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Meteorological variables are essential inputs for agricultural simulation models and the lack of measured data is a big challenge for the application of these models in many agricultural zones. Studies indicated that gridded meteorological datasets can be proper replacements for measured data. This paper aimed to examine a new gridded meteorological dataset namely CRU-JRA for crop modeling intents. The CRU-JRA is a 6-hourly dataset with a spatial resolution of 0.5° × 0.5° that was primarily constructed for modeling purposes. The CERES-Wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) was used for the simulation of irrigated and rainfed wheat production systems in Iran. Results showed that the CRU-JRA maximum and minimum temperature values had a relatively fine accuracy with a normalized root mean square error (NRMSE) of 14% for the simulated grain yield. The performance of the CRU-JRA solar radiation values for the simulation of grain yield was similar with a NRMSE of 14.4%. The weakest performance was found for the CRU-JRA precipitation values with a NRMSE of 18.9%. Overall, the CRU-JRA dataset performed comparatively acceptable and similar to existing gridded meteorological datasets for crop modeling purposes in the study area, however further calibrations can improve the accuracy of the next versions of this dataset. More research is necessary for the investigation of the CRU-JRA dataset for agricultural modeling purposes across diverse climates. [ABSTRACT FROM AUTHOR]

This study aims to predict the yield of two strategic crops in Iran; wheat and rice, under climate scenarios that indicate probable changes in climate variables. It implemented by a stochastic model based on the Monte Carlo method. This model were estimated based on historical data from 1988 to 2019 for precipitation and temperature provided possible changes in the pattern of and their probability of occurrence. The results show that rain-fed wheat, irrigated wheat and rice yields decrease by 42%, 29% and 21% respectively in the average scenario. Therefore, policy makers should try to make the right decisions to increase the production of the country's strategic crops. R&D management to introduce drought-tolerant varieties, use of modern irrigation systems and use of low-volume irrigation methods are some of the proposed solutions to mitigate the effects of climate change. [ABSTRACT FROM AUTHOR]

Salinity is challenging agriculture by reducing crop productivity. Endophytes from halophyte plants have the potential to alleviate salinity stress in crops. Here, 78 bacterial strains were recovered from 10 habitat-adapted halophyte plants in the central deserts of Iran. Eight superior halotolerant strains tolerating 3 M NaCl, were identified as the Gram-positive genera Bacillus and Oceanobacillus (Bacillaceae), Brachybacterium (Dermabacteraceae), Micrococcus (Micrococcaceae), and Salinicoccus (Staphylococcaceae). Scanning electron microscopy (SEM) showed that the most halotolerant strain, i.e., Salinicoccus hispanicus, experienced accelerated binary fission under salinity. Furthermore, seeds of the two winter wheat cultivars, i.e., cv. Homa (rain-fed) and cv. Mihan (irrigated), inoculated by those bacteria, showed enhanced germination indices under different salinity gradients, and also under normal conditions. Indeed, the superior bacteria, i.e., Oceanobacillus sp. strain 76, Micrococcus luteus strain 14, and Bacillus sp. strain 7, enhanced seed germination indices in both wheat cultivars including final seed germinations, as well as the root, shoot and seedling lengths. These strains were capable of producing the plant hormone auxin (IAA). Thus, we propose that halotolerant endophytic bacteria from desert-adapted halophyte plants could alleviate salinity stress in strategic crops such as the wheat Triticum aestivum L., especially in dryland farming. [ABSTRACT FROM AUTHOR]

Rising temperatures of 1.5–4 °C by the end of the twenty-first century and continuing after 2100 have caused climate change to threaten food security. Indeed, the rainfed production of strategic crops such as wheat in countries such as Iran, which are likely to be highly affected by climate change, is very important. This study aimed to identify the suitable areas for rainfed wheat cultivation and the yield gap estimation in current and future climatic conditions using geographical analysis, a crop simulation model, and the GYGA protocol in Iran. For this, environmental variables (including average, minimum, and maximum temperatures, rainfall) along with topographic (slope, elevation) and edaphic components (such as organic carbon, pH, EC, [CaCO3], exchangeable sodium percentage, cation exchange capacity, and soil erosion) were involved. The results revealed that around 30% of the total areas (6.62 million ha) are not suitable at all, while just 13% of total lands (2.97 million ha) were highly suitable and suitable. These areas are mainly located in the northern part of Iran. The study of the climate change scenarios indicated that the northern, northwestern, and western parts of the country have great potential for rainfed wheat production and future climate change will benefit wheat production in these areas, but in other parts of the country, more unfavorable conditions are expected. The mean water-limited potential yield (Yw) difference between marginally suitable to not suitable classes was narrow (< 0.3 t ha−1), while for highly suitable to moderately suitable classes was about 2.5 t ha−1. [ABSTRACT FROM AUTHOR]