Spatial distribution of Phoma leaf spot of coffee and relationship with environmental and host variables

被引:0
|
作者
Silva, Humberson Rocha [1 ]
Pozza, Edson Ampelio [2 ]
de Freitas, Aurivan Soares [3 ]
Freitas, Marcelo Loran de Oliveira
Alves, Marcelo de Carvalho [2 ,4 ]
Barbosa Junior, Mauro Peraro [2 ]
机构
[1] Univ Fed Rural Pernambuco, Recife, PE, Brazil
[2] Univ Fed Lavras, Lavras, MG, Brazil
[3] Univ Fed Rural Rio De Janeiro UFRRJ, BR-23890000 Seropedica, Rio De Janeiro, Brazil
[4] Inst Fed Minas Gerais, Campus Bambui, Bambui, MG, Brazil
来源
REVISTA DE AGRICULTURA NEOTROPICAL | 2024年 / 11卷 / 03期
关键词
Coffea arabica L; Altitude; Geostatistics; Plant mineral nutrition; SCALE;
D O I
10.32404/rean.v11i3.8565
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The objective of this study was to evaluate the spatial distribution of Phoma leaf spot of coffee and its relationship with the environmental variables altitude, soil texture, and mineral nutrients. In addition, the relationship between disease and foliar nutrients, leafing, and plant production was evaluated. The study was carried out in a 7.65 ha coffee plantation for two years. A total of 86 points were georeferenced in this area. The incidence and severity of the disease were assessed monthly, and the data were transformed into annual values of "Area Under the Incidence Progress Curve" (AUIPC) and "Area Under the Severity Progress Curve" (AUSPC) of the disease. Likewise, the monthly data for the leafing were transformed into annual values of "Area Under the Leafing Progress Curve" (AULPC). Environmental and host variables significantly correlated with the AUIPC were subjected to geostatistical modeling. Higher AUIPC and AUSPC were observed in the second year of the study. The altitude, Prem and Ca present in the soil, as well as the P and N present in the leaves, showed a positive correlation with the AUIPC. The K, Cu, and Mn present in the leaves, the AULPC and the production were negatively correlated with this variable. The exponential semivariogram model was the most appropriate to model the spatial autocorrelation of the variables analyzed, except for altitude.
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页数:10
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