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Background: The severity and frequency of drought are expected to increase substantially in the coming century and dramatically reduce crop yields. Manipulation of rhizosphere microbiomes is an emerging strategy for mitigating drought stress in agroecosystems. However, little is known about the mechanisms underlying how drought-resistant plant recruitment of specific rhizosphere fungi enhances drought adaptation of drought-sensitive wheats. Here, we investigated microbial community assembly features and functional profiles of rhizosphere microbiomes related to drought-resistant and drought-sensitive wheats by amplicon and shotgun metagenome sequencing techniques. We then established evident linkages between root morphology traits and putative keystone taxa based on microbial inoculation experiments. Furthermore, root RNA sequencing and RT-qPCR were employed to explore the mechanisms how rhizosphere microbes modify plant response traits to drought stresses. Results: Our results indicated that host plant signature, plant niche compartment, and planting site jointly contribute to the variation of soil microbiome assembly and functional adaptation, with a relatively greater effect of host plant signature observed for the rhizosphere fungi community. Importantly, drought-resistant wheat (Yunhan 618) possessed more diverse bacterial and fungal taxa than that of the drought-sensitive wheat (Chinese Spring), particularly for specific fungal species. In terms of microbial interkingdom association networks, the drought-resistant variety possessed more complex microbial networks. Metagenomics analyses further suggested that the enriched rhizosphere microbiomes belonging to the drought-resistant cultivar had a higher investment in energy metabolism, particularly in carbon cycling, that shaped their distinctive drought tolerance via the mediation of drought-induced feedback functional pathways. Furthermore, we observed that host plant signature drives the differentiation in the ecological role of the cultivable fungal species Mortierella alpine (M. alpina) and Epicoccum nigrum (E. nigrum). The successful colonization of M. alpina on the root surface enhanced the resistance of wheats in response to drought stresses via activation of drought-responsive genes (e.g., CIPK9 and PP2C30). Notably, we found that lateral roots and root hairs were significantly suppressed by co-colonization of a drought-enriched fungus (M. alpina) and a drought-depleted fungus (E. nigrum). Conclusions: Collectively, our findings revealed host genotypes profoundly influence rhizosphere microbiome assembly and functional adaptation, as well as it provides evidence that drought-resistant plant recruitment of specific rhizosphere fungi enhances drought tolerance of drought-sensitive wheats. These findings significantly underpin our understanding of the complex feedbacks between plants and microbes during drought, and lay a foundation for steering "beneficial keystone biome" to develop more resilient and productive crops under climate change. FGv_ocsEwwAXXw4e-N4Vhr Video Abstract [ABSTRACT FROM AUTHOR]

Climate change and variability are projected to alter the geographic suitability of lands for crops cultivation. Accurately predicting changes in the potential current and future land suitability distribution dynamics of wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) crops due to climate change scenarios is critical to adapting and mitigating the impacts of bioclimatic changes, and plays a significant role in securing food security in East Asia region. This study compiled large datasets of wheat, soybean and rice occurrence locations from GBIF and 19 bioclimatic variables obtained from the WorldClim database that affect crops growth. We recognized potential future suitable distribution regions for crops under the one socioeconomic pathway, (SSP585) for 2021–2040 and 2041–2060, using the MaxEnt model. The accuracy of the MaxEnt was highly significant with mean AUC values ranging from 0.833 to 0.882 for all models evaluated. The jackknife test revealed that for wheat, Bio4 and Bio12 contributed 17.6% and 12.6%, for soybean Bio10 and Bio12 contributed 15.6% and 49.5%, while for rice Bio12 and Bio14 contributed 12.9% and 36.0% to the MaxEnt model. In addition, cultivation aptitude for wheat, soybean, and rice increased in southeast China, North Korea, South Korea, and Japan, while decreasing in Mongolia and northwest China. Climate change is expected to increase the high land suitability for wheat, soybean, and rice in East Asia. Simulation results indicate an average decrease of unsuitable areas of -98.5%, -41.2% and -36.3% for wheat, soybean and rice from 2060 than that of current land suitability. In contrast, the high land suitable for wheat, soybean and rice cultivation is projected to increase by 75.1%, 68.5% and 81.9% from 2060 as compared with current. The findings of this study are of utmost importance in the East Asia region as they present an opportunity for policy makers to develop appropriate adaptation and mitigation strategies required to sustain crops distribution under future climates. Although the risks of wheat, soybean and rice cultivation may be significantly higher in the future because of high temperatures, heat waves, and droughts caused by climate change. [ABSTRACT FROM AUTHOR]

Increasing phosphorus (P) fertiliser use efficiency (PUE) is essential for addressing global nutrition security, food production costs, and environmental pollution. However, a myriad of soil × climate × crop × management interactions control PUE and adaptive tools are needed to put this complexity into context at the field scale. We conducted a Morris global sensitivity analysis on an evaluated agricultural system model (APSIM) across 132 years of climate data to identify important drivers of PUE in a subtropical dryland cropping system. We selected soil, crop, and management parameters to understand their influence on yield, biomass, and grain P export as measures of PUE in a subtropical wheat crop. We then examined three P fertility scenarios ranging from low to high (10, 40, 70 mg available P kg−1 at 0–10 cm, with subsoils to 180 cm at 9–10 mg available P kg−1) resulting in 1,782,000 simulations. In scenarios with medium or high P fertility and higher in-crop rainfall (> 200 mm), nitrogen (N) fertiliser was the most important driver for increasing yield and associated PUE. At low P fertility and lower in-crop rainfall (< 200 mm), P fertiliser and P sorption isotherm parameters were the most important drivers. This highlighted potential constraints to PUE analysis in the region if rainfall data is not available, and to modelling activities if P isotherm data is not available. Our study is the first to use a Morris global sensitivity analysis method for defining the influence of N and P fertiliser, and in-crop rainfall, as short-term (year–year) drivers of PUE. This method may be adapted to investigate emerging challenges in increasing PUE in other agricultural systems, but future research should include interactions with deep P banding, the effects of climate change, and demonstrate drivers over the longer-term (5–10 years). [ABSTRACT FROM AUTHOR]

The paper considers a problem of modeling the impact of the future climate on the yield of crops (in the example of spring wheat). The authors have analyzed the sources of climatic data and values of agrometeorological indicators for past and future periods. Using agroclimatic parameters, they have developed a mathematical model of the dependence of the median of the distribution function of spring wheat yield on climatic changes. The authors performed the calculations using this model and analyzed the obtained results. The analysis indicates a significant increase in the yield level of spring wheat in 2030–2040 and an increase in the risk of losses of its yield compared to historical data. [ABSTRACT FROM AUTHOR]

• Cd is an exceptionally toxic and extremely mobile element in both soil and plant systems. • Zn foliar application effectually enhanced wheat quality and its tolerance against Cd. • Current study will give interesting outcomes to cope with Cd contaminated soils and improving plant performance. To address food production challenges and combat heavy metal toxicity, an economically viable and sustainable approach is essential. Cadmium (Cd) contamination poses risks to crops and human health. Leveraging the structural similarity between zinc (Zn) and cadmium, we explored foliar Zn spray's potential to alleviate Cd toxicity and enhance wheat yield. Our field study near Peshawar, Pakistan, during the 2021–2022 winter, employed a split-plot design to investigate Zn's impact on wheat biofortification. Across three wheat varieties (JANBAZ-10, Pirsabak (PS)-2013, PS-2015), four foliar Zn levels (0 %, 0.5 %, 1.0 %, 1.5 % solution) were tested at various growth stages. Pirsabak-2015 exhibited optimal results, with a 1 % foliar Zn treatment producing the highest grain yield (3409 kg ha−1), biological yield (9022 kg ha−1), grains per spike (56), and 1000-grain weight (40.6 g). Application of 1 % biochar also significantly increased grain yield. Zn concentration peaked in grains and leaves with 1.5 % Zn solution, followed by 1.0 % Zn in the PS-2015 cultivar. Moreover, 1 % Zn application enhanced photosynthetic parameters and significantly reduced cadmium concentrations in leaves and grains. Notably, 1.0 % Zn led to improved stress tolerance as indicated by decreased electrolyte leakage and increased superoxide dismutase and peroxidase activities. Applying 1.0 % Zn solution as a foliar spray during different growth stages demonstrates the potential to enhance wheat yield, increase grain Zn content, and mitigate Cd toxicity in Cd-contaminated soil. Further research across diverse cereal crops and climates will help establish 1.0 % Zn foliar spray as an effective Cd stress mitigation strategy. [ABSTRACT FROM AUTHOR]

