Calibration and Validation of AQUACROP and APSIM Models to Optimize Wheat Yield and Water Saving in Arid Regions

Kheir, Ahmed M. S.; Alkharabsheh, Hiba M.; Seleiman, Mahmoud F.; Al-Saif, Adel M.; Ammar, Khalil A.; Attia, Ahmed; Zoghdan, Medhat G.; Shabana, M.; Aboelsoud, Hesham M.; Schillaci, Calogero

doi:10.3390/land10121375

Cited by 33 publications

(16 citation statements)

References 60 publications

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“…implications of various management strategies (Kheir et al, 2021), and integrating CGMs with whole-genome prediction (Cooper et al, 2016;Messina et al, 2018;Technow et al, 2015). Recent studies also suggest the use of detailed genomic information and a well-structured CGM to statistically impute key parameters, facilitating CGM calibration at the scale of a breeding population (Cooper et al, 2016;Messina et al, 2018).…”

Section: Core Ideasmentioning

confidence: 99%

Calibration of a crop growth model in APSIM for 15 publicly available corn hybrids in North America

2023

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Application of crop growth models (CGMs) in plant breeding is limited by the large number of candidate cultivars that breeders work with and the large number of CGM parameters that affect cultivar performance. The objectives of this study were to (1) calibrate 15 publicly available maize hybrids in Agricultural Production Systems sIMulator and quantify prediction accuracy in modeling physiological trait differences (yield, biomass, phenology, etc.) among genotypes; (2) better understand minimum phenotypic data requirements for CGM cultivar calibration to inform breeding efforts; and (3) quantify simulated genotype by environment interactions (G × E) across years for five traits. We calibrated hybrids with two years of multi‐trait, temporal field measurements. The R2 of simulated versus observed phenotypes was 0.89 for grain yield and over 0.80 for half of all other simulated traits. Phenology parameters accounted for nearly half of the variability in grain yield. Average (across traits) normalized root mean square error was reduced from 35% to 30% with calibration based on phenological measurements and was reduced to 20% with inclusion of physiological and nitrogen‐related measurements such as radiation use efficiency and grain nitrogen. Long‐term simulations demonstrated distinct G × E among the hybrids which accounted for 2%–29% of the total genetic variation across traits. Parameter values derived in this work will provide insight regarding important physiological traits for further phenotyping, selection, and understanding of G × E. These calibrations are for publicly available hybrids, which are currently lacking.

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Section: Core Ideasmentioning

confidence: 99%

Calibration of a crop growth model in APSIM for 15 publicly available corn hybrids in North America

2023

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“…Crop simulation models can be used to evaluate the optimization of different resources for a specific agroecological zone (Kheir et al, 2021;Khan et al, 2022). The decrease in crops yields can be perhaps due to long-term variation in precipitation patterns and temperature that is more expected to shift cropping seasons, suitability of crops cultivation, and high incidence of pests and diseases (Aryal et al, 2019).…”

Section: Production Of Agricultural Crops Production Of Agricultural ...mentioning

confidence: 99%

Climate change, its impact on crop production, challenges, and possible solutions

Alotaibi

2023

Not Bot Horti Agrobo

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Climate change poses serious threats to agriculture and food security, and extreme weather events have reduced crop productivity worldwide. Future projections predict that the average global temperature will rise by 2.0 to 6.4 °C and the increase in sea level will be 59 cm by the end of 21st century. The unprecedented rise in temperature has led to an increase in the incidence of heat waves, droughts, floods, and irregular patterns of precipitation. These changes have a dramatic impact on prevailing agricultural cropping systems, productivity, and food security of people regionally and globally. The change in climatic parameters have substantial effects on weeds, diseases, insect, and pests in different ways, and can result in an increase of their geographical distribution, number of generations, and survival during winter. Thus, to sustain the crop production on the eve of climate change is the main challenge. Therefore, adaptation measures are prerequisites to reduce the effects of climatic changes on production of agricultural crops. In this review, a brief insight has been given in the impact of climate change on agriculture and, the future challenges of climate change on the production of crops. In addition, integrated approaches, or recent developments for the improvement of crops such as breeding, transgenic approaches to biotechnology, and functional genomics, agronomic practices, cultivation of climate resilient crops, and nanotechnology for abiotic stress such as drought stress, temperature, heat, and salinity tolerance have also been discussed.

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“…protein, vitamins, dietary fibers, and phytochemicals (Akmal and Goher, 2021;Seleiman et al, 2021b;Taha et al, 2021). In the recent past, climate changes are observed which have affected many crops including wheat with different ways of occurrence in a crop life cycle (Battaglia et al, 2021;Ding et al, 2021;Khan and Akmal, 2021;Kheir et al, 2021). The scarcity of water at the time of sowing has shifted wheat sowing from late October to the end of November and even in December in areas where the crop is sown as a rainfed crop (Anjum, and Arif, 2022).…”

Section: Introduction Introduction Introduction Introductionmentioning

confidence: 99%

Impacts of heat shock on productivity and quality of Triticum aestivum L. at different growth stages

Goher

Alkharabsheh

Seleiman

et al. 2023

Not Bot Horti Agrobo

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The transitional phase of climate change is becoming a threat worldwide. Fluctuations in temperature are frequently observed in the life cycles of field crops. The current study was intended to evaluate heat stress (HS) at sensitive stages on four wheat cultivars’ growth, grain yield, and quality traits during two consecutive seasons. The experiment included four spring wheat cultivars that were exposed to HS durations (i.e., 0, 48, 96 and 144 h) at booting and anthesis stages. Pots were kept in an open-air, and labeled pots were moved to the glasshouse at the respective growth stage. After HS treatments, pots were moved from the glasshouse to the original position in the open air. The results showed that the cultivars differed in yield and grain quality traits, but their collective mean effect was significantly expressed with HS and HS duration (HSd) on the measured traits. Spike length was significantly affected by HS at the anthesis in comparison to those obtained from the control. However, the increase in HSd did not cause a significant effect on spike length compared to other treatments. Spike weight was significantly decreased in plants exposed to HS at booting and anthesis as well as by increasing HSd. In addition, grain weight and numbers were decreased in plants exposed to HS at booting and anthesis stages with a similar pattern by increasing HSd. Moreover, a reduction in amylose content was observed in grains of plants exposed to HS at booting and anthesis stages or when plants as exposed to a longer period of HSd. Nonetheless, amylopectin, wet gluten (WG) and grain N (GN) showed an increase in plants exposed to HS at booting and anthesis stages and/or extending HSd. This study concludes that plants exposed to different HS treatments during the life cycle had lower values for spike length, grains weight, and grains number per spike including amylose content in comparison to those obtained from the control. The decrease was significantly noted in the yield and grain quality of wheat when plants were exposed to HS at the booting stage in comparison to those exposed to HS at anthesis.

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Calibration and Validation of AQUACROP and APSIM Models to Optimize Wheat Yield and Water Saving in Arid Regions

Cited by 33 publications

References 60 publications

Calibration of a crop growth model in APSIM for 15 publicly available corn hybrids in North America

Calibration of a crop growth model in APSIM for 15 publicly available corn hybrids in North America

Climate change, its impact on crop production, challenges, and possible solutions

Impacts of heat shock on productivity and quality of Triticum aestivum L. at different growth stages

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