Abstract Forecasting crop yields, or providing an expectation of ex-ante harvest amounts, is highly relevant to the whole agricultural production chain. Farmers can adapt their management, traders or insurers their pricing schemes, suppliers their stocks, logistic companies their routes, national authorities their food balance sheets to guide import or export and, finally, international aid organizations can mobilize reliefs. Evidence has grown in the literature that such forecasts with a meaningful lead time are possible on various geographic scales and for a broad range of crops. Here, we present a systematic review of the methods applied in end-of-season yield forecasting and three frequently used data sources: weather data, satellite data and crop masks. Our literature database comprises 362 studies (2004–2019) which were evaluated regarding methods, crops, regions, data sources, lead time and performance. Moreover, we present 24 sources of real-time and predictive weather data, 21 sources of remote sensing data and 16 crop masks. Yield forecasting in our literature sample has been performed for 44 crops in 71 countries, also including many non-staple crops, but with an apparent bias in regions and crops. Forecasting performance depends on various factors, including crop, region, method, lead time to harvest and input diversity. Our systematic review supports a broader application of locally successful approaches at larger scales by providing a comprehensive, accessible compendium of necessary information for yield forecasting. We discuss improvement potentials with respect to methodological approaches and available data sources. We additionally suggest standardization procedures for future forecasting studies and encourage studying additional crops and geographic regions. Implications of forecasts for different target groups on different scales and the adaptation towards climate change are also discussed.

中文翻译：

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本地到区域产量预测方法和常用数据资源的系统回顾

摘要 预测作物产量，或提供事前收获量的预期，与整个农业生产链高度相关。农民可以调整他们的管理、贸易商或保险公司的定价方案、供应商的库存、物流公司的路线、国家当局的食品平衡表来指导进出口，最后，国际援助组织可以动员救济。文献中越来越多的证据表明，这种具有有意义提前期的预测可以在不同的地理范围内和广泛的作物范围内进行。在这里，我们系统回顾了季末产量预测中应用的方法和三个常用数据源：天气数据、卫星数据和作物掩码。我们的文献数据库包含 362 项研究（2004-2019 年），这些研究对方法、作物、地区、数据来源、交付时间和性能进行了评估。此外，我们提供了 24 个实时和预测性天气数据源、21 个遥感数据源和 16 个作物掩码。我们的文献样本对 71 个国家/地区的 44 种作物进行了产量预测，其中还包括许多副粮作物，但在区域和作物方面存在明显偏差。预测绩效取决于多种因素，包括作物、地区、方法、收获的提前期和投入的多样性。我们的系统评价通过提供一个全面的、可访问的产量预测必要信息纲要，支持在更大范围内更广泛地应用当地成功的方法。我们讨论了方法论方法和可用数据源方面的改进潜力。我们还建议未来预测研究的标准化程序，并鼓励研究其他作物和地理区域。还讨论了对不同尺度的不同目标群体的预测的影响以及对气候变化的适应。