The paper presents the behaviour of some wheat varieties under the years 2014, 2016, 2018, 2019, 2020, 2023 conditions in Dobrogea area in demonstrative plots carried out at S.C. SPORT AGRA S.R.L. Amzacea, Constanta County. The main aspects emphasized in this research area have been: climatic conditions, obtained yield, and economical efficiency. Looking to the pathogens, for wheat Septoria tritici showed an AR between 17-27% and Pyrenophora graminea showed a low atack (AR = 4.5-17.5%). The pathogen Puccinia striiformis was present in low precentage (AR = 0-13.5%) in the 2018 April observations. For crop protection against pathogens, 2 foliar tratments with fungicides were applied, Artea 330 EC(ciproconazol 80 g/l + propiconazol 250 g/l) 0,4 l/ha, in March and Priaxor EC (fluxapiroxad 150 g/l + piraclostrobin 75 g/l) 1l/ha and in April respectively. Fungal treatments have stopped the development of foliar and ear diseases. The beneficial effects were found in the good yields obtained in 2014, 2016, 2018, 2019, except the years 2020 and 2023. In 2020 Otilia reached 2,370 kg/ha, Miranda 2,260 kg/ha and Solindo variety 4,297 kg/ha and Ursita 4,165 kg/ha in 2023. All these special yields have been obtained under non-irrigated conditions. [ABSTRACT FROM AUTHOR]

Advances in breeding efforts to increase the rate of genetic gains and enhance crop resilience to climate change have been limited by the procedure and costs of phenotyping methods. The recent rapid development of sensors, imageprocessing technology, and data-analysis has provided opportunities for multiple scales phenotyping methods and systems, including satellite imagery. Among these platforms, satellite imagery may represent one of the ultimate approaches to remotely monitor trials and nurseries planted in multiple locations while standardizing protocols and reducing costs. However, the deployment of satellite-based phenotyping in breeding trials has largely been limited by low spatial resolution of satellite images. The advent of a new generation of highresolution satellites may finally overcome these limitations. The SkySat constellation started offering multispectral images at a 0.5 m resolution since 2020. In this communication we present a case study on the use of time series SkySat images to estimate NDVI from wheat and maize breeding plots encompassing different sizes and spacing. We evaluated the reliability of the calculated NDVI and tested its capacity to detect seasonal changes and genotypic differences. We discuss the advantages, limitations, and perspectives of this approach for high-throughput phenotyping in breeding programs. [ABSTRACT FROM AUTHOR]

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Drought is a serious threat to agriculture particularly of rainfed regions like Potohar region of Pakistan. Wheat, staple food crop of this region, is mostly affected by drought, thereby impacting food security of the region. Effective drought monitoring and its impacts on wheat production have therefore been the key concerns of the farmers and policy makers in order to plan for any upcoming food crises in the region. A proactive drought management approach is needed in this regard. This study aims to assist the decision-making process for drought monitoring and yield predictions, as it informs drought assessment and its impacts on crop yield using drought and vegetation indices along with climate and crop yield data. This research quantifies recurrent drought events for Rubi (wheat crop) season (November–April) from 2000 to 2018 in the Potohar region using indices such as standardized precipitation index (SPI), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI) along with climatic parameters, i.e., mean temperature, rainfall and soil moisture. Results show a strong positive correlation of wheat yield with rainfall (r = 0.97) and soil moisture (r = 0.88), while a strong negative correlation with temperature (r = − 0.98). Three moderate (2000–01, 2001–02, 2009–10) and two weak (2011–12, 2017–18) drought events are identified using SPI, whereas two more drought events (2007–08 and 2016–17) are noticed when vegetation indices are used. Looking at Oceanic Niño Index (ONI), no definite pattern relating to ongoing La-Nina or El-Nino conditions during the specific drought years is observed for the Potohar region. Artificial neural network (ANN), a multilayer perception (MLP) model, is applied afterward to see the individual impact of each study parameter on wheat yield. Soil moisture is found to impact yield by 100%, temperature as 74%, rainfall as 61% and then rest of the indices. The findings of this study not only provide a scientific base for future studies on drought indicators, but assert that a cumulative approach is needed for effective drought management at national level. [ABSTRACT FROM AUTHOR]

Clarifying the spatiotemporal variation of crop irrigation water requirement (IWR) under the background of climate change is an essential basis for water resource management, determining the irrigation quota and adjusting the planting structure. Using 61 years of climate data from 205 stations in Northwest China, this study investigated the spatiotemporal variations of climatic factors and IWR during the growth period of five main grain crops (spring wheat, winter wheat, spring maize, summer maize, and rice) and explored the dominant climatic driving factors of IWR variation. Results showed that (1) the IWR of grain crops showed distinct differences. Rice was the highest water consumption crop (mean of 753.78 mm), and summer maize was the lowest (mean of 452.90 mm). (2) The variation trends and average values of IWR of different grain crops have spatial heterogeneity across Northwest China. For most crops, high values and increasing trends of IWR were mainly located in eastern Xinjiang, western Gansu, and western Inner Mongolia. (3) Tmax (maximum temperature), Tmin (minimum temperature), and Peff (effective precipitation) showed an increasing trend during the growth period of each grain crop, while U10 (wind speed at 10 m height), SD (solar radiation), and RH (relative humidity) presented decreasing trends. (4) SD, Tmax, and U10 promoted the increase of grain crops' IWR, while Peff and RH inhibited it. The impacts of climatic factors on the grain crop IWR differed among different regions. Peff was the most influential factor to the IWR of all grain crops in most areas. Therefore, under the premise of a significant increase in T and uncertain precipitation mode in the future, it is urgent to take effective water-saving measures according to the irrigation needs of the region. To cope with the adverse impact of climate change on the sustainable development of agriculture in the northwest dry area, to ensure regional and national food security. [ABSTRACT FROM AUTHOR]

This study aimed to assess the impact of climate change on spring wheat production and to provide more accurate projections by directly investigating the effect of climate change on crop development and yield. Based on ground observation data from 1981 (1986 Dingxi) to 2020 in four case areas in northwest China, and the relationships among spring wheat growth, yield, and climate factors were analyzed and determined. The results showed that the extreme arid (Dunhuang) and semiarid regions (Dingxi) tend to be warmer and wetter, whereas arid regions (Wuwei) and semihumid regions (Linxia) tend to be warmer and drier. Correlation analysis indicated that yield of spring wheat in Wuwei, Dingxi, and Linxia Stations increased significantly. The decrease in the number of days (≥30 °C) during the growth period at Wuwei resulted in a significant yield increase in the past 40 years. At Dingxi, yield increased over the last 35 years due to the significant increases in precipitation during growth, the number of grains per panicle, and thousand‐grain weight, and the decrease in infertile spikelets. Further increase in global temperature and changes in future precipitation patterns will likely affect spring wheat production in northwest China. Core Ideas: The relationship between climate factors and growth and yield of spring wheat are explored.Dominant climatic factors affecting the growth of spring wheat in different climatic regions of northwest China are studied.Regional differences in spring wheat growth and yield in response to climate change are assessed.Climate change trends in different climatic regions over time are examined.Impact of climate change on crop development and yield are assessed. [ABSTRACT FROM AUTHOR]

The accuracy prediction for the crop yield is conducive to the food security in regions and/or nations. To some extent, the prediction model for crop yields combining the crop mechanism model with statistical regression model (SRM) can improve the timeliness and robustness of the final yield prediction. In this study, the accumulated biomass (AB) simulated by the Agricultural Production Systems sIMulator (APSIM) model and multiple climate indices (e.g., climate suitability indices and extreme climate indices) were incorporated into SRM to predict the wheat yield in the North China Plain (NCP). The results showed that the prediction model based on the random forest (RF) algorithm outperformed the prediction models using other regression algorithms. The prediction for the wheat yield at SM (the period from the start of grain filling to the milky stage) based on RF can obtain a higher accuracy (r = 0.86, RMSE = 683 kg ha−1 and MAE = 498 kg ha−1). With the progression of wheat growth, the performances of yield prediction models improved gradually. The prediction of yield at FS (the period from flowering to the start of grain filling) can achieve higher precision and a longer lead time, which can be viewed as the optimum period providing the decent performance of the yield prediction and about one month's lead time. In addition, the precision of the predicted yield for the irrigated sites was higher than that for the rainfed sites. The APSIM-simulated AB had an importance of above 30% for the last three prediction events, including FIF event (the period from floral initiation to flowering), FS event (the period from flowering to the start of grain filling) and SM event (the period from the start of grain filling to the milky stage), which ranked first in the prediction model. The climate suitability indices, with a higher rank for every prediction event, played an important role in the prediction model. The winter wheat yield in the NCP was seriously affected by the low temperature events before flowering, the high temperature events after flowering and water stress. We hope that the prediction model can be used to develop adaptation strategies to mitigate the negative effects of climate change on crop productivity and provide the data support for food security. [ABSTRACT FROM AUTHOR]

