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SPATIAL AND TEMPORAL VARIABILITY OF SORGHUM AND CORN YIELD: INTERACTIONS OF BIOTIC AND ABIOTIC FACTORS

机译:高粱和玉米产量的空间和时间变异性:生物和非生物因子的相互作用

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Incomplete understanding of factors affecting spatial and temporal variability of crop yields is one of the reasons for the slow adoption of site-specific farming (SSF). Experiment were designed to describe interactions between biotic and abiotic factors on the spatial variability of grain yield of sorghum and corn and to use this information for managing SSF. Experiments were done using a Low Energy Precision Application (LEPA) irrigation system in 1997,1998, and 1999 for sorghum and in 1998 and 1999 for corn at Halfway, TX. Drought tolerant and susceptible hybrids were grown under high and low water irrigation regimes. Data on plant growth, soil physical properties, soil moisture, pests, and diseases, were collected from geo-referenced points on a30 m grid and analyzed using state-space analysis and stepwise regressions. Water, elevation, soil texture, soil NO3-N, hybrid, plant density, pests and diseases influenced grain yields. The effect of elevation and soil texture on grain yields was seasonally stable and management decisions on variable rate fertilizer and water can be based on this information. The effect of soil moisture, soil NO3-N, hybrid, plant density, pests and diseases on grain yields was seasonally unstable and not easy to predict. The effect of these factors and their interactions with soil physical factors on grain yields can be assessed indirectly through plant growth analysis. Plant height, leaf area index (LAI), and total plant dry matter predicted grain yields of sorghumbetter than that of corn. Information from plant growth analysis can be used for in-season crop management. To successfully implement SSF, biotic and abiotic effects on crop growth and grain yields should be evaluated as a system.
机译:对影响作物产量的空间和时间变异性的因素的不完全理解是慢速采用现场耕作的原因之一(SSF)。实验旨在描述生物和非生物因素与高粱和玉米籽粒产量的空间变异性的相互作用,并使用这些信息管理SSF。在1997,1998,1999年的高粱和1999年,1998年和1999年,在玉米,在玉米,玉米,实验进行了实验。在高水平和低水中灌溉制度下生长耐旱和易感杂种。从A30M网格上的地理参考点收集有关植物生长,土壤物理性质,土壤水分,害虫和疾病的数据,并使用状态空间分析和逐步回归分析。水,海拔,土壤质地,土壤No3-N,杂种,植物密度,害虫和疾病影响谷物产量。升高和土壤质地对粮食产量的影响是季节性稳定的,可变速率肥料和水的管理决策可以基于这些信息。土壤湿度,土壤NO3-N,杂种,植物密度,害虫和污染物产量的影响是季节性不稳定,不容易预测。通过植物生长分析,可以间接评估这些因素及其与土壤物理因素对土壤物理因素的相互作用。植物高度,叶面积指数(LAI),以及总植物干物质预测粮食产量高于玉米。植物生长分析的信息可用于季节性作物管理。为了成功实施SSF,应评估生物和非生物效应作物生长和谷物产量的影响。

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