Examinando por Materia "Theobroma cacao."

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A Comparison of Classification Algorithms for Predicting Distinctive Characteristics in Fine Aroma Cocoa Flowers Using WEKA Modeler
(2024-09-24) Tineo Flores, Daniel; Murillo, Yuriko S.; Marin, Mercedes; Gomez Fernandez, Darwin; Taboada, Víctor H.; Goñas Goñas, Malluri; Quiñonez Huatangari, Lenin
The expression of crop functional traits is influenced by environmental and management conditions, which in turn is reflected in genetic diversity. This study employed a data mining approach to determine the functional traits of flowers that influence cocoa diversity. A total of 1,140 flowers from 228 trees were utilized in this study, with 177 representing fine aroma cocoa trees and 51 trees belonging to other commercial cultivars. Three attribute evaluators (InfoGainAttributeEval, CorrelationAttributeEval and GainRatioAttributeEval), and six algorithms (Naive Bayes, Multinomial Logistic Regression, J48, Random Forest, LTM and Simple Logistic) were employed in this study. The findings indicated that the GainRatioAttributeEval attribute generator was the most efficacious in discerning the functional trait in cocoa diversity flowers. The algorithms Simple Logistic and LMT were the most accurate and specific, while Naive Bayes was the most efficient in terms of computational complexity for model building. This research provides a comprehensive overview of the use of machine learning to analyze functional traits of flowers that most influence cocoa genetic diversity. It also highlights the need to further improve these models by integrating additional techniques to increase their efficiency and extend the data mining approach to other agricultural sectors.
The Germination and Subsequent Development of Cocoa Seedlings (Theobroma cacao L.) Are Subject to Influence From the Pregerminative Methods Employed
(John Wiley & Sons Ltd., 2025-12-20) Chuquibala Checan, Beimer; Torres de la Cruz, Magdiel; Mendoza Merino, Jani Elisabet; Tineo Flores, Daniel; Arce Inga, Marielita; Álvarez Robledo, Yeltsin Abel; Atalaya Marin, Nilton; Gómez Fernández, Darwin; Goñas Goñas, Malluri
In Peru, cocoa production has increased significantly, thereby establishing a prominent position for this crop in the country's agricultural landscape. The effect of different pregerminative methods on seed germination of cocoa ecotypes and their influence on seedling development in nursery were evaluated. Three cocoa ecotypes were used INDES 24, INDES 31, and INDES 67, and five pregerminative methods were applied to the seeds with mucilage, mucilage removal, tegument removal, water immersion, and immersion in Trichoderma harzianum solution. Parameters such as germination percentage GP, mean germination time GT50, mean germination rate GR50, and plant growth characteristics in terms of cotyledon height, plant height, number of leaves per plant, and stem diameter were evaluated. The results revealed that the treatments INDES 24 removal tegument, INDES 67 removal tegument, INDES 67 water immersion, and INDES 67 immersion in T. harzianum showed the best GPs of 100% at 72 h. Additionally, the INDES 67 tegument removal showed the best mean germination time and rate GT50 and GR50 with 24 h and 8 seeds/24 h, respectively. For growth parameters, INDES 67 mucilage removal showed the highest values for cotyledon height and the number of leaves per plant with 4 cm and 13.33 leaves/plant; for plant height and stem diameter, the treatments INDES 31 tegument removal and INDES 24 mucilage removal obtained the highest average values with 30.21 cm and 6.65 mm, respectively. These findings demonstrate that pregerminative methods significantly impact the germination and growth of cocoa plants. This insight can enhance cocoa propagation practices and improve the success rate of their establishment in the field.