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首页> 外文会议>International Conference on Environmental and Computer Science >A Computer Model for Simulating Sunflower Growth and Yield
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A Computer Model for Simulating Sunflower Growth and Yield

机译：模拟向日葵成长和产量的计算机模型

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Sunflower (Helianthus annus L.) is one of the most important oil seed crops in Iran. In spite of very progressing in production mechanization and varieties breeding, weather is still one of the most important determining factors for growth and production crops. Under optimal water and nutrient supply, radiation and temperature are two important factors for determining of production and dry matter accumulation. Quantification of the effect of radiation and effect of temperature on growth and yield of sunflower is important in selecting this crop for different agro-climatic situation. Environmental limitations in production at each regional can be evaluated using a crop simulation model and prolong weather data. The model operates simulation daily and it has four segments include simulation of leaf area index, light interception, dry matter production and seed yield. For testing model, the capability of the model was determined to predicting of leaf area index and accumulated dry matter production. Paired data of observed and simulated for both leaf area index and accumulated dry matter were tested by t test. Between paired data were not significant (a=0.05). Also linear regression between observed and simulated values for leaf area index and accumulated dry matter explained more than 95% of variability.
机译：向日葵（Helianthus Annus L.）是伊朗最重要的石油种子之一。尽管生产机械化和品种繁殖非常进展，但天气仍然是增长和生产作物最重要的决定因素之一。在最佳水和营养供应下，辐射和温度是用于确定生产和干物质积累的两个重要因素。定量辐射效果的效果和温度对向日葵的生长和产量的影响对于选择这种作物进行不同农业气候局势至关重要。可以使用作物仿真模型和延长天气数据来评估每个区域的生产环境限制。该模型每日运行仿真，它有四个部分，包括叶面积指数，光截止，干物质产生和种子产量的模拟。对于测试模型，确定模型的能力以预测叶面积指数和累积的干物质产生。通过T检测测试叶面积指数和累积干物质的观察和模拟的成对数据。成对数据之间不显着（a = 0.05）。在叶面积指数和累积的干物质之间观察和模拟值之间的线性回归解释了超过95％的可变性。

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