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures. [ABSTRACT FROM AUTHOR]

Understanding the precipitation–yield relationships is crucial for evaluating the impacts of climate variability on crop yield. As a north–south transitional zone and major wheat-producing province in China, the Anhui was chosen for this study. Data on county-level yield, daily precipitation, and monthly large-scale atmospheric circulation indices were collected, and then 13 precipitation indices were calculated during different wheat-growing stages. The K-means clustering algorithm, trend detection analysis, Pearson correlation and stepwise regression analysis were used to reflect the variation characteristics of wheat yield and to identify crucial precipitation indices influencing climate-driven wheat yield (CDWY). The main results were as follows: (1) the wheat yield from 74 counties in Anhui was divided into three sub-regions, i.e., southern, central, and northern Anhui. (2) While wheat yield had all increasing trends in three sub-regions, a notable inter-annual fluctuation was shown for CDWY in northern Anhui, which was dominated by the quasi 7-year oscillation. (3) Total precipitation of extreme rainy days in the filling-maturation period posed significant negative impacts on CDWY for southern and northern Anhui. In contrast, the number of light rain during the same period had a critical impact on the central region. Furthermore, these crucial precipitation indices were mainly influenced by different atmospheric circulations. (4) Optimal yield prediction models were constructed based on three predictors as year, crucial precipitation indices, and corresponding atmospheric circulations for each sub-region, which had an average relative error from 8.98% to 12.58%. These findings will provide a scientific basis for understanding yield fluctuations by combining crucial precipitation indices and atmospheric circulations in Anhui. [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the growing conditions of agricultural crops. With increasing surface temperature, future suitable areas for crop production will see an altitude shift. Such shift is an adaptation response of crops to climate change. However, in the study area there are a limited number of studies that have dealt with geographical shifts of crops caused by climate change. This study was conducted with the aim of assessing impacts of climate change on altitudinal migration of crops and length of growing period (LGP). The climate and crop modeling study were carried out using ArcGIS, Diva GIS and MaxEnt using 30 years of climate data for the period 1980 to 2009. Results showed that wheat (Triticum aestivum) and barley (Hordeum vulgare L.) would migrate upward along the altitudinal gradients in the coming 80 years. However, areas under these crops are expected to drop by 16–100%. Highly impacted areas are expected to increase, whereas low impacted and new suitable areas are expected to decline significantly. Suitable areas for sorghum (Sorghum bicolor) and teff (Eragrostis tef Zucc.) production are expected to increase. While wheat and barley are projected to be highly affected by future climate change, sorghum and teff should be relatively stable. No significant difference was observed in LGP between the considered RCP 2.6 and RCP 8.5 climate scenarios. Therefore, this study concluded that upward movement of crops was one mechanism to adapt to climate change, and new varieties resilient to future climate change needs to be developed. [ABSTRACT FROM AUTHOR]

Global climate change has profound impacts on agricultural production, and it includes increasing temperature, global dimming, altered precipitation patterns, and elevated CO 2 concentration. However, the comprehensive assessment of the impact of different individual climatic factors and their interactions on crop production is relatively limited. Here we assessed the impacts of climate change and different climatic factors on winter wheat yields, interannual yield variability, and resource use efficiency in China from 1980 to 2020, with four wheat crop models (DSSAT-CERES-Wheat, DSSAT-Nwheat, WheatGrow, and APSIM-Wheat). The results showed that climate change was estimated to decrease wheat yields and increase interannual yield variability in the main winter wheat production region of China, especially in the Middle-lower Reaches of the Yangzi River Subregion, where yield reduction and the coefficient of variation increase could be 4.3 % and 30.2 %, respectively. Without considering the CO 2 effect, the primary reason for yield decrease and interannual yield variability increase was the interactions of temperature and solar radiation across the main winter wheat production region of China, and wheat yields were estimated to decrease by 9.2 % in the Southwest Subregion while the interannual yield variability increased by 49.5 % in the Middle-lower Reaches of the Yangzi River Subregion. The elevated CO 2 concentration was mostly beneficial, manifested as increasing the yield and decreasing interannual yield variability, but it could not fully offset negative impacts of climate change. Moreover, radiation use efficiency increased while heat use efficiency and precipitation use efficiency decreased during the study period. It is imperative to consider the diverse climatic factors and their respective regional impacts when adapting to climate change in China. [Display omitted] • Yield variability increased by 30 % in the Middle-lower Reaches of Yangzi River region. • Yield changes were mainly due to temperature and radiation interactions. • Elevated CO 2 failed to fully offset negative impacts of climate change. • Radiation use efficiency of wheat increased in the past decades. • Heat and precipitation use efficiency of wheat decreased in the past decades. [ABSTRACT FROM AUTHOR]

Multi-ovary wheat (three pistil) is a unique germplasm for the seed production of hybrid wheat. The purpose of the present study was to transfer the multi-ovary trait to semi-dwarf plants to increase the production of grains in wheat crops. Therefore, tall, semi-dwarf, and dwarf plants were crossed with plants with the three-pistil trait. A three-pistil tall plant was used as the female parent, while tall (Synthetic hexaploid), semi-dwarf, and dwarf plants were used as male parents. F1 and F2 progenies with parents were planted in 2015-16 using RCBD. The outcome of the crosses showed that multi-ovary tall plants gave significant difference for all five traits (days to maturity, plant height, number of seeds per spike, grain weight per spike, and grain yield per unit area) in both generations. The greatest number of grains per spike and grain yield per unit area were obtained from the cross of three-pistil tall and dwarf parent (P1/P6) in the F1 and F2 generations. The cross also resulted in a significant reduction in height (96 cm). Further heterosis studies conducted with crosses between three-pistil tall and dwarf parent (P1/P6) showed the greatest heterosis and heterobeltiosis for the number of grains per spike (60.0 and 26.19%, respectively) and grain yield per m2 (27.68 and 2.85%, respectively). In the case of grain weight per spike, the heterosis value was also positive and significant (17.7). Meanwhile, for other traits, their values were negative for heterosis and heterobeltiosis. High numbers of grains and grain weight were found to be associated with positive heterobeltiosis and in turn the grain yield per m2, but plant height and maturity had negative affirmation with heterobeltiosis. Heterosis studies also indicated the dominant gene action for the three-pistil trait. Thus, the study clearly signified that grain yield can be increased by using the multi-ovary genotype with the semi-dwarf height. This new germplasm will be helpful for breeders to increase the production of wheat crops in the southern climate of Pakistan. [ABSTRACT FROM AUTHOR]

Durum wheat is used as raw material for many foods. Climate change might be responsible for larger or smaller changes in crop yields. For the combined assessment of climate and crop, growing degree days (GDDs) have a crucial role. Two experimental lines and twelve commercial wheat (Triticum durum) varieties from diverse backgrounds were cultivated to compare their crop properties, yield, and protein content in terms of GDDs. The experiment was established in typical Mediterranean environment, using a randomized complete block design with blocks of varieties and lines for two growing seasons. For all varieties, GDDs to head emergence was affected by factor year, whereas GDDs from head emergence to harvest were influenced by both varieties and year. Protein content (%) was not affected by genotypes. Factor of variety and interaction variety × year had an impact on vitreousness; it was ranged from 79.75 % ('Makaras' variety) to 44.00 % ('Levante' variety). Yield had no statistically significant difference among varieties/lines. In durum wheat cultivation, up to head emergence, when GDDs increased, yield would be declined in contrast to GDDs from emergence to harvest; with the increasing of GDDs to harvest, yield was climbed. Nowadays, the integrations of and interpretation of GDDs in the evaluation of crop performance seem vital. [ABSTRACT FROM AUTHOR]

