Examinando por Materia "LDA"

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Antagonistic interaction between zinc and cadmium in cocoa (Theobroma cacao L. var. CCN-51) seedlings amended with rock phosphate
(Frontiers Media SA, 2026-02-12) Díaz Chuquizuta, Henry; Malca Quezada, María Esmilda; Vallejos Torres, Geomar; Cuevas Gimenez, Juan Pablo; Huamaní Yupanqui , Hugo Alfredo; Sánchez Ojanasta, Martín; Solórzano Acosta, Richard Andi; Martínez Zapata, Boris Guillermo
Introduction: In the San Martın region, several studies have reported Cd concentrations in surface soils approaching the upper limit (UL), with mean values ranging from 0.27 to 1.351 mg·kg- ¹. Methods: Cadmium (Cd) transfer to Theobroma cacao (CCN-51) seedlings was evaluated under 12 factorial combinations of phosphate rock (RFP) and foliar zinc sulphate (ZnSO4) applications, using relative uptake (foliar Cd/soil Cd) as the primary response variable. Results: The treatment showing the highest Cd uptake was T4, defined as RFP = 0 mg·kg-1 and ZnSO4 = 527.80 mg·plant-1, with a value of 53.12. The observed range in relative uptake was 33.08 units, indicating substantial variation among management combinations. At the factor-level analysis, the high RFP treatment (114.55 mg·kg- ¹) was associated with an average reduction of approximately 26.5% in relative uptake and lower within-group variability compared to the 0 mg·kg- ¹ level. Interaction plots indicated that the effect of ZnSO4 on nutrient uptake depended on RFP level, with a descending response profile at high RFP concentrations. In parallel, soil correlation analyses identified available phosphorus and pH as the principal modulators of Cd transfer from soil to plant. Leaf-level principal component analysis showed that Zn and K were projected in the opposite direction to P2O5 and Cd, consistent with an ionic balance mechanism regulating Cd accumulation, and achieved an overall classification accuracy of approximately 81%, thereby confirming multivariate separability among treatments. Discussion: Collectively, these integrated results support identifying T4 as the treatment with the highest Cd uptake within the evaluated set. Accordingly, the presence of Zn²+–Cd²+ antagonism can be asserted; however, its expression is strongly influenced by soil pH and, most critically, by the availability of phosphorus derived from RFP.
Mango varietal discrimination using hyperspectral imaging and machine learning
(Springer Nature, 2024-07-29) Castro, Wilson; Tene, Baldemar; Castro, Jorge; Guivin, Alex; Ruesta Campoverde, Nelson Asdrubal; Avila George, Himer
Mango is a highly diverse tropical fruit with numerous varieties that differ in flavor, texture, and chemical composition. Consequently, identifying fraudulent substitutions of mango varieties poses a significant challenge using traditional techniques. Therefore, there is an increasing need for new methods to discriminate between mango varieties. Hyperspectral imaging coupled with machine learning techniques presents a promising approach for varietal discrimination. In this study, mango samples of eleven varieties were collected from a germplasm bank, with four slices obtained from each sample. Hyperspectral images were acquired in the Vis–NIR and NIR ranges for each slice, and spectral profiles were extracted and pretreated. Three discrimination models, linear discriminant analysis, K-nearest neighbor, and artificial neural networks, were implemented and validated using relevant wavelengths selected through a covering array feature selection algorithm. The performance of these models was evaluated using precision, accuracy, and F-score metrics. The average spectral profiles of the studied varieties exhibited a similar behavior with slight differences, which could be used for classification within the evaluated ranges. The optimal number of variables selected to refine the models was 17 for the UV–Vis–NIR range and 21 for the NIR range, with an accuracy ranging between 0.752 and 0.972. This study concludes that hyperspectral imaging combined with machine learning techniques can effectively discriminate between different varieties of mango.