Examinando por Autor "Tineo Flores, Daniel"

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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.
Global perspectives on the biodegradation of LDPE in agricultural systems
(Frontiers Media S.A., 2025-01-06) Mendoza Merino, Jani Elisabet; Tineo Flores, Daniel; Chuquibala Checan, Beimer; Atalaya Marin, Nilton; Taboada Mitma, Victor Hugo; Tafur Culqui, Josué; Tarrillo Julca, Ever; Gómez Fernández, Darwin; Goñas Goñas, Malluri; Reyes Reyes, María Andrea
The increasing use of plastics globally has generated serious environmental and human health problems, particularly in the agricultural sector where low-density polyethylene (LDPE) and other plastics are widely used. Due to its low recycling rate and slow degradation process, LDPE is a major source of pollution. This paper addresses the problem of plastic accumulation in agriculture, focusing on LDPE biodegradation strategies. The studies reviewed include recent data and the methodologies used include state-of-the-art technologies and others that have been used for decades, to monitor and measure the degree of biodegradation that each treatment applied can have, including SEM, GCMS, HPLC, and microscopy. The countries investigating these biodegradation methodologies are identified, and while some countries have been developing them for some years, others have only begun to address this problem in recent years. The use of microorganisms such as bacteria, fungi, algae, and insect larvae that influence its decomposition is highlighted. A workflow is proposed to carry out this type of research. Despite the advances, challenges remain, such as optimizing environmental conditions to accelerate the process and the need for further research that delves into microbial interactions in various environmental contexts.
Holistic sustainability in cattle ranching: A tri-dimensional framework for social, economic, and environmental resilience
(2025-01-08) Tafur Culqui, Josue; Gomez Fernandez, Darwin; Cruz Luis, Juancarlos Alejandro; Taboada Mitma, Victor H.; Quichua Baldeon, Rosalia; Arce Inga, Marielita; Anchayhua, Janella; Rabanal Oyarse, Raul; Goñas Goñas, Malluri; Tineo Flores, Daniel
Sustainability is a multidisciplinary concept that integrates social, economic, and environmental dimensions. To assess sustainability in production systems, this study employed a multidimensional approach, using indicators that reflect these three dimensions. The research focused on understanding the current dynamics of livestock farming by surveying 120 livestock farmers who provided prior consent. Indicators were quantified using a weighted scale, where values close to 10 represented the most desirable conditions, and values near 0 indicated the least desirable. The findings revealed key insights across the three dimensions. Social dimension: The age of the farmer emerged as a significant factor, with agricultural training playing a secondary role. Economic dimension: Annual yield and economic dependency on livestock farming were identified as critical factors y, Environmental dimension: Farm specialization, water availability, and soil erosion were highlighted as essential indicators for sustainable development. Additionally, a positive correlation was observed between these indicators. More experienced producers tended to rely more heavily on livestock farming for their income, achieving higher yields but often at the cost of intensive land use. These results underscore the need for balanced actions to promote sustainability, such as reducing social inequalities, diversifying animal production, supporting ongoing training for farmers, improving water management practices. In conclusion, achieving sustainability in livestock farming requires a holistic approach that balances social, economic, and environmental factors. Addressing these areas can enhance both the sustainability of production systems and the quality of life for livestock farmers.
