基于在阿根廷圣地亚哥德尔埃斯特罗进行的一项后代试验中选择的Prosopis alba Grisebah种群的乳高直径,开发了一种高度估计方法

Q4 Agricultural and Biological Sciences AgriScientia Pub Date : 2019-12-24 DOI:10.31047/1668.298x.v36.n2.24310
Javier Eduardo Frassoni, M. Joseau
{"title":"基于在阿根廷圣地亚哥德尔埃斯特罗进行的一项后代试验中选择的Prosopis alba Grisebah种群的乳高直径,开发了一种高度估计方法","authors":"Javier Eduardo Frassoni, M. Joseau","doi":"10.31047/1668.298x.v36.n2.24310","DOIUrl":null,"url":null,"abstract":"The main objective of this work was to develop a height estimation method of Prosopis alba based on the diameter at breast height (DBH) of populations with superior characteristics selected through a progeny trial located in the INTA Experimental Agricultural Station, Province of Santiago del Estero, Argentina. The progeny trial was established in 2008 and consists of 3,671 individuals (202 families). The registered variables were DBH and total height (TH) of 123 individuals, taken at random from the three blocks that make up the trial. Linear regressions were performed to develop the model that best fits height estimation with all the sampled individuals (AI model) and, also using the data of 7 individuals - the three trees of greater diameter, the three of smaller diameter and an individual of intermediate diameter-, called the reduced height estimation model (RHEM model). AI model and RHEM model were satisfactory to estimate height of the trees based on their DBH in the trial of progenies in Santiago del Estero. However, the RHEM model offers an important saving of time and effort, simplifying the field activity.","PeriodicalId":39278,"journal":{"name":"AgriScientia","volume":"36 1","pages":"89-95"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Development of a height estimation method based on the diameter at breast height of Prosopis alba Grisebach selected populations from a progeny trial in Santiago del Estero, Argentina\",\"authors\":\"Javier Eduardo Frassoni, M. Joseau\",\"doi\":\"10.31047/1668.298x.v36.n2.24310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main objective of this work was to develop a height estimation method of Prosopis alba based on the diameter at breast height (DBH) of populations with superior characteristics selected through a progeny trial located in the INTA Experimental Agricultural Station, Province of Santiago del Estero, Argentina. The progeny trial was established in 2008 and consists of 3,671 individuals (202 families). The registered variables were DBH and total height (TH) of 123 individuals, taken at random from the three blocks that make up the trial. Linear regressions were performed to develop the model that best fits height estimation with all the sampled individuals (AI model) and, also using the data of 7 individuals - the three trees of greater diameter, the three of smaller diameter and an individual of intermediate diameter-, called the reduced height estimation model (RHEM model). AI model and RHEM model were satisfactory to estimate height of the trees based on their DBH in the trial of progenies in Santiago del Estero. However, the RHEM model offers an important saving of time and effort, simplifying the field activity.\",\"PeriodicalId\":39278,\"journal\":{\"name\":\"AgriScientia\",\"volume\":\"36 1\",\"pages\":\"89-95\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AgriScientia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31047/1668.298x.v36.n2.24310\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AgriScientia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31047/1668.298x.v36.n2.24310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 1

摘要

这项工作的主要目的是根据在阿根廷圣地亚哥-德尔埃斯特罗省INTA实验农业站进行的后代试验中选择的具有优良特性的种群的乳高直径(DBH),开发一种白腹蛛的高度估计方法。该子代试验建立于2008年,由3671个个体(202个家族)组成。登记的变量是123个人的DBH和总身高(TH),从组成试验的三个区块中随机抽取。进行了线性回归,以开发出最适合所有采样个体高度估计的模型(AI模型),并使用7个个体的数据——三棵直径较大的树、三棵直径较小的树和一棵直径中等的树——称为减少高度估计模型(RHEM模型)。在Santiago del Estero的后代试验中,AI模型和RHEM模型能够令人满意地根据树木的DBH来估计树木的高度。但是,RHEM模型大大节省了时间和精力,简化了现场活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Development of a height estimation method based on the diameter at breast height of Prosopis alba Grisebach selected populations from a progeny trial in Santiago del Estero, Argentina
The main objective of this work was to develop a height estimation method of Prosopis alba based on the diameter at breast height (DBH) of populations with superior characteristics selected through a progeny trial located in the INTA Experimental Agricultural Station, Province of Santiago del Estero, Argentina. The progeny trial was established in 2008 and consists of 3,671 individuals (202 families). The registered variables were DBH and total height (TH) of 123 individuals, taken at random from the three blocks that make up the trial. Linear regressions were performed to develop the model that best fits height estimation with all the sampled individuals (AI model) and, also using the data of 7 individuals - the three trees of greater diameter, the three of smaller diameter and an individual of intermediate diameter-, called the reduced height estimation model (RHEM model). AI model and RHEM model were satisfactory to estimate height of the trees based on their DBH in the trial of progenies in Santiago del Estero. However, the RHEM model offers an important saving of time and effort, simplifying the field activity.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
AgriScientia
AgriScientia Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
0.30
自引率
0.00%
发文量
0
审稿时长
22 weeks
期刊介绍: AgriScientia es una revista de acceso abierto, de carácter científico-académico, gestionada por el Área de Difusión Científica de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Córdoba, Argentina. La revista recibe artículos en los idiomas español e inglés. El objetivo de esta publicación es la difusión de los resultados de investigaciones de carácter agronómico. Está destinada a investigadores, estudiantes de pregrado, grado y posgrado, profesionales en el área de las ciencias agropecuarias y público en general interesado en las temáticas relacionadas. Su periodicidad es semestral. Los artículos se reciben durante todo el año. Los tipos de documentos que se publican son artículos científicos, comunicaciones y revisiones.
期刊最新文献
Assessment of land use change in the dryland agricultural region of Córdoba, Argentina, between 2000 and 2020 based on NDVI data Impacto ambiental de las aplicaciones de fitosanitarios en producciones ornamentales intensivas en el partido de Moreno, provincia de Buenos Aires Selección de cepas bacterianas con capacidad antifúngica contra fitopatógenos de alfalfa para constituir un consorcio bacteriano Evaluating Nitrogen Release Rates of Commercial Slow-Release Urea Products Using Brix Value Analysis: A Validation Study Comparing Two Methods Aportes a la morfología de semillas de Hibiscus cannabinus L. y ajuste de la prueba de tetrazolio para estimar viabilidad y vigor
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1