This study investigates the impacts of climate change on yield of selected cereal crops (wheat and maize) in the northern climatic region of Khyber Pakhtunkhwa (KP) province of Pakistan for the period 1986–2015. The first-generation unit root tests such as the Levin, Lin, and Chu (LLC), augmented Dickey-Fuller (ADF)–Fisher, and the second-generation unit root tests such as cross-sectional augmented Im-Pesaran-Shin (CIPS) and cross-sectional ADF (CADF) are used to check stationarity of the series. The cointegration among the variables is discovered via Pedroni test and Westerlund method. The long- and short-run impacts of climatic variables (average precipitation, maximum temperature, and minimum temperature) on yield of wheat and maize crops are assessed through the autoregressive distributed lag (ARDL) model. The empirical findings reveal that average precipitation has a significantly positive impact on yield of both crops in long- as well as short-run. The results further reveal that the effect of average minimum temperature on both crops is insignificant in long-run. However, the short-run effect of average minimum temperature is significantly positive on yield of maize crop but insignificant on yield of wheat crop. In long-run, an increase in average maximum temperature negatively affects crop yield. In short-run, however, it positively affects the yield of wheat and maize crops. The study recommends that increase in area under cultivation, development of advanced irrigation system, and farmers' access to metrological information will help in lowering the drastic impacts of climate change on crop productivity. [ABSTRACT FROM AUTHOR]

Cropping intensification is a solution to ensure global food security amid the threats of climate change and variability. Crop models are used extensively to evaluate the performance of single crop for a particular year under future climate. However, very few literatures are available on the application of crop models to evaluate intensive cropping systems. The study attempts to address this issue by evaluating the impact of projected climate derived from 29 GCMs during four future scenarios (mid and end-century under RCP4.5 and RCP8.5) on the performance of rice–wheat-groundnut cropping sequence in Mohanpur, India, using the sequence analysis module of DSSAT. A marked reduction in crop duration was simulated for rice (4 to 17 days) and wheat (1 to 16 days) during all four future scenarios. On the contrary, the duration of groundnut increased by 1–4 days. Under elevated CO2 concentration, an increase in biomass was simulated for all three crops. During future periods under elevated CO2, the yield of rice tends to increase under all the future scenarios whereas wheat and groundnut could decrease the magnitude of yield reduction due to an increase in temperature. Rice was benefited due to the carry-over effect of residue from preceding groundnut and, hence, could sustain the yield on the long-term. The uncertainty in simulation due to the selection of GCMs was also quantified. The study provided a better understanding on how a cropping sequence responds to projected climate rather than a single crop in a sequence, which can be used to develop better adaptation strategies. [ABSTRACT FROM AUTHOR]

BACKGROUND Adaptive crop management is critical to food security in a changing climate, but the respective contributions of climate change and crop management to yields remain unclear. Thus, we distinguished and quantified the respective contribution of climate change and crop management on wheat yield between 1981 and 2018 in China, using first‐difference multivariate regression model. RESULTS: Wheat production in China has increased over the past four decades. Under the sole impact of climate change, wheat yield generally decreased (−5.45 to +1.09% decade−1). Crop management increased the wheat yield from 7.11 to 19.94% decade−1. Sensitivities of wheat yield to climatic variables (average temperature, accumulated sunshine hours, accumulated precipitation) were spatially heterogeneous; notably, in spring‐wheat planting areas, wheat yield was more susceptible to the negative impact of warming. In terms of relative contribution, the contribution of climate change to spring wheat yield was −24.08% to −5.41%, and the contribution to winter wheat was −4.98% to +34.69%. Crop management had a positive contribution to all wheat‐growing areas (65.31–96.84%). CONCLUSION: Crop management had a greater effect on wheat yield than climate change did. Among the three climatic variables investigated, average temperature had the dominant effect on wheat yield change; the impact of precipitation was minimal but mostly negative. The results provide insight regarding the contribution of climate change and crop management to wheat yield; adaptation measures may be more effective in planting areas where crop management contributes more, which will help stakeholders optimize crop management and adaptation strategies. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

• Growth stage-specific ECIs are important in estimating wheat yield. • Coupling crop model with machine learning can improve yield estimation accuracy. • Feature selection can reduce computation cost without affecting accuracy. • APSIM with RF and GA was the optimal model in estimating wheat yield. Assessing the impact of climate extremes on crop production is an important prerequisite for exploring agronomic practices to deal with changing climate. Process-based crop models are effective tools to assess the effect of climate change on crop yield, but cannot accurately express the impact of extreme climate events on crop yield. In this study, we developed a series of hybrid models by incorporating the APSIM model outputs and the most informative growth stage-specific extreme climate indices (ECIs) selected by two feature selection techniques (stepwise regression, SR and genetic algorithm, GA) into two machine learning algorithms (random forest, RF and light gradient boosting machine, LGBM) to evaluate impacts of climate extremes on wheat yields in the North China Plain (NCP). The results showed that the RF model outperformed the LGBM model in estimating wheat yield regardless of input variables. Applying feature selection to two machine learning algorithms can greatly reduce computational cost without significantly affecting model accuracy. The APSIM+RF-GA hybrid model was the optimal model for estimating wheat yield with explained 93 % of the observed yield variation and the accuracy of the model is improved by 33 % compared with the APSIM model alone. Extreme low temperature events before flowering and extreme high temperature events after flowering are the main extreme climate events causing the loss of wheat yield. In addition, we evaluated the impact of future climate change on wheat yield using the APSIM+RF-GA hybrid model and the APSIM model, respectively. Yields projected using a single APSIM model increased at all stations but yields projected using APSIM+RF-GA model decreased at 12.5–28.1 % of stations in the NCP under future climate scenarios. Compared to the APSIM+RF hybrid model, the future yield projected using single APSIM model might be overestimated by 12.7–19.2 % because of underestimating the yield loss caused by climate extremes. The increase of heat stress after flowering and frost stress during floral initiation to flowering were the main factors for future yield loss. Using the machine learning algorithm to make an external modification to the outputs of the APSIM model could improve the accuracy of yield estimation under extreme climate conditions and the method is more suitable for projecting future crop yield. This study is conducive to developing adaptation strategies to alleviate the negative impacts of future climate extremes on crop production. [ABSTRACT FROM AUTHOR]

Phytohormones are important for the growth and development of plants. The objective of the experiment was to investigate the effect of foliar application of uniconazole (UCZ) at the four-leaf stage on hormone crosstalk and production of winter wheat. An experiment was carried out during 2015–2016 and 2016–2017 growth season in a semi-arid region, where UCZ at a concentration of 0 (CK, distilled water), 15 (FU15), 30 (FU30), and 45 (FU45) mg L−1 were sprayed on wheat crop at the four-leaf stage at a rate of 138.8 mL m−2. UCZ alters the endogenous hormone contents in flag leaves and in grains. UCZ inhibited gibberellic acid (GA) in flag leaves and in grains where the lower GA with UCZ improved the zeatin + zeatin riboside (Z + ZR) and abscisic acid (ABA) contents. The lower GA and higher Z + ZR and ABA contents with UCZ-treated plants improved the chlorophyll content and canopy apparent photosynthesis (CAP) as well as the grain-filling characteristics. The Z + ZR and ABA in flag leaves were positively correlated with chlorophyll content and CAP value while negatively with GA. Moreover, the Z + ZR and ABA were positively correlated with maximum grain weight, mean grain-filling rate, and maximum grain-filling rate, while negatively with GA level. Treatment FU30 significantly improved the chlorophyll content, CAP value, spike weight, grain-filling characteristics, and hormone contents of Z + ZR and ABA while it decreased the GA level. The hormone crosstalk with UCZ significantly increased the yield of wheat crop, where FU30 treatment performs better. [ABSTRACT FROM AUTHOR]

