Difference between Attainable Yield and Farmers’ Actual Yield in Rice in Japan
We developed yield-estimation models based on yield trial data for the eight main-consumed rice cultivars in Japan using environmental variables, including soil available N, N fertilizers, air temperature, and solar radiation. The difference between attainable yield and farmers’ actual yield was det...
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Veröffentlicht in: | Japanese Journal of Crop Science 2022/01/05, Vol.91(1), pp.28-38 |
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creator | Ohsumi, Akihiro Morioka, Ryoko Ebato, Munehiro Nakagawa, Hiroshi Yoshida, Hiroe |
description | We developed yield-estimation models based on yield trial data for the eight main-consumed rice cultivars in Japan using environmental variables, including soil available N, N fertilizers, air temperature, and solar radiation. The difference between attainable yield and farmers’ actual yield was determined by comparing the model-estimated values and the yield in the statistical yearbook of Ministry of Agriculture, Forestry and Fisheries (MAFF). Yield-estimation models were developed using three calculation methods, i.e., partial least square regression (PLS), random forests (RF), and XGBoost (XGB); and, the effect of data-cleansing treatments was evaluated. The goodness of model fitting for PLS was improved by the data-cleansing treatment, whereas that for RF and XGB was decreased. The calculation method to explain yield variation better differed with the variety. The average rank of feature importance of daily minimum temperature during the reproductive period was the highest in RF and XGB. The significant positive correlation between the model-estimated values and yield in the statistical yearbook of MAFF indicates that these models can explain the yield response to different environments, and shows that the attainable yield is 55.4–57.3 kg 10 a–1 higher than the farmers’ actual yield in Japan. |
doi_str_mv | 10.1626/jcs.91.28 |
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The significant positive correlation between the model-estimated values and yield in the statistical yearbook of MAFF indicates that these models can explain the yield response to different environments, and shows that the attainable yield is 55.4–57.3 kg 10 a–1 higher than the farmers’ actual yield in Japan.</description><identifier>ISSN: 0011-1848</identifier><identifier>EISSN: 1349-0990</identifier><identifier>DOI: 10.1626/jcs.91.28</identifier><language>eng ; jpn</language><publisher>Tokyo: CROP SCIENCE SOCIETY OF JAPAN</publisher><subject>Air temperature ; Attainable yield ; Crop yield ; Cultivars ; Farmers ; Farmers’ yield ; Fertilizers ; Fisheries ; Forestry ; PLS ; Random forests ; Rice ; Soil fertility ; Soil temperature ; Solar radiation ; Statistical analysis ; Statistics ; XGBoost ; Yield estimation</subject><ispartof>Japanese Journal of Crop Science, 2022/01/05, Vol.91(1), pp.28-38</ispartof><rights>2022 by The Crop Science Society of Japan</rights><rights>Copyright Japan Science and Technology Agency 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2208-fde381ca54b3c1768806c7b72cca63cc81c4e8c9fb3148c471526ef439c29f933</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,1879,27911,27912</link.rule.ids></links><search><creatorcontrib>Ohsumi, Akihiro</creatorcontrib><creatorcontrib>Morioka, Ryoko</creatorcontrib><creatorcontrib>Ebato, Munehiro</creatorcontrib><creatorcontrib>Nakagawa, Hiroshi</creatorcontrib><creatorcontrib>Yoshida, Hiroe</creatorcontrib><title>Difference between Attainable Yield and Farmers’ Actual Yield in Rice in Japan</title><title>Japanese Journal of Crop Science</title><addtitle>Jpn. J. Crop Sci.</addtitle><description>We developed yield-estimation models based on yield trial data for the eight main-consumed rice cultivars in Japan using environmental variables, including soil available N, N fertilizers, air temperature, and solar radiation. The difference between attainable yield and farmers’ actual yield was determined by comparing the model-estimated values and the yield in the statistical yearbook of Ministry of Agriculture, Forestry and Fisheries (MAFF). Yield-estimation models were developed using three calculation methods, i.e., partial least square regression (PLS), random forests (RF), and XGBoost (XGB); and, the effect of data-cleansing treatments was evaluated. The goodness of model fitting for PLS was improved by the data-cleansing treatment, whereas that for RF and XGB was decreased. The calculation method to explain yield variation better differed with the variety. The average rank of feature importance of daily minimum temperature during the reproductive period was the highest in RF and XGB. The significant positive correlation between the model-estimated values and yield in the statistical yearbook of MAFF indicates that these models can explain the yield response to different environments, and shows that the attainable yield is 55.4–57.3 kg 10 a–1 higher than the farmers’ actual yield in Japan.