Samuel de Assis Silva , Railton Oliveira dos Santos , Daniel Marçal de Queiroz , Julião Soares de Souza Lima , Levi Fraga Pajehú , Caique Carvalho Medauar
{"title":"可可栽培管理区划定中的土壤电导率","authors":"Samuel de Assis Silva , Railton Oliveira dos Santos , Daniel Marçal de Queiroz , Julião Soares de Souza Lima , Levi Fraga Pajehú , Caique Carvalho Medauar","doi":"10.1016/j.inpa.2021.04.004","DOIUrl":null,"url":null,"abstract":"<div><p>Apparent electrical conductivity is an important parameter for describing the spatial variability of physical and chemical attributes of the soil and for the delineation of management zones. The objective of this work is to outline management zones for the cocoa cultivation based on the spatial variability of the productivity and the apparent electrical conductivity (ECa) of the soil. Data collection was performed in a regular sample grid containing 120 points in an area cultivated with cocoa trees, located in the municipality of Ilhéus, state of Bahia, Brazil. At each sampling point (cocoa tree), soil samples were collected to determine chemical attributes. Productivity was measured for one year, counting, monthly, the number of fruits, which were classified into off-season cocoa, harvest and annual production. Measurements of the apparent electrical conductivity of the soil were performed at different times of the year using a portable conductivity meter. The data were analyzed using classical statistics and geostatistics. The management zones were delineated using the fuzzy k-means algorithm. The ideal number of class was defined using the fuzziness performance index (FPI) and the entropy of the modified partition (MPE) indexes. The Kappa coefficient was used to validate the management zones, assessing their agreement with the chemical attributes of the soil. The ECa of the soil values presented moderate temporal variation, with maximum amplitude of 19.37<!--> <!-->mS<!--> <!-->m<sup>−1</sup> and minimum of 0.82<!--> <!-->mS<!--> <!-->m<sup>−1</sup> between measurement periods; higher averages of the ECa coincided with the highest levels of water in the soil. The measurements of the ECa of the soil carried out in April and October showed greater correlation with the chemical attributes of the soil, with significant values for 11 and 8 of the 17 attributes evaluated, respectively. The management zones from the ECa measured in April showed: a) reduced number of classes; b) spatial continuity between classes, and; c) agreement from reasonable (kappa between 0.20 and 0.40) to good (kappa > 0.41) with most of the chemical attributes of the soil. The ECa of the soil measured in April is, individually, the variable recommended for the management of soil fertility in tropical areas cultivated with cocoa trees.</p></div>","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"9 3","pages":"Pages 443-455"},"PeriodicalIF":7.7000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.inpa.2021.04.004","citationCount":"3","resultStr":"{\"title\":\"Apparent soil electrical conductivity in the delineation of management zones for cocoa cultivation\",\"authors\":\"Samuel de Assis Silva , Railton Oliveira dos Santos , Daniel Marçal de Queiroz , Julião Soares de Souza Lima , Levi Fraga Pajehú , Caique Carvalho Medauar\",\"doi\":\"10.1016/j.inpa.2021.04.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Apparent electrical conductivity is an important parameter for describing the spatial variability of physical and chemical attributes of the soil and for the delineation of management zones. The objective of this work is to outline management zones for the cocoa cultivation based on the spatial variability of the productivity and the apparent electrical conductivity (ECa) of the soil. Data collection was performed in a regular sample grid containing 120 points in an area cultivated with cocoa trees, located in the municipality of Ilhéus, state of Bahia, Brazil. At each sampling point (cocoa tree), soil samples were collected to determine chemical attributes. Productivity was measured for one year, counting, monthly, the number of fruits, which were classified into off-season cocoa, harvest and annual production. Measurements of the apparent electrical conductivity of the soil were performed at different times of the year using a portable conductivity meter. The data were analyzed using classical statistics and geostatistics. The management zones were delineated using the fuzzy k-means algorithm. The ideal number of class was defined using the fuzziness performance index (FPI) and the entropy of the modified partition (MPE) indexes. The Kappa coefficient was used to validate the management zones, assessing their agreement with the chemical attributes of the soil. The ECa of the soil values presented moderate temporal variation, with maximum amplitude of 19.37<!