Comparing outputs of multiple climate and crop models is an option to assess the uncertainty in simulations in a changing climate. The use of multiple wheat models under five plausible future simulated climatic conditions is rarely found in literature. CERES-Wheat, DSSAT-Nwheat, CROPSIM-Wheat, and APSIM-Wheat models were calibrated with observed data form eleven sowing dates (15 October to 15 March) of irrigated wheat trails at Faisalabad, Pakistan, to explore close to real climate changing impacts and adaptations. Twenty-nine GCM of CMIP5 were used to generate future climate scenarios during 2040–2069 under RCP 8.5. These scenarios were categorized among five climatic conditions (Cool/Wet, Cool/Dry, Hot/Wet, Hot/Dry, Middle) on the basis of monthly changes in temperature and rainfall of wheat season using a stretched distribution approach (STA). The five GCM at Faisalabad and Layyah were selected and used in the wheat multimodels set to CO2 571 ppm. In the future, the temperature of both locations will elevate 2–3 °C under the five climatic conditions, although Faisalabad will be drier and Layyah will be wetter as compared with baseline conditions. Climate change impacts were quantified on wheat sown on different dates, including 1 November, 15 November, and 30 November which showed average reduction at semiarid and arid environment by 23.5%, 19.8%, and 31%, respectively. Agronomic and breeding options offset the climate change impacts and also increased simulated yield about 20% in all climatic conditions. The number of GCMs was considerably different in each quadrate of STA, showing the uncertainty in possible future climatic conditions of both locations. Uncertainty among wheat models was higher at Layyah as compared with Faisalabad. Under Hot/Dry and Hot/Wet climatic conditions, wheat models were the most uncertain to simulate impacts and adaptations. DSSAT-Nwheat and APSIM-Wheat were the most and least sensitive to changing temperature among years and climatic conditions, respectively. [ABSTRACT FROM AUTHOR]

Global dimming, a decadal decrease in incident global radiation, is often accompanied with an increase in the diffuse radiation fraction, and, therefore, the impact of global dimming on crop production is hard to predict. A popular approach to quantify this impact is the statistical analysis of historical climate and crop data, or use of dynamic crop simulation modelling approach. Here, we show that statistical analysis of historical data did not provide plausible values for the effect of diffuse radiation versus direct radiation on rice or wheat yield. In contrast, our field experimental study of 3 years demonstrated a fertilization effect of increased diffuse radiation fraction, which partly offset yield losses caused by decreased global radiation, in both crops. The fertilization effect was not attributed to any improved canopy light interception but mainly to the increased radiation use efficiency (RUE). The increased RUE was explained not only by the saturating shape of photosynthetic light response curves but also by plant acclimation to dimming that gradually increased leaf nitrogen concentration. Crop harvest index slightly decreased under dimming, thereby discounting the fertilization effect on crop yields. These results challenge existing modelling paradigms, which assume that the fertilization effect on crop yields is mainly attributed to an improved light interception. Further studies on the physiological mechanism of plant acclimation are required to better quantify the global dimming impact on agroecosystem productivity under future climate change. [ABSTRACT FROM AUTHOR]

The extreme temperatures and uneven distribution of rainfall associated with climate change are expected to affect agricultural productivity and food security. A study was conducted to evaluate the impact of climate change on wheat in southeastern regions of Turkey. The CERES-wheat crop simulation model was calibrated and evaluated with data from eight surveyed farms. The four farms were used for calibration and four for evaluation. Climate change scenarios were developed for the middle (2036–2065) and late 21st century (2066–2095) under representative concentration pathways (RCPs 4.5 and 8.5) for study sites in Islahiye and Nurdagi. Model calibration results showed a good agreement between observed and simulated yield with only a 1 to 11% range of error. The model evaluation results showed good fit between observed and simulated values of all parameters with % error ranged from 0.51 to 13.3%. Future climate change projections showed that maximum temperature (Tmax) will increase between 1.6 °C (RCP4.5) and 2.3 °C (RCP8.5), while minimum temperature (Tmin) will increase between 1.0 °C (RCP4.5) and 1.5 °C (RCP8.5) for mid-century. At the end of the century, Tmax is projected to increase from 2 °C (RCP4.5) to 4 °C (RCP8.5) and Tmin from 1.3 °C (RCP4.5) to 3.1 °C (RCP8.5). Climate change impacts results showed that future rise in temperature will reduce wheat yield by 16.3% in mid-century and 16.8% at the end of the century at Islahiye and for Nurdagi, while 13.0% in mid and 14.4% end of the century. The use of climate and crop modeling technique provides useful information in evaluating the climate change impacts and may assist stakeholders to make decisions to overcome the negative impacts in the near and long term. [ABSTRACT FROM AUTHOR]

Unpredicted variability in climate change on the planet is associated with frequent extreme high-temperature events impacting crop yield globally. Wheat is an economically and nutritionally important crop that fulfils global food requirements and each degree rise in temperature results in ∼6% of its yield reduction. Thus, understanding the impact of climate change, especially the terminal heat stress on global wheat production, becomes critically important for policymakers, crop breeders, researchers and scientists to ensure global food security. This review describes how wheat perceives heat stress and induces stress adaptation events by its morpho-physiological, phenological, molecular, and biochemical makeup. Temperature above a threshold level in crop vicinity leads to irreversible injuries, viz. destruction of cellular membranes and enzymes, generation of active oxygen species, redox imbalance, etc. To cope with these changes, wheat activates its heat tolerance mechanisms characterized by hoarding up soluble carbohydrates, signalling molecules, and heat tolerance gene expressions. Being vulnerable to heat stress, increasing wheat production without delay seeks strategies to mitigate the detrimental effects and provoke the methods for its sustainable development. Thus, to ensure the crop's resilience to stress and increasing food demand, this article circumscribes the integrated management approaches to enhance wheat's performance and adaptive capacity besides its alleviating risks of increasing temperature anticipated with climate change. Implementing these integrated strategies in the face of risks from rising temperatures will assist us in producing sustainable wheat with improved yield. • The rising temperature caused by climate change leads to abiotic stress harms crop growth and productivity. • Heat stress (HS) is limiting factor that declines and affects wheat production globally. • Perception and adaptation mechanism induced in response to stress explains the impact of climate change on crop "wheat". • Need of crop resilience to sustain the productivity matching the rising food demand. • Recently and successfully used management strategies improve stress tolerance and yield to cope with the existing/upcoming environmental changes. [ABSTRACT FROM AUTHOR]

Climate change also affects food production. However, what will be the response of agricultural crops to future climate conditions across Europe is one of the key issues for the development, implementation and proper implementation of the new European agricultural policy. This paper addresses the potential response of selected European agricultural crops (wheat [Triticum aestivum L.], maize [Zea Mays L.], potato [Solanum tuberosum L.] and olive [Olea europaea L.]) to climate scenarios (RCP2.6, RCP4.5 and RCP8.5) in the second half of the 21st century (2070) by considering different global climate models (CC, HE and MP). Bioclimatic data from the ECOCROP database (temperature and precipitation ranges) for each considered crop and the WorldClim climatic database for Europe were used to develop maps showing the future potential crop climate suitability. The results confirm existing assumptions that, in general, the optimal climatic conditions for the production of selected crops will shift towards higher latitudes or altitudes. Indeed, this potential spatial shift is, of course, species specific and depends on many other natural and socio-economic factors. [ABSTRACT FROM AUTHOR]

Understanding the impacts of climate change on crop yield is important for improving crop growth and yield formation in northwestern China. In this study, we evaluated the relationship between meteorological dryness/wetness conditions and spring wheat yield in the Ili river basin (IRB). The climate and yield data from 1961 to 2013 were collected to analyze characteristics and correlations between these two variables using the standardized precipitation evapotranspiration index (SPEI), yield detrending method, modified Mann-Kendall test and Spearman correlation analysis. Main results were as follows: (1) correlations between monthly SPEI values (MSV) and climatic yield of spring wheat indicated that the dryness/wetness condition in May was a key factor affecting yield in the whole region; (2) although the MSV in May and yield fluctuated from negative to positive values in time, the severely and extremely dryness events were in good agreement with the higher yield losses; (3) each increase of 0.5 MSV in May promoted over 3% increase of yield in most part of IRB; however, the larger variability of MSV in May resulted in larger yield fluctuations; and (4) the Tibetan Plateau index in April showed significant correlations with the MSV in May and yield, which provided a precursory signal for decision-makers to better understand potential yield fluctuations. [ABSTRACT FROM AUTHOR]