</description><subject>Air temperature</subject><subject>Attainable yield</subject><subject>Crop yield</subject><subject>Cultivars</subject><subject>Farmers</subject><subject>Farmers’ yield</subject><subject>Fertilizers</subject><subject>Fisheries</subject><subject>Forestry</subject><subject>PLS</subject><subject>Random forests</subject><subject>Rice</subject><subject>Soil fertility</subject><subject>Soil temperature</subject><subject>Solar radiation</subject><subject>Statistical analysis</subject><subject>Statistics</subject><subject>XGBoost</subject><subject>Yield estimation</subject><issn>0011-1848</issn><issn>1349-0990</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNo90M1KAzEQB_AgCpbag2-w4MnD1nw1m4CXUq0fFBTRg6eQnU50yzatyRbx5mv4ej6JW7b2NDDzmxn4E3LK6JApri4WkIaGDbk-ID0mpMmpMfSQ9ChlLGda6mMySKkqKaVGKC1MjzxeVd5jxACYldh8IoZs3DSuCq6sMXutsJ5nLsyzqYtLjOn3-ycbQ7Nx9W5Wheypapfbeu_WLpyQI-_qhINd7ZOX6fXz5DafPdzcTcazHDinOvdzFJqBG8lSACuU1lRBURYcwCkB0M4kajC-FExqkAUbcYVeCgPceCNEn5x1d9dx9bHB1NjFahND-9JyJRUbFZpv1XmnIK5SiujtOlZLF78so3abmW0zs4ZZrlt72dlFatwb7qWLTQU1_kvW8X0b3l20GMQfKUZ0hA</recordid><startdate>20220105</startdate><enddate>20220105</enddate><creator>Ohsumi, Akihiro</creator><creator>Morioka, Ryoko</creator><creator>Ebato, Munehiro</creator><creator>Nakagawa, Hiroshi</creator><creator>Yoshida, Hiroe</creator><general>CROP SCIENCE SOCIETY OF JAPAN</general><general>Japan Science and Technology Agency</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7ST</scope><scope>7T7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>SOI</scope></search><sort><creationdate>20220105</creationdate><title>Difference between Attainable Yield and Farmers’ Actual Yield in Rice in Japan</title><author>Ohsumi, Akihiro ; Morioka, Ryoko ; Ebato, Munehiro ; Nakagawa, Hiroshi ; Yoshida, Hiroe</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2208-fde381ca54b3c1768806c7b72cca63cc81c4e8c9fb3148c471526ef439c29f933</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng ; jpn</language><creationdate>2022</creationdate><topic>Air temperature</topic><topic>Attainable yield</topic><topic>Crop yield</topic><topic>Cultivars</topic><topic>Farmers</topic><topic>Farmers’ yield</topic><topic>Fertilizers</topic><topic>Fisheries</topic><topic>Forestry</topic><topic>PLS</topic><topic>Random forests</topic><topic>Rice</topic><topic>Soil fertility</topic><topic>Soil temperature</topic><topic>Solar radiation</topic><topic>Statistical analysis</topic><topic>Statistics</topic><topic>XGBoost</topic><topic>Yield estimation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ohsumi, Akihiro</creatorcontrib><creatorcontrib>Morioka, Ryoko</creatorcontrib><creatorcontrib>Ebato, Munehiro</creatorcontrib><creatorcontrib>Nakagawa, Hiroshi</creatorcontrib><creatorcontrib>Yoshida, Hiroe</creatorcontrib><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Japanese Journal of Crop Science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ohsumi, Akihiro</au><au>Morioka, Ryoko</au><au>Ebato, Munehiro</au><au>Nakagawa, Hiroshi</au><au>Yoshida, Hiroe</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Difference between Attainable Yield and Farmers’ Actual Yield in Rice in Japan</atitle><jtitle>Japanese Journal of Crop Science</jtitle><addtitle>Jpn. J. Crop Sci.</addtitle><date>2022-01-05</date><risdate>2022</risdate><volume>91</volume><issue>1</issue><spage>28</spage><epage>38</epage><pages>28-38</pages><issn>0011-1848</issn><eissn>1349-0990</eissn><abstract>We developed yield-estimation models based on yield trial data for the eight main-consumed rice cultivars in Japan using environmental variables, including soil available N, N fertilizers, air temperature, and solar radiation. The difference between attainable yield and farmers’ actual yield was determined by comparing the model-estimated values and the yield in the statistical yearbook of Ministry of Agriculture, Forestry and Fisheries (MAFF). Yield-estimation models were developed using three calculation methods, i.e., partial least square regression (PLS), random forests (RF), and XGBoost (XGB); and, the effect of data-cleansing treatments was evaluated. The goodness of model fitting for PLS was improved by the data-cleansing treatment, whereas that for RF and XGB was decreased. The calculation method to explain yield variation better differed with the variety. The average rank of feature importance of daily minimum temperature during the reproductive period was the highest in RF and XGB. The significant positive correlation between the model-estimated values and yield in the statistical yearbook of MAFF indicates that these models can explain the yield response to different environments, and shows that the attainable yield is 55.4–57.3 kg 10 a–1 higher than the farmers’ actual yield in Japan.</abstract><cop>Tokyo</cop><pub>CROP SCIENCE SOCIETY OF JAPAN</pub><doi>10.1626/jcs.91.28</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Air temperature Attainable yield Crop yield Cultivars Farmers Farmers’ yield Fertilizers Fisheries Forestry PLS Random forests Rice Soil fertility Soil temperature Solar radiation Statistical analysis Statistics XGBoost Yield estimation |
title | Difference between Attainable Yield and Farmers’ Actual Yield in Rice in Japan |
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