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      Robustly forecasting maize yields in Tanzania based on climatic predictors

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          Abstract

          Seasonal yield forecasts are important to support agricultural development programs and can contribute to improved food security in developing countries. Despite their importance, no operational forecasting system on sub-national level is yet in place in Tanzania. We develop a statistical maize yield forecast based on regional yield statistics in Tanzania and climatic predictors, covering the period 2009–2019. We forecast both yield anomalies and absolute yields at the sub-national scale about 6 weeks before the harvest. The forecasted yield anomalies (absolute yields) have a median Nash–Sutcliffe efficiency coefficient of 0.72 (0.79) in the out-of-sample cross validation, which corresponds to a median root mean squared error of 0.13 t/ha for absolute yields. In addition, we perform an out-of-sample variable selection and produce completely independent yield forecasts for the harvest year 2019. Our study is potentially applicable to other countries with short time series of yield data and inaccessible or low quality weather data due to the usage of only global climate data and a strict and transparent assessment of the forecasting skill.

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          Regression Shrinkage and Selection Via the Lasso

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            River flow forecasting through conceptual models part I — A discussion of principles

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              • Record: found
              • Abstract: not found
              • Article: not found

              The Split-Apply-Combine Strategy for Data Analysis

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                Author and article information

                Contributors
                laudien@pik-potsdam.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 November 2020
                12 November 2020
                2020
                : 10
                : 19650
                Affiliations
                [1 ]GRID grid.4556.2, ISNI 0000 0004 0493 9031, Potsdam Institute for Climate Impact Research (PIK), ; P.O. Box 60 12 03, 14412 Potsdam, Germany
                [2 ]GRID grid.460789.4, ISNI 0000 0004 4910 6535, National Research Institute for Agriculture, , Food and Environment (INRAE), UMR 518 AgroParisTech Université Paris-Saclay, ; 16 rue Claude Bernard, 75231 Paris Cedex 05, France
                [3 ]GRID grid.5155.4, ISNI 0000 0001 1089 1036, Agroecosystem Analysis and Modelling, Faculty of Organic Agricultural Sciences, , University of Kassel, ; Mönchebergstraße 19, 34109 Kassel, Germany
                Article
                76315
                10.1038/s41598-020-76315-8
                7665066
                5422e87d-d76b-4d16-9fce-3b0c39e78b8f
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 June 2020
                : 27 October 2020
                Funding
                Funded by: German Ministry for Foreign Affairs
                Funded by: Agence nationale de la recherche (ANR)
                Funded by: International Climate Initiative (IKI)
                Funded by: Projekt DEAL
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                climate sciences,climate change,projection and prediction,plant sciences
                Uncategorized
                climate sciences, climate change, projection and prediction, plant sciences

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