Breeding for resilience to climate change is a daunting prospect. Crop and climate models tell us that global wheat yields are likely to decline as the climate warms, causing a significant risk to global food security. High temperatures are known to affect crop development yet breeding for tolerance to heat stress is difficult to achieve in field environments. We conducted an active warming study over two years to quantify the effects of heat stress on genetic variation of soft red winter (SRW) wheat (Triticum aestivum L.). Forty SRW cultivars and breeding lines were chosen based on marker genotypes at photoperiod sensitivity and reduced height loci. These genotypes were planted in a randomized complete block design replicated twice across two environments, ambient and artificially warmed. Average heading date occurred 5 days earlier in the warmed environment than in the ambient environment over both years (p ≤ 0.05). On average, grain yield was significantly reduced in the warmed environment by 211.41 kg/ha (p ≤ 0.05) or 4.84%, though we identified 13 genotypes with increased yield in response to warming in both years. Of these genotypes, eight had significantly increased N uptake while six showed significantly increased N utilization efficiency under warming. Under warming, genotypes with wild‐type alleles at the Rht‐D1 locus display significantly greater yields (p ≤ 0.01) and biomass (p ≤ 0.001) than genotypes with reduced height alleles. Of the 13 genotypes with higher (p ≤ 0.01) yields under warming, nine have the wild‐type allele at the Rht‐D1 locus in addition to being photoperiod insensitive. The next steps will be to validate these findings in other populations and to develop an efficient breeding/phenotyping scheme that will lead to more resilient cultivars. Increasing global temperatures will reduce wheat yield and productivity. To identify genetic variation for resilience to warming, we screened a set of diverse wheat genotypes in a warmed and a control environment. On average, grain yield was significantly (p < 0.05) reduced in the warmed environment though we identified genotypes which had higher yields in response to warming in both years. [ABSTRACT FROM AUTHOR]

The paper aims to explore the biasness in the RegCM climate model outputs for diverse agro-climatic zones of Uttar Pradesh, India, with emphasis on wheat (Rabi growing season) and rice (Kharif growing season) yields with and without bias correction using quantile mapping approach for the baseline period of 1971-2000. The result shows that RCM highly underestimated the maximum and minimum temperature. There exists a bias towards lower precipitation in annual and Kharif and higher in Rabi along with strikingly low intense warm (maximum temperature > 45 °C and 40 °C) and high cold events (maximum temperature < 20 °C and minimum temperature < 5 °C) in the RCM simulation and biased towards low extreme rainfall > 50 mm/day. Bias correction through quantile mapping approach, however, showed excellent agreement for annual and seasonal maximum and minimum temperature and satisfactory for extreme temperatures but drastically failed to correct rainfall. The study also quantified the biasness in the simulated potential, irrigated, and rainfed wheat and rice yield using DSSAT (Decision Support System for Agro-technology Transfer) crop model by employing observed, RCM baseline, and RCM baseline bias-corrected weather data. The grain yields of RCM-simulated wheat and rice were high while the bias-corrected yield has shown good agreement with corresponding observed yield. Future research must account for the development of more reliable RCM models and explicitly bias correction method in specific to complement future analysis. [ABSTRACT FROM AUTHOR]

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures. [ABSTRACT FROM AUTHOR]

Winter wheat ( Triticum aestivum L.)-fallow (WF) remains a prominent cropping system throughout the Central Great Plains despite documentation confirming the inefficiency of precipitation storage during the summer fallow period. Wheat yield is greatly influenced by available soil water at planting, and that quantity is influenced by cropping intensity, tillage intensity, crop grown prior to winter wheat planting, and length of the non-crop period prior to winter wheat planting. The objective of this study was to determine the effect of cropping system intensity, tillage, and crop prior to wheat planting on available soil water at planting and the probabilities of having certain minimum amounts of available soil water at wheat planting. Available soil water was measured at wheat planting for nine cropping systems varying in fallow frequency, tillage intensity, and crop prior to wheat over a 25-yr period at Akron, CO. Available soil water at wheat planting was found to be greatest (average 218 mm) for no-tillage (NT) and reduced-tillage (RT) systems in which a fallow period of 12–14 months preceded wheat planting. The lowest amounts of available soil water at wheat planting were found for the continuously cropped rotations (average 100 mm). The cumulative probability exceedance graphs of available soil water at planting fell into three groupings: 1) the five rotations that had a NT or RT fallow period prior to the next wheat crop; 2) the WF (conventional till) rotation; 3) the three rotations with either pea ( Pisum sativum L.) or proso millet ( Panicum miliaceum L.) prior to the next wheat crop. These graphs provide a valuable decision support tool for helping farmers assess risk in moving from a WF cropping system to a system of greater cropping intensity and diversity. [ABSTRACT FROM AUTHOR]

Wheat is an important cereal food crop providing key nutrients to humankind. Rusts are the most destructive pathogens of cereal crops, with the exception of rice, across the world and resistant cultivars have been widely employed to reduce the yield losses caused by them. The modern intensive monoculture of cultivars and changing climatic conditions has created congenial conditions for the emergence of new virulent races such as Ug99, which is a great concern for world food security. Conventional breeding efforts have not been effective in quickly developing new varieties with durable and broad‐spectrum resistance against the rapidly evolving rust pathogen races. However, in the last two decades, biotechnological methods such as marker‐assisted selection (MAS) and transgenic technology have provided novel strategies for enhancing resistance levels and durability in crop plants in a short span of time. Nevertheless, broad application of transgenics in agriculture is hindered by biosafety apprehensions. In recent years, improved versions of biotechnological breeding methods such as genomic selection, genome editing technologies, cisgenesis and intragenesis, RNA‐dependent DNA methylation (RdDM), agroinfiltration and reverse breeding are gaining popularity. These technologies provide a tremendous capability to manipulate crop plants more precisely than before and accelerate crop improvement efforts for sustained food production as well as overcoming safety concerns associated with food crops. [ABSTRACT FROM AUTHOR]

Sowing date is a crucial factor for wheat ( Triticum estivum L.) production. From traditional field experiments, optimum sowing date for wheat cultivation could be found out based on existing weather and soil conditions but not possible for futuristic sowing window to address climate change impacts. Crop simulation model can play an important role in this regards. So, a study was conducted at Regional Wheat Research Centre (RWRC), Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh to evaluate the CERES-wheat crop model in simulating optimum sowing window for wheat. Thirteen sowing dates starting from 21 October to 20 December at five days interval were tested with wheat cultivar BARI Gom-26. The model was calibrated and validated with one field experimental data followed by 30 years seasonal runs. Optimum sowing window for wheat is 15 November–30 November in Bangladesh. On an average, grain yield of wheat was reduced by 30–40 kg day −1  ha −1 when sown from 1 December to 20 December. Similarly, grain yield reduction was about 148–102 kg day −1  ha −1 with early sown wheat (21 October–14 November). [ABSTRACT FROM AUTHOR]

Polyamine metabolism is in relation with several metabolic pathways and linked with plant hormones or signalling molecules; in addition polyamines may modulate the up- or down-regulation of gene expression. However the precise mechanism by which polyamines act at the transcription level is still unclear. In the present study the modifying effect of putrescine pre-treatment has been investigated using the microarray transcriptome profile analysis under the conditions where exogenous putrescine alleviated osmotic stress in wheat plants. Pre-treatment with putrescine induced the unique expression of various general stress-related genes. Although there were obvious differences between the effects of putrescine and polyethylene glycol treatments, there was also a remarkable overlap between the effects of putrescine and osmotic stress responses in wheat plants, suggesting that putrescine has already induced acclimation processes under control conditions. The fatty acid composition in certain lipid fractions and the antioxidant enzyme activities have also been specifically changed under osmotic stress conditions or after treatment with putrescine. [ABSTRACT FROM AUTHOR]

