Examinando por Autor "Alvarez Garcia, Wuesley Yusmein"

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Implementing artificial intelligence to measure meat quality parameters in local market traceability processes
(John Wiley & Sons Inc., 2024-09-20) Alvarez Garcia, Wuesley Yusmein; Mendoza, Laura; Muñoz Vílchez, Yudith Yohany; Casanova Núñez-Melgar, David; Quilcate Pairazaman, Carlos
The application of computer technologies associated with sensors and artificial intelligence (AI) in the quantification and qualification of quality parameters of meat products of various domestic species is an area of research, development, and innovation of great relevance in the agri-food industry. This review covers the most recent advances in this area, highlighting the importance of computer vision, artificial intelligence, and ultrasonography in evaluating quality and efficiency in meat products’ production and monitoring processes. Various techniques and methodologies used to evaluate quality parameters such as colour, water holding capacity (WHC), pH, moisture, texture, and intramuscular fat, among others related to animal origin, breed and handling, are discussed. In addition, the benefits and practical applications of the technology in the meat industry are examined, such as the automation of inspection processes, accurate product classification, traceability, and food safety. While the potential of artificial intelligence associated with sensor development in the meat industry is promising, it is crucial to recognize that this is an evolving field. This technology offers innovative solutions that enable efficient, cost effective, and consumer-oriented production. However, it also underlines the urgent need for further research and development of new techniques and tools such as artificial intelligence algorithms, the development of more sensitive and accurate multispectral sensors, advances in computer vision for 3D image analysis and automated detection, and the integration of advanced ultrasonography with other technologies. Also crucial is the development of autonomous robotic systems for the automation of inspection processes, the implementation of real-time monitoring systems for traceability and food safety, and the creation of intuitive interfaces for human-machine interaction. In addition, the automation of sensory analysis and the optimisation of sustainability and energy efficiency are key areas that require immediate attention to address the current challenges in this agri-food and agri-industrial sector, highlighting and emphasising the importance of ongoing innovation in the field.
Rye production under acid soils and drought conditions: an alternative for the sustainability of high Andean livestock farming in Peru
(MDPI, 2023-07-05) Carrasco Chilón, William Leoncio; Alvarez Garcia, Wuesley Yusmein; Cervantes Peralta, Marieta Eliana; Quilcate Pairazamán, Carlos Enrique; Vásquez Pérez, Héctor Vladimir
The rye (Secale cereale L.) crop shows a high potential to contribute to the sustainability of high Andean livestock because it supports the agroclimatic conditions and acid soils in the Peruvian Andes. The production of green forage, hay, and grain from the rye crop in acid soils was studied with the use of different levels of phosphorus and potassium fertilization in four local rye ecotypes (CBI-001, CSM-001, CJS-001, and CCE-001). The green forage yield (GFY) ranged from 32.35 to 53.62 t ha−1, dry matter from 6.05 to 8.56 t ha−1, and hay from 7.0 to 10.36 t ha−1; nutritional levels ranged from 9.02% to 13.56% protein and 6.50% to 7.75% ash levels, mainly with differences between ecotypes (p < 0.05). No differences existed between fertilization levels for the number of stems per plant, spikes per plant, and grains per ear (p > 0.05). Also, CBI-001 and CCE-001 were superior with 1868.4 and 1797.8 kg ha−1 of grain, respectively (p = 0.0072); the use of 60 kg ha of nitrogen, 120 kg ha−1 of P2O5, and 80 kg ha−1 of K2O gave higher grain and residue yields. The high nutritional value and yield of the rye ecotypes studied in acid soil conditions and without irrigation can be an alternative for livestock feeding and grain production in the rainy season in the Andes as a dual-purpose crop.