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Identification of factors affecting rice yield gap in southwest China: An experimental study

Knowledge about the relative importance of influencing-factors on rice yield gap is crucial to rice production, especially in southwestern China where topography is extremely complicated. In the current study, the data of rice yield from a total of 76 experiments were collected in 2008 and 2009 in C...

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Autores principales: Ran, Yuanyuan, Chen, Hui, Ruan, Dinglun, Liu, Hongbin, Wang, Shuai, Tang, Xiaoping, Wu, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235302/
https://www.ncbi.nlm.nih.gov/pubmed/30427875
http://dx.doi.org/10.1371/journal.pone.0206479
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author Ran, Yuanyuan
Chen, Hui
Ruan, Dinglun
Liu, Hongbin
Wang, Shuai
Tang, Xiaoping
Wu, Wei
author_facet Ran, Yuanyuan
Chen, Hui
Ruan, Dinglun
Liu, Hongbin
Wang, Shuai
Tang, Xiaoping
Wu, Wei
author_sort Ran, Yuanyuan
collection PubMed
description Knowledge about the relative importance of influencing-factors on rice yield gap is crucial to rice production, especially in southwestern China where topography is extremely complicated. In the current study, the data of rice yield from a total of 76 experiments were collected in 2008 and 2009 in Chongqing, southwest China. For each location, two treatments with fertilizer and without fertilizer were carried out, each treatment was performed with three replications, and yield gap was calculated using fertilized yield minus unfertilized yield. Seventeen influencing-factors including variety, fertilization, climate, terrain, and soil properties were obtained at each location. Regression tree (RT) model were employed to investigate relative important of influencing-factors to rice yield gap variability. The result of Pearson correlation analysis suggested yield gap of rice was positively correlated with sunshine hours, phosphorous and potassium fertilizers, while negatively correlated with soil available nitrogen content. The results of RT showed that the selected influencing-factors explained about 74.1% of rice yield gap variation. Meanwhile, the result also indicated variety followed by others had more influence on rice yield gap variation. Our findings analyzed by regression model at a regional scale suggested that more precise fertilization recommendation should be formulated based on comprehensive factors (e.g., soil, climate, terrain, variety), which reasonably guided farmer and government for rice production.
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spelling pubmed-62353022018-12-01 Identification of factors affecting rice yield gap in southwest China: An experimental study Ran, Yuanyuan Chen, Hui Ruan, Dinglun Liu, Hongbin Wang, Shuai Tang, Xiaoping Wu, Wei PLoS One Research Article Knowledge about the relative importance of influencing-factors on rice yield gap is crucial to rice production, especially in southwestern China where topography is extremely complicated. In the current study, the data of rice yield from a total of 76 experiments were collected in 2008 and 2009 in Chongqing, southwest China. For each location, two treatments with fertilizer and without fertilizer were carried out, each treatment was performed with three replications, and yield gap was calculated using fertilized yield minus unfertilized yield. Seventeen influencing-factors including variety, fertilization, climate, terrain, and soil properties were obtained at each location. Regression tree (RT) model were employed to investigate relative important of influencing-factors to rice yield gap variability. The result of Pearson correlation analysis suggested yield gap of rice was positively correlated with sunshine hours, phosphorous and potassium fertilizers, while negatively correlated with soil available nitrogen content. The results of RT showed that the selected influencing-factors explained about 74.1% of rice yield gap variation. Meanwhile, the result also indicated variety followed by others had more influence on rice yield gap variation. Our findings analyzed by regression model at a regional scale suggested that more precise fertilization recommendation should be formulated based on comprehensive factors (e.g., soil, climate, terrain, variety), which reasonably guided farmer and government for rice production. Public Library of Science 2018-11-14 /pmc/articles/PMC6235302/ /pubmed/30427875 http://dx.doi.org/10.1371/journal.pone.0206479 Text en © 2018 Ran et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ran, Yuanyuan
Chen, Hui
Ruan, Dinglun
Liu, Hongbin
Wang, Shuai
Tang, Xiaoping
Wu, Wei
Identification of factors affecting rice yield gap in southwest China: An experimental study
title Identification of factors affecting rice yield gap in southwest China: An experimental study
title_full Identification of factors affecting rice yield gap in southwest China: An experimental study
title_fullStr Identification of factors affecting rice yield gap in southwest China: An experimental study
title_full_unstemmed Identification of factors affecting rice yield gap in southwest China: An experimental study
title_short Identification of factors affecting rice yield gap in southwest China: An experimental study
title_sort identification of factors affecting rice yield gap in southwest china: an experimental study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235302/
https://www.ncbi.nlm.nih.gov/pubmed/30427875
http://dx.doi.org/10.1371/journal.pone.0206479
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