Recently, sugarcane largely introduced in "Dera Ismail Khan" (D.1.Khan) Khyber Pakhtunkhwa Province, Pakistan, especially during the summer season. The current study was conducted at Arid Zone Research Centre (AZRC), Dera Ismail Khan (D.1.Khan) to evaluate cost and benefit, as well as climatic profile suitability for wheat cultivation, during 2014/2015 and 2015/2016 seasons. A sample of 200 respondents from 10 major wheat growing villages of the respective areas of the district was interviewed through pre-tested questionnaire. The study revealed that the cost of wheat production was Rs. 35,680 per acres, whereas output comes 1680 kg per acre (42 mounds) amounting Rs. 63,600 per acres. Farmers' margin also rises by adding the value of family labor and owned land, which is sufficient to sustain a normal family. Moreover, positive influence between return price and output of wheat was concluded from the study, whereas negative effect of cost was also observed. The output elasticity of Land preparation (LP), Seed and Sowing (SS), Farm inputs (Fl), Irrigation (Irr), Pesticides / insecticides (Pest) and Harvester threshing (HT) are 0.124587, 0.31244, 0.5874, 0.55461, 0.08248 and 0.65743, respectively. From climatic point of view, calculated accumulated growing degree days all over the studied seasons at the studied district were about 2663.5 degree days two seasons average. This is sufficient for the used type of wheat at this area to push the different growing stages and present economic crop yield. [ABSTRACT FROM AUTHOR]

The results obtained indicate a favorable climate change for cereal yields. This change in climate was expressed by increase in maximum temperature of 1.45°C, minimum temperature of 1.26°C and 2.5 mm increase in precipitation. It was also observed that change in climate increased the total production of wheat to 16544.4 tonnes during the studied periods of 1990 to 2004 and 2004 to 2014 due to improved productivity of wheat to 6.33 tonnes/ha. It was also observed that different durum wheat producing regions in eastern Algeria did not differ significantly in respect to production. On the basis of this study, it can be concluded that climate change had positive effect on durum wheat production in the Bordj Bou Arréridj province of Algeria. [ABSTRACT FROM AUTHOR]

An attempt was made to determine the seasonal evapotranspiration and crop coefficient of wheat during various growth stages under drip irrigation and N-fertigation scheduling in Jalgaon, Maharashtra during 2012-13 and 2013-14. The results revealed that grain and straw yield of wheat increased significantly at each higher levels of drip irrigation up to 1.0 Epan and fertigation of 120 kg N ha-1 in both the years. The mean daily ETc of wheat during its initial stage was found to be lower and almost constant and it increased continuously during vegetative stage, flowering and grain filling stage (4.75 mm day-1) and decreased during the maturity stage. The measured seasonal ETc of wheat was ranged from 294.5 to 453.5 mm. The highest seasonal ETc and ETc was recorded in surface check basin irrigation at IW/ CPE 1 and lowest in deficit irrigation schedule i.e. drip irrigation at 0.6 Epan. Each higher level of nitrogen from N0 to N160 slightly increased the seasonal ETc of wheat. Estimated crop coefficient values (0.71, 1.31, 1.34 and 0.76 at initial, crop development, mid season and late season stage) at 1.0 Epan through drip were slightly higher over the FAO Kc values. [ABSTRACT FROM AUTHOR]

Heading time is a critical feature determining wheat performance. Over the years, average global temperatures have increased, leading to adjustments in agronomic practices such as sowing dates and cultivar election. Bread wheat development is regulated by the effect of vernalization (Vrn), photoperiod sensitivity (Ps), and earliness per-se (Eps). The aim of this study was (i) to quantify the physiology behind wheat development for a wide range of contrasting commercial genotypes, and (ii) to design a simple wheat phenology prediction model that considers vernalization and photoperiod effects. Seventeen wheat genotypes that vary in VERNALIZATION-1 (Vrn1) , PHOTOPERIOD-1 (Ppd1) , and EARLINESS PER-SE D1 (Eps-D1) alleles were classified into four groups: Winter Sensitive (WS), Winter Insensitive (WI), Spring Sensitive (SS), and Spring Insensitive (SI). Field trials with vernalization treatments were carried out in different sites, years, and sowing dates. Genotypes with Vrn1 triple winter alleles exhibited the highest vernalization requirements, while cycle duration in spring genotypes remained constant. Photoperiod sensitivity was higher for those genotypes molecularly classified as Ppd1 sensitive but a differential response was evident when control and vernalization treatments were compared: after 6-week vernalization, Ps in WI decreased significantly without significant differences for WS, SS, and SI. For winter genotypes, the optimum photoperiod (Po) was the longest for the 6-week vernalized groups, and within that level of vernalization WI showed the longest Po values. The variability in Ps and Po values could be explained by the interaction between photoperiod and vernalization over Vrn1 upregulation and their consequent effect on wheat cycle duration. A wheat phenological model using photoperiod and vernalization correction factors was calibrated to predict heading dates in the Argentine wheat region. The model accurately predicted heading date with an error of 8.1, 6.5, 6.2, and 7.0 days for WI, WS, SI, and SS, respectively. The development of a model that uses simple universal process-based parameters is crucial for farmers, advisors, and researchers as it increases the precision in wheat cycle arrangement, but in a relatively parsimonious fashion. • Predicting phenology is essential for crop adaptation in a climate change scenario. • Photoperiod sensitivity had a differential response to increasing levels of pre-vernalization depending on Vrn1 and Ppd1. • Eps-D1 allele partially separated between precocity groups for average phase duration. • A heading date model using simple photoperiod and vernalization coefficients improves traditional wheat phenology prediction. [ABSTRACT FROM AUTHOR]

Recently there has been a renewed interest in the optimization and development of legume cultivation technologies in many European Countries. By choosing the species which fit well the local soil and weather conditions might be an excellent solution to obtain a high fodder and grain yield. Field trials with faba bean (Vicia faba L.) and faba bean spring wheat (Triticum aestivum L.) mixture were conducted to evaluate the effect of seed inoculation with Rhizobium strain on the productivity of faba bean and its mixture with spring wheat. The study was conducted at two sites, Joniškėlis Experimental Station (site I) and Vėžaičiai Branch (site II) of the Lithuanian Research Centre for Agriculture and Forestry. The findings obtained in site I revealed that the dry matter (DM) yield of crops at the pod development stage averaged 7575 kg ha-1 and the grain yield averaged 6067 kg ha-1; the corresponding values for site II were 5684 kg ha-1 and 4937 kg ha-1, respectively. In most cases, the content of nutrients - crude proteins, crude fat, crude fibre, neutral detergent fibre, and crude ash in the biomass was higher in site I. The faba bean - spring wheat mixture produced a higher grain yield and a higher metabolizable energy content in grains compared with the faba bean grown as a sole crop; other measured parameters did not reveal the superiority of the mixture over the sole faba bean. Rhizobium spp. application had a positive impact by increasing the above-ground biomass DM yield and grain yield in a sole crop as well as in a mixture with wheat. [ABSTRACT FROM AUTHOR]

The experiment was conducted in concrete drought plots during Rabi seasons 2014-15 and 2015-16 at CCS Haryana Agricultural University, Hisar on wheat genotypes to find out the suitable genotypes for restricted irrigation application. The experiment was designed as split plot consisting of three irrigation schedules viz., normal irrigated (Control), three irrigations at 25, 85 and 105 DAS (moderate stress) and two irrigations at 25 and 85 DAS (Severe stress) in the main plots and five genotypes namely WH 1080, WH 1126, WH 1142, WH 1164 and WH 1181 in the sub-plots replicated thrice. Water stress conditions compared to normal irrigated condition decreased significantly all the plant water relation parameters viz. leaf water potential(LWP), relative water content (RWC), canopy temperature depression(CTD) and physiological parameters like transpiration rate, photosynthetic rate and stomatal conductance. RWC, photosynthetic rate and CTD were found highest and lowest with WH1164 and WH1142, respectively. Among the wheat genotype tested WH1164 was recorded with maximum grain yield (4265 kg/ha) due to maximum number of tillers , better plant water status and higher rate of photosynthesis of flag leaf at anthesis compared other genotypes under restricted soil moisture conditions. Hence WH1164 found best wheat genotype to improve the wheat productivity under water limited conditions of Hisar. [ABSTRACT FROM AUTHOR]

Calculating crop water requirements has a special economic importance in rationalization of water consumption in the agricultural field under current and future climate conditions. Crop water requirements were estimated from daily potential ET at ambient and projected air temperature by using Papadakis method and then by multiplying with crop coefficients. In the present study responses to future climate scenarios of 21st century projected by the GCM (ECHam5) and RCM (PRECIS) given by Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC SRES) A1B emissions were investigated. The ECHam5 and PRECIS data were taken to calculate the ET for present time slice (PTS), mid century (MC) and end century (EC)at four different dates of transplanting/sowing rice and wheat crop. It has been observed that by ECHam5model,the most suitable time for rice transplanting during PTS is 16thJune while it will be on 6th July during MC as well as EC. According to RCM model,the most suitable time for rice transplantingis 16th June for PTS, MC and EC. In wheat crop, it has been observed that 2nd December is suitable time for sowing during PTS, MC, and EC. Annual crop water requirement during PTS, MC and EC were 997.6, 908.1and 1020.3 mm, respectively. [ABSTRACT FROM AUTHOR]