Integrating remote sensing and in-situ data to determine climate diversity and variability in cocoa systems in the provinces of Jaén and San Ignacio, Cajamarca (NW Perú)
(Elsevier, 2024-12-08) Atalaya Marin, Nilton; Goña Goñas, Malluri; Tineo Flores, Daniel; Chuquibala Checan, Beimer; Arce Inga, Marielita; Tarrillo Julca, Ever; Alvarez Robledo, Yeltsin Abel; Tafur Culqui, Josué; Cabrera Hoyos, Héctor Antonio; Gómez Fernández, Darwin
La falta de información sobre la distribución geográfica de los sistemas de cacao, junto con la diversidad de especies y la influencia de los factores climáticos en los rendimientos, representa desafíos para la gestión agronómica de estas plantaciones y la implementación de políticas agrícolas más efectivas. Este estudio tuvo como objetivo mapear el área de cacao, la diversidad de especies y su respuesta a la variabilidad climática histórica en las provincias de Jaén y San Ignacio, Cajamarca, Perú. Se procesaron datos de PlanetScope y Sentinel-1 en Google Earth Engine utilizando el algoritmo de clasificación Random Forest. Se identificaron 4,338.6 ha de sistemas de monocultivo y agroforestería de cacao, logrando una precisión temática del 85% y un índice kappa de 0.81. Se determinó que Musa sp. predomina en altitudes bajas, mientras que Inga edulis mostró mayor dominio en altitudes más elevadas. La aplicación de datos climáticos y de rendimiento del cacao permitió calcular el índice de anomalía estandarizada, evidenciando el impacto notable de la precipitación en la producción de cacao, especialmente en 2021 y 2022. Este enfoque integrado proporciona una comprensión más profunda de los sistemas agroforestales de cacao, estableciendo una base sólida para la toma de decisiones destinadas a optimizar el rendimiento mediante prácticas agrícolas adaptadas a condiciones climáticas específicas y fomentando la biodiversidad mediante la incorporación de especies nativas.
Morphological, phylogenetic, and genomic evidence reveals the causal agent of thread blight disease of cacao in Peru is a new species of Marasmius in the section Neosessiles, Marasmius infestans sp. nov.
(F1000Research, 2024-01-29) Huamán Pilco, Ángel Fernando; Ramos Carrasco, Tito Ademir; Ernesto Franco, Mario Emilio; Tineo Flores, Daniel; Estrada Cañari, Richard; Romero, Pedro Eduardo; Aguilar Rafael, Vilma; Ramírez Orrego, Lourdes Adriana; Tincopa Marca, Rosalina; Márquez, Fanny Rosario; Oliva Cruz, Manuel; Díaz Valderrama, Jorge Ronny
The thread blight disease (TBD) of cacao (Theobroma cacao) in the department of Amazonas, Peru was recently reported to be caused by Marasmius tenuissimus (Sect. Neosessiles). This same species is known to be the main causal agent of TBD in West Africa. However, some morphological characteristics, such as the presence of rhizomorphs, the almost exclusively white color, and pileus sizes less than 5 mm, among others, differ to the description of M. tenuissimus. Therefore, we aimed to conduct a taxonomic revision of the cacao-TBD causal agent in Peru, by using thorough micro and macro morphological, phylogenetic, and nuclear and mitochondrial genomic approaches. We showed that the causal agent of TBD of cacao in Amazonas, Peru, belongs to a new species, Marasmius infestans sp. nov. This study enriches our knowledge of species in the Sect. Neosessiles, and strongly suggests that the M. tenuissimus species complex is highly diverse.
Multicriteria evaluation and remote sensing approach to identifying degraded soil areas in northwest Peru
(Taylor & Francis Group, 2024-12-23) Arce Inga, Marielita; Atalaya Marin, Nilton; Barboza Castillo, Elgar; Tarrillo Julca, Ever; Chuquibala Checan, Beimer; Tineo Flores, Daniel; Fernandez Zarate, Franklin Hitler; Cruz Luis, Juancarlos Alejandro; Goñas Goñas, Malluri; Gómez Fernández, Darwin
Soil is a vital nonrenewable resource characterized by rapid degradation and slow regeneration processes. In this study, soil degradation in Jaén and San Ignacio was assessed via a multicriteria evaluation approach combined with remote sensing (RS) data. Nine factors were analyzed classified three categories: environmental, topographic, and edaphological factors. The results revealed that the slope (59.07%) was the main influencing factor, followed by land use and land cover (LULC) (56.36%). The degradation map revealed that 83.48% of the area exhibited moderate degradation, 14.49% low degradation, and 1.56% high degradation. The districts of Pomahuaca and San José de Lourdes demonstrated the largest areas of moderate degradation, accounting for 13.71% and 22.54%, respectively. Bellavista and Huarango exhibited the largest areas of very high degradation, accounting for 0.27% and 0.08%, respectively. The (AHP) method and RS data were employed to assess soil degradation, highlighting the need for sustainable soil restoration and conservation strategies.