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Item Morphological diversity of arabica coffee (Coffea arabica) by in-situ exploration in three agroecosystems West Java, Indonesia(Editora UFLA, 2025-05-20) Maxiselly, Yudithia; Atiningsih, Fukita Ghaury; Rasiska, Siska; Hutapea, Dedi; Bakti, Citra; Wahyudin, Abdillah Azzam; Maharani, YaniArabica coffee, a type of coffee in high demand, is cultivated in various regions. West Java is a significant contributor to Arabica coffee production in Indonesia. This region has various coffee agroecosystems. The research aims to identify the diversity of West Java Arabica coffee cultivated in different agroecosystems. The research involved observing plantation locations of Arabica coffee in Cimaung, Cilengkrang, and Pangalengan, West Java, in three agroecosystems (agroforestry, intercropping area, and residential area). Fifty-two accessions were found and analyzed using the Shannon diversity index for qualitative characters, Principal Component Analysis (PCA), and Cluster analysis. The Shannon diversity index revealed the range between 0.221 and 1.55; the PCA results show a variability of 43.208% on two main components (PC1-PC2), indicating a wide variation for Arabica coffee accessions. The characteristics of fruit, seed, and leaf qualitative traits were influential in determining diversity. The cluster analysis explained the distribution patterns of agroecosystems and the relationship of each accession. It showed a close relationship between agroforestry and residential areas. The cluster analysis also revealed distinct variations of accessions in the agroforestry and residential area at Cilengkrang compared to others. Based on the results, these findings could potentially be used as basic knowledge to develop a new Arabica coffee clone, especially in West Java.Item Multivariate analysis applied to spray deposition in ground application of phytosanitary products in coffee plants(Associação Brasileira de Engenharia Agrícola, 2021) Palma, Roxanna P.; Cunha, João P. A. R. da; Guimarães, Ednaldo C.; Santana, Denise G. de; Assunção, Heli H. T. deAn adequate combination of factors involved in the technology used for phytosanitary product application contributes to an efficient spray deposition on the target. The objective of this study was to use multivariate analysis to characterize the magnitude of effects and the order of influence of three factors that interfere with the quality of phytosanitary product application in coffee plants. An entirely randomized design was adopted, with four repetitions, using a 2 × 2 × 3 factorial scheme, with two classes of droplets quality (fine and coarse), two application rates (250 and 400 L ha-1), and the use of adjuvants (with no adjuvant or with Fighter® and Aureo® adjuvants). The quality of the application was determined by jointly analyzing the spray deposition on three thirds of leaves, in their internal and external layers, the runoff to soil, coverage, droplet density, relative amplitude, and the volumetric median diameter. The results underwent analysis of variance (ANOVA) to measure the effect sizes (η2). After testing the assumptions of multivariate analysis, clustering and principal component analyses were performed. The class of droplets was found to be the most influential factor in the quality of the phytosanitary product application (spray deposition and runoff to soil). When focusing on spray deposition on leaves, the second-most influential factor was the application rate and the relation between the application rate and the adjuvants. For the other variables, the second-most influential factor was the application rate.Item Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation(Sociedade Brasileira de Ciência do Solo, 2012-03) Silva, Samuel de Assis; Lima, Julião Soares de SouzaThe spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 – 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K + , Ca 2+ , Mg 2+ , Na + , S, Al 3+ , pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characte- ristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.