Alfredo Ruiz-Orta, Atenas Tapia-Rodríguez, Dulce Karen Figueroa-Figueroa, José Francisco Ramírez-Dávila
{"title":"ANALYSIS OF THE SPATIAL ASSOCIATION OF FUMAGINA (Capnodium spp.) AND GREEN SCALE (Coccus viridis) IN COFFEE IN SULTEPEC, MEXICO","authors":"Alfredo Ruiz-Orta, Atenas Tapia-Rodríguez, Dulce Karen Figueroa-Figueroa, José Francisco Ramírez-Dávila","doi":"10.47163/agrociencia.v57i7.2945","DOIUrl":null,"url":null,"abstract":"The coffee crop (Coffea arabica L.) presents phytosanitary problems that can be economically significant if not properly managed, such as green scale (Coccus viridis) and fumagina (Capnodium spp.). Geostatistics is a tool that allows the producer to make optimal, timely, and accurate decisions for the integrated management of these problems. The objective of the research was to analyze the distribution and spatial association of fumagina and green scale in the coffee crop in Sultepec, State of Mexico, Mexico. During the first semester of 2022, random coffee plots were marked and geo-referenced for sampling. Several methods were used to obtain the spatial distribution of fumagina and green scale. The results showed fits of Gaussian, exponential, and mostly spherical geostatistical models, which represent an aggregate distribution and an association of these problems with each other. The estimation of the infested and infected area for both problems was obtained using the ordinary kriging method, revealing the presence of foci of infection and infestation. In plot three, it was identified that these are maintained and increase as the sampling progresses, finding a high degree of dependence and spatial stability. It is concluded that the populations of green scale and fumagina have an r value of 0.70, indicating a high association and correlation between them, which leads to a spatial distribution and possible management of targeted control of these phytosanitary problems and, in turn, sustainable management of the crop.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47163/agrociencia.v57i7.2945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The coffee crop (Coffea arabica L.) presents phytosanitary problems that can be economically significant if not properly managed, such as green scale (Coccus viridis) and fumagina (Capnodium spp.). Geostatistics is a tool that allows the producer to make optimal, timely, and accurate decisions for the integrated management of these problems. The objective of the research was to analyze the distribution and spatial association of fumagina and green scale in the coffee crop in Sultepec, State of Mexico, Mexico. During the first semester of 2022, random coffee plots were marked and geo-referenced for sampling. Several methods were used to obtain the spatial distribution of fumagina and green scale. The results showed fits of Gaussian, exponential, and mostly spherical geostatistical models, which represent an aggregate distribution and an association of these problems with each other. The estimation of the infested and infected area for both problems was obtained using the ordinary kriging method, revealing the presence of foci of infection and infestation. In plot three, it was identified that these are maintained and increase as the sampling progresses, finding a high degree of dependence and spatial stability. It is concluded that the populations of green scale and fumagina have an r value of 0.70, indicating a high association and correlation between them, which leads to a spatial distribution and possible management of targeted control of these phytosanitary problems and, in turn, sustainable management of the crop.