The effect of epidemiological factors on the severity of stripe rust in cv. PBW 343, under early sowing conditions were studied during 2013-14 and 2014-15, rabi seasons. The disease was first appeared in 1st standard meteorological week (SMW) when the crop stage was at 73 days after sowing. Sharp increase in disease severity was observed during 6th to 8th SMW due to the conducive weather conditions which prevailed during the previous fortnight. The meteorological parameters like maximum temperature, minimum temperature, morning vapour pressure, evening vapour pressure and micro meteorological parameters (canopy temperature and soil temperature) had significantly positive correlation with the disease severity in the tested wheat variety, whereas, maximum relative humidity had significant negative correlation. Rainfall had moderately positive correlation with the disease severity. The models generated through stepwise multiple regression analysis revealed that thermic, and hydric variables contributed significantly for the variance in disease severity. Among the three principal components, Pc1 that was contributed by various epidemiological factors (thermic and biological) accounted for maximum variance in disease severity followed by Pc2 (light variables) and Pc3 (hydric variables). [ABSTRACT FROM AUTHOR]

Crop water productivity is an important indicator of agricultural water use. Understanding the impacts of climatic and agricultural factors variation on crop water productivity will provide a theoretical basis for regional crop productivity improvement. In this study, crop productivities at two scales were estimated based on the analysis of the agricultural water use in Hetao irrigation district, China. The sensitivity analysis was used to explore the sensitivity of crop water productivity to the variation of climatic and agricultural factors. Contribution rate analysis method was adopted to quantitatively evaluate the driving force of water productivity changes due to the variation of climatic and agricultural factors during the study period. Results show that crop water productivity of wheat had an average of 0.85 kg/m 3 over the study period at the field scale, and it had an average of 0.46 kg/m 3 at the regional scale. Both displayed an obvious upward during the study period. Among the climatic factors, water productivity of wheat at both the field and regional scales had higher sensitivity to relative humidity and wind speed, and had a lower sensitivity to sunshine hours. Among the agricultural variables, the crop water productivity had a higher sensitivity to irrigation efficiency, and is less sensitive to the amount of fertilizer used. The increase of agricultural inputs and irrigation efficiency were the main factors contributing to water productivity increases in Hetao Irrigation district. Climatic variations within the study period had less impact on the water productivity of wheat. [ABSTRACT FROM AUTHOR]

Wheat crop is influenced by different microclimatic parameters like solar radiation, canopy temperature etc. Agronomic manipulation like change in row spacing and row direction can be used as a strategy to modify the microclimate of crop. Keeping these facts in view, field trials were conducted during rabi 2012-13 and 2013-14 under two experiments in first experiment wheat varieties HD 2967, PBW 550 and PBW 343 were sown under three row spacing viz. 15 cm, 22.5 cm and 30 cm. In second experiment, wheat varieties HD 2967, PBW 550 and PBW 343 were sown under two row direction viz. North-South (N-S) and East-West (E-W). Short wave radiation interception and canopy temperature was recorded under different treatments at 15 days interval. Among different row spacing, short wave radiation interception and canopy temperature was maximum at 30 cm row spacing (77.7% and 25.1°C) followed by 22.5 cm (75.7% and 24.2°C) and 15 cm row spacing (73.9% and 23.2°C), whereas under row directions short wave radiation interception and canopy temperature was more (76.5% and 23.9°C) in E-W row direction as compared to N-S row direction (75% and 23.2°C). Relationships were developed between dry matter accumulation and canopy temperature. Polynomial relationships gave significant R² value (0.66 & 0.69) under different treatments. This two year study indicated that agronomic manipulations play an important role in microclimate modification and canopy temperature significantly influence dry matter accumulation under different crop geometry. [ABSTRACT FROM AUTHOR]

We build on the price transmission framework to identify domestic wheat price effects of wheat export controls. We explicitly take into account that a harvest failure causes domestic price effects. Moreover, the analysis at the regional level provides further evidence of the functioning of export controls in a large country. Results suggest a pronounced regional heterogeneity in the strength of domestic price effects of the 2010/11 export ban in Russia. The wheat price dampening effects amount to up to 67% and are strongest in the major wheat exporting region with direct access to the world market. This effect is transmitted to other regions by increased and reversed interregional trade flows. In contrast, we find that regional variation of export controls' domestic price effects in Ukraine is rather small. [ABSTRACT FROM AUTHOR]

The field experiments were carried out during rabi seasons of 2013-14 and 2014-15 at Research Farm, School of Climate Change and Agricultural Meteorology, PAU, Ludhiana to study the effect of different temperature regimes, nitrogen levels and post anthesis strategies on phenology growth, development and grain yield of wheat. The experiment was laid out in Split- Split plot design having three temperature regimes (D1=October 30, D2=November 15 and D3= November 30) in main plot, three nitrogen levels (N1=RDF (Recommended dose of N), N2=125% RDF (25% more than recommended N), N3=150% RDF (50% more than recommended N) in sub plot and four heat stress management post-anthesis strategies (P0=Control, P1=Water sprayed, P2=Foliar spray of ZnSO4.7H20 (0.5%), P3=Thiourea (10 mM) at anthesis and 20 days after anthesis in sub-sub plot during both years. The agrometeorological indices such as accumulated growing Degree Days (AGDD), heliothermal units (HTU), photo thermal units (PTU) and heat use efficiency (HUE) were calculated and their relation with grain yield was also observed. The results showed that the crop sown on October 30 with 150% RDF when spray at or after anthesis at regular intervals with any of stress alleviating chemicals such as ZnSO4.7H2O (0.5%), Thiourea (10 mM) or water accumulated more number of growing degree days, photo thermal units and had higher heat use efficiency than other treatments because crop exhibited best growth and development as the favorable environmental conditions concided with higher heat unit requirement of different phenophases and gave higher grain yield [ABSTRACT FROM AUTHOR]

In order to study the effective water-saving cultivation of wheat in Sichuan under drought conditions to reduce grain loss, the effects of different irrigation methods (natural rainfall, artificial irrigation, and infiltrating irrigation) on soil physical characteristics and main agronomic characters and yield of wheat were analyzed. The results showed that different irrigation treatments at different growth stages had different effects on soil physical characteristics and agronomic characters of wheat. At the seedling and jointing stage, there were small differences between the treatments in soil compactness, soil bulk density, and soil water content. At the flowering and maturation stage, different irrigation treatments had great impacts on soil compactness, soil bulk density, soil water content, and agronomic characters of wheat. In the hilly areas of Sichuan Basin, infiltrating irrigation at the jointing stage was the best, and wheat yield increased significantly, 2 113.46 kg/hm² higher than that in the control. [ABSTRACT FROM AUTHOR]

The Crop Environment Resource Synthesis (CERES) models have been developed and utilized for the last 30 years to simulate crop growth in response to climate, soil, genotypes and management across locations throughout the world. We reviewed 215 papers found in the literature that contained field observed data where the CERES models were tested. Over 30 simulated variables of the CERES models have been tested in 43 different countries under various experimental treatments. Across all testing conditions, the CERES models simulated grain yield with a root mean square error (RMSE) of less than 1400 kg/ha (~10% relative error, RE), 1200 kg/ha (~20% RE) and 800 kg/ha (~10% RE) for maize, wheat, and rice, respectively. Phenological development was simulated with less than 7 days difference from the observations in most studies. The CERES models simulated aboveground biomass, harvest index, evapotranspiration, and soil water reasonably well too. The simulations of grain number (up to 4340 root mean square error, RMSE), grain weight (up to 22% error), intercepted photosynthetically active radiation (IPAR, up to 0.41 MJ/plant), leaf area index (LAI, 31.9% error), soil temperature (over 10°C difference), and nitrogen (N) dynamics (up to 80% error) were less accurate. In fact the average error of CERES model simulations tends to be higher under marginal crop growing conditions such as extreme heat or cold, water and nutrient deficit conditions. [ABSTRACT FROM AUTHOR]