zinc ameliorate the crop against the high temperature. Finally, it has been suggested that modern genomics and omics techniques should be used to develop thermotolerance in wheat.

The shifting influence of future water and temperature stress on the optimal flowering period for wheat in Western Australia

An optimal flowering period (OFP) minimises the long-term combined risk of extreme weather events on crop yield and exists in all environments. With climate change, the frequency, timing and intensity of these events are likely to change, which in turn may shift the OFP. It is important to explore how the OFP would change under a future climate. Knowledge of the OFP is important for formulating breeding strategies and developing suitable varieties. Here, a simulation analysis was conducted at 4 sites in Western Australia to quantify any shift in the OFP due to climate change, by accounting for the effects of frost, heat and water stress on wheat yield. Three global climate models that projected the greatest precipitation decrease under the Representative Concentration Pathways 8.5 during 2061-2100 were ensembled to represent a dry future climate condition (dry scenario); and 3 models that predicted the smallest decrease in precipitation were ensembled to represent a wet future climate condition (wet scenario). The simulation results predicted that the timing of OFPs for wheat in Western Australia would occur earlier than the current OFP. On average the OFP was 29 days earlier in the dry scenario and 11 days earlier in the wet scenario. Early sowing of long-season varieties would be preferable to achieve the OFP in both climate scenarios due to greater yield potential. Early sowing opportunities were very limited under the dry scenario, and therefore fast maturing varieties for late sowing would also be necessary.

Combining QTL Analysis and Genomic Predictions for Four Durum Wheat Populations Under Drought Conditions

Durum wheat is an important crop for the human diet and its consumption is gaining popularity. In order to ensure that durum wheat production maintains the pace with the increase in demand, it is necessary to raise productivity by approximately 1.5% per year. To deliver this level of annual genetic gain the incorporation of molecular strategies has been proposed as a key solution. Here, four RILs populations were used to conduct QTL discovery for grain yield (GY) and 1,000 kernel weight (TKW). A total of 576 individuals were sown at three locations in Morocco and one in Lebanon. These individuals were genotyped by sequencing with 3,202 high-confidence polymorphic markers, to derive a consensus genetic map of 2,705.7 cM, which was used to impute any missing data. Six QTLs were found to be associated with GY and independent from flowering time on chromosomes 2B, 4A, 5B, 7A and 7B, explaining a phenotypic variation (PV) ranging from 4.3 to 13.4%. The same populations were used to train genomic prediction models incorporating the relationship matrix, the genotype by environment interaction, and marker by environment interaction, to reveal significant advantages for models incorporating the marker effect. Using training populations (TP) in full sibs relationships with the validation population (VP) was shown to be the only effective strategy, with accuracies reaching 0.35–0.47 for GY. Reducing the number of markers to 10% of the whole set, and the TP size to 20% resulted in non-significant changes in accuracies. The QTLs identified were also incorporated in the models as fixed effects, showing significant accuracy gain for all four populations. Our results confirm that the prediction accuracy depends considerably on the relatedness between TP and VP, but not on the number of markers and size of TP used. Furthermore, feeding the model with information on markers associated with QTLs increased the overall accuracy.

Technological Quality and Nutritional Value of Two Durum Wheat Varieties Depend on Both Genetic and Environmental Factors

Durum wheat ( Triticum turgidum L. subsp. durum (Desf.) Husn) is a major food source in Mediterranean countries since it is utilized for the production of pasta, leavened and unleavened breads, couscous, and other traditional foods. The technological and nutritional properties of durum wheat semolina depend mainly on the type of gluten proteins and on their amount, which is a genotype- and environment-dependent trait. Gluten proteins are also responsible for celiac disease (CD), an autoimmune enteropathy with a prevalence of about 0.7-2% in the human population. At this purpose, two Italian durum wheat cultivars, Saragolla and Cappelli, currently used for monovarietal pasta, were chosen to compare (i) the reserve and embryo proteome, (ii) the free and bound phenolics, antioxidant activity, and amino acid composition, and (iii) the content of immunogenic peptides produced after a simulated gastrointestinal digestion. The results obtained from 2 years of field cultivation on average showed a higher amount of gluten proteins, amino acids, and immunogenic peptides in Cappelli. Saragolla showed a higher abundance in bound phenolics, antioxidant enzymes, and stress response proteins in line with its higher antioxidant activity. However, the impact of the year of cultivation, largely depending on varying rainfall regimes through the wheat growth cycle, was significant for most of the parameters investigated. Differences in technological and nutritional characteristics observed between the two cultivars are discussed in relation to the influence of genetic and environmental factors.