--> <!-->mS<!--> <!-->m<sup>−1</sup> and minimum of 0.82<!--> <!-->mS<!--> <!-->m<sup>−1</sup> between measurement periods; higher averages of the ECa coincided with the highest levels of water in the soil. The measurements of the ECa of the soil carried out in April and October showed greater correlation with the chemical attributes of the soil, with significant values for 11 and 8 of the 17 attributes evaluated, respectively. The management zones from the ECa measured in April showed: a) reduced number of classes; b) spatial continuity between classes, and; c) agreement from reasonable (kappa between 0.20 and 0.40) to good (kappa > 0.41) with most of the chemical attributes of the soil. 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引用次数: 3
摘要
视电导率是描述土壤理化属性空间变异性和划定管理区域的重要参数。这项工作的目的是根据生产力的空间变异性和土壤的视电导率(ECa)来概述可可种植的管理区域。数据收集是在巴西巴伊亚州ilhsamus市可可树种植区域的一个包含120个点的规则样本网格中进行的。在每个采样点(可可树),收集土壤样品以确定化学属性。生产力是用一年的时间来衡量的,每月计算水果的数量,这些水果被分为淡季可可、收获和年产量。使用便携式电导率仪在一年中的不同时间测量土壤的视电导率。利用经典统计学和地统计学对数据进行分析。采用模糊k-均值算法划定管理区域。利用模糊性能指标(FPI)和改进分区指标(MPE)的熵来定义理想的类数。Kappa系数用于验证管理区域,评估其与土壤化学属性的一致性。土壤值的ECa呈现中等的时间变化,测量周期间最大振幅为19.37 mS m−1,最小振幅为0.82 mS m−1;非洲经委会的平均值越高,土壤中水分含量也越高。在4月和10月进行的土壤ECa测量显示,土壤的化学属性与土壤的相关性较大,17个属性中分别有11个和8个具有显著值。ECa在4月份测量的管理区域显示:a)班级数量减少;B)类间的空间连续性;C)从合理(kappa在0.20和0.40之间)到良好(kappa >0.41)具有土壤的大部分化学特性。4月份测量的土壤ECa是单独推荐用于种植可可树的热带地区土壤肥力管理的变量。
Apparent soil electrical conductivity in the delineation of management zones for cocoa cultivation
Apparent electrical conductivity is an important parameter for describing the spatial variability of physical and chemical attributes of the soil and for the delineation of management zones. The objective of this work is to outline management zones for the cocoa cultivation based on the spatial variability of the productivity and the apparent electrical conductivity (ECa) of the soil. Data collection was performed in a regular sample grid containing 120 points in an area cultivated with cocoa trees, located in the municipality of Ilhéus, state of Bahia, Brazil. At each sampling point (cocoa tree), soil samples were collected to determine chemical attributes. Productivity was measured for one year, counting, monthly, the number of fruits, which were classified into off-season cocoa, harvest and annual production. Measurements of the apparent electrical conductivity of the soil were performed at different times of the year using a portable conductivity meter. The data were analyzed using classical statistics and geostatistics. The management zones were delineated using the fuzzy k-means algorithm. The ideal number of class was defined using the fuzziness performance index (FPI) and the entropy of the modified partition (MPE) indexes. The Kappa coefficient was used to validate the management zones, assessing their agreement with the chemical attributes of the soil. The ECa of the soil values presented moderate temporal variation, with maximum amplitude of 19.37 mS m−1 and minimum of 0.82 mS m−1 between measurement periods; higher averages of the ECa coincided with the highest levels of water in the soil. The measurements of the ECa of the soil carried out in April and October showed greater correlation with the chemical attributes of the soil, with significant values for 11 and 8 of the 17 attributes evaluated, respectively. The management zones from the ECa measured in April showed: a) reduced number of classes; b) spatial continuity between classes, and; c) agreement from reasonable (kappa between 0.20 and 0.40) to good (kappa > 0.41) with most of the chemical attributes of the soil. The ECa of the soil measured in April is, individually, the variable recommended for the management of soil fertility in tropical areas cultivated with cocoa trees.
期刊介绍:
Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining