نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار گروه امور زراعی دانشکده کشاورزی و منابع طبیعی دانشگاه گنبد کاووس
2 محقق مؤسسه تحقیقات پنبه کشور،
3 محقق مؤسسه تحقیقات پنبه کشور
4 دانشجوی دکتری اکولوژی گیاهان زراعی
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Background and purpose: Cotton is the most important natural fiber crop globally and in Iran, where approximately 90,000 hectares are cultivated annually. The main cotton-producing provinces include Razavi Khorasan, Fars, South Khorasan, Golestan, North Khorasan, Semnan, and Isfahan. Reliable crop simulation models are valuable tools for assessing crop performance under diverse environmental and management conditions. This study aimed to evaluate the SSM-iCrop2 model for simulating cotton phenological development and growth under the environmental conditions of Bandargaz city, Golestan province. In the SSM-iCrop2 model, various aspects of plant growth and development are represented through phenological subprograms. The model operates on a daily time step and requires detailed weather data (maximum and minimum temperature, radiation, and precipitation) along with agricultural management information (planting date and genotype).
Materials and methods: To evaluate the model’s ability to simulate the developmental stages of newly introduced cotton varieties, a split-plot experiment based on a randomized complete block design with three replications was conducted at the Bandargaz Cotton Research Station during two growing seasons (2021–2022). The main factor was three planting dates, and the sub-factor consisted of six cotton genotypes. Each plot consisted of five 6-meter planting rows, with one non-planted row between treatments to minimize border effects. Model performance was evaluated by comparing simulated and observed values using root mean square error (RMSE), coefficient of variation (CV), correlation coefficient (R), and the proportion of data points falling within a ±15% deviation from the 1:1 line.
Results: Field observations showed that days to flowering ranged from 52 to 73 days, with a mean of 62.94 days, which was comparable to the model-predicted mean of 64.33 days. The RMSE for days to budding was 8.73 days, with a CV of 20.3% and a correlation coefficient of 0.76, indicating good agreement between simulated and observed values. For yield, the RMSE was 57.43 g m⁻², representing 19.7% of the observed mean yield. The correlation coefficient for yield was 0.89, with 95% of the simulated values falling within ±15% of the 1:1 line. These findings confirm the model’s accuracy in simulating both phenological stages and yield performance
Conclusion: The results demonstrated that the SSM-iCrop2 model provides acceptable accuracy for predicting cotton developmental stages, including budding, flowering, and ripening, as well as total yield under the climatic conditions of Bandargaz. The majority of simulated points were within the reliable range of ±15% of the 1:1 line, confirming the model’s effectiveness and robustness in estimating crop parameters. Therefore, SSM-iCrop2 can be recommended as a practical tool for analyzing cotton productivity and for assessing the effects of environmental variation, management practices, and genetic factors in major cotton-growing regions of Iran.
کلیدواژه‌ها [English]
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