{"title":"通过田间试验和模型模拟确定最佳种植密度和施氮量。","authors":"Bizuwork Tafes Desta, Sisay Eshetu Tesema, Gebrekidan Feleke Mekuria, Almaz Meseret Gezahegn, Alemayehu Zemede Lemma","doi":"10.1038/s41598-025-95862-6","DOIUrl":null,"url":null,"abstract":"<p><p>Poor crop management practices are key factors leading to a significant reduction in durum wheat yield in the central highlands of Ethiopia. The aim of this study was to determine optimum plant density and nitrogen rate that increase durum wheat productivity while reducing environmental impacts. A combination of data from field experiments conducted from 2017 to 2020 under rainfed conditions and simulation data of CERES-Wheat model were used for this study. The CERES-Wheat model was calibrated for Utuba cultivar from 3-years (2017-2019) field experiment data. The model was further evaluated with the experimental data conducted during the 2020 cropping season under four plant densities and four nitrogen fertilizer rates. Because of differences in temperature and rainfall patterns during the potential growing season, seasonal analysis was used to determine the optimum plant density and N rate using 37 years (1985-2022) of historical weather data. The simulation results suggested that 275 plants m<sup>-2</sup> with an application of 200 kg ha<sup>-1</sup> N increased grain yield, improved nitrogen use, and produced the highest economic return while minimizing environmental risk under rainfed conditions. Compared with the current plant density (175 plants m<sup>-2</sup>) and N fertilizer (100 kg ha<sup>-1</sup>) an increase in plant density to 275 plants m⁻<sup>2</sup> with 200 kg ha⁻<sup>1</sup> N resulted in a 49% increase in grain yield by about 49%, N use efficiency by 23% with the highest net return (2114 US$ ha<sup>-1</sup>). In general, this study showed that the CERES-Wheat model can be a promising tool for providing crop management recommendations under rainfed durum wheat farming.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"26021"},"PeriodicalIF":3.9000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12271441/pdf/","citationCount":"0","resultStr":"{\"title\":\"Determining optimum plant density and nitrogen rate using field experiment and model simulation.\",\"authors\":\"Bizuwork Tafes Desta, Sisay Eshetu Tesema, Gebrekidan Feleke Mekuria, Almaz Meseret Gezahegn, Alemayehu Zemede Lemma\",\"doi\":\"10.1038/s41598-025-95862-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Poor crop management practices are key factors leading to a significant reduction in durum wheat yield in the central highlands of Ethiopia. The aim of this study was to determine optimum plant density and nitrogen rate that increase durum wheat productivity while reducing environmental impacts. A combination of data from field experiments conducted from 2017 to 2020 under rainfed conditions and simulation data of CERES-Wheat model were used for this study. The CERES-Wheat model was calibrated for Utuba cultivar from 3-years (2017-2019) field experiment data. The model was further evaluated with the experimental data conducted during the 2020 cropping season under four plant densities and four nitrogen fertilizer rates. Because of differences in temperature and rainfall patterns during the potential growing season, seasonal analysis was used to determine the optimum plant density and N rate using 37 years (1985-2022) of historical weather data. The simulation results suggested that 275 plants m<sup>-2</sup> with an application of 200 kg ha<sup>-1</sup> N increased grain yield, improved nitrogen use, and produced the highest economic return while minimizing environmental risk under rainfed conditions. Compared with the current plant density (175 plants m<sup>-2</sup>) and N fertilizer (100 kg ha<sup>-1</sup>) an increase in plant density to 275 plants m⁻<sup>2</sup> with 200 kg ha⁻<sup>1</sup> N resulted in a 49% increase in grain yield by about 49%, N use efficiency by 23% with the highest net return (2114 US$ ha<sup>-1</sup>). In general, this study showed that the CERES-Wheat model can be a promising tool for providing crop management recommendations under rainfed durum wheat farming.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"15 1\",\"pages\":\"26021\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12271441/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-025-95862-6\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-95862-6","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
不良的作物管理做法是导致埃塞俄比亚中部高地硬粒小麦产量大幅下降的关键因素。本研究旨在确定在提高硬粒小麦产量的同时减少环境影响的最佳种植密度和施氮量。本研究采用2017 - 2020年旱作条件下的田间试验数据和CERES-Wheat模型的模拟数据相结合。利用3年(2017-2019)田间试验数据,对Utuba品种的CERES-Wheat模型进行了校准。利用2020年种植季4种密度和4种氮肥施用量下的试验数据,对该模型进行了进一步评价。由于潜在生长季节的温度和降雨模式存在差异,利用1985-2022年37年的历史气象资料,采用季节分析方法确定了最适宜的种植密度和施氮量。模拟结果表明,在雨养条件下,施用200 kg hm -1 N的275株m-2可提高粮食产量,改善氮素利用,在环境风险最小的同时产生最高的经济效益。与目前的种植密度(175株m-2)和施氮(100 kg ha-1)相比,将种植密度增加到275株m-2, 200 kg ha-1 N,粮食产量增加49%,氮素利用效率提高23%,净收益最高(2114美元ha-1)。总的来说,本研究表明,CERES-Wheat模型可以作为一种有前途的工具,为旱作硬粒小麦种植提供作物管理建议。
Determining optimum plant density and nitrogen rate using field experiment and model simulation.
Poor crop management practices are key factors leading to a significant reduction in durum wheat yield in the central highlands of Ethiopia. The aim of this study was to determine optimum plant density and nitrogen rate that increase durum wheat productivity while reducing environmental impacts. A combination of data from field experiments conducted from 2017 to 2020 under rainfed conditions and simulation data of CERES-Wheat model were used for this study. The CERES-Wheat model was calibrated for Utuba cultivar from 3-years (2017-2019) field experiment data. The model was further evaluated with the experimental data conducted during the 2020 cropping season under four plant densities and four nitrogen fertilizer rates. Because of differences in temperature and rainfall patterns during the potential growing season, seasonal analysis was used to determine the optimum plant density and N rate using 37 years (1985-2022) of historical weather data. The simulation results suggested that 275 plants m-2 with an application of 200 kg ha-1 N increased grain yield, improved nitrogen use, and produced the highest economic return while minimizing environmental risk under rainfed conditions. Compared with the current plant density (175 plants m-2) and N fertilizer (100 kg ha-1) an increase in plant density to 275 plants m⁻2 with 200 kg ha⁻1 N resulted in a 49% increase in grain yield by about 49%, N use efficiency by 23% with the highest net return (2114 US$ ha-1). In general, this study showed that the CERES-Wheat model can be a promising tool for providing crop management recommendations under rainfed durum wheat farming.
期刊介绍:
We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections.
Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021).
•Engineering
Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live.
•Physical sciences
Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics.
•Earth and environmental sciences
Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems.
•Biological sciences
Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants.
•Health sciences
The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.