Examinando por Autor "Mamani Cato, Ruben Herberht"

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Addressing challenges in promoting the use of animal-origin textile fibers for mitigating microplastic pollution on earth
(MedCrave Group, 2023-11-27) Frank, Eduardo Narciso; Hick, Michel Victor Hubert; Flores Gutiérrez, Alfonso; Castillo, Maria Flavia; Prieto, Alejandro