马产量预测的方法演变:全面审查
Yongxin Lin1,2, Shuang Li1, Shaoguang Duan1
1State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China.
Frontiers in plant science
|August 11, 2023
概括
准确的土豆产量预测对于粮食安全至关重要. 遥感,作物生长模型和人工智能显示出希望,但需要更多的跨品种和领域的数据.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 数据科学数据科学数据科学
背景情况:
- 马 (Solanum tuberosum L.) 是全球的主食作物,需要改善产量预测,以实现粮食安全和经济稳定.
- 准确的作物产量预测支持农业规划,保险和贸易.
- 方法上的进步对于提高土豆生产效率至关重要.
研究的目的:
- 审查土豆产量预测方法的演变.
- 要突出遥感 (RS),作物生长模型 (CGM) 和产量限制因子 (LF) 分析的作用.
- 为未来的土豆产量预测研究提供理论基础.
主要方法:
- 关于土豆产量预测研究的综合文献调查.
- 分析方法,包括遥感 (基于卫星和无人机),作物生长模型和产量限制因素分析.
- 评估人工智能 (AI) 与遥感技术的整合.
主要成果:
- 遥感,特别是基于卫星的遥感,是大规模土豆产量预测和决策支持的关键.
- 作物生长模型是优化管理和应对气候变化影响的有效方法.
- 无人驾驶飞行器 (UAV) 遥感与人工智能相结合,为土豆种植中的精准农业提供了巨大的潜力.
- 目前的研究受限于研究的土豆品种数量和现场样本大小.
结论:
- 预测未来的土豆产量需要来自多个来源的时间序列数据,包括更广泛的品种和更大的田间样本大小.
- 整合基于无人机的RS和AI等先进技术对于精确的土豆管理至关重要.
- 持续的研究对于完善预测准确性和支持可持续的土豆生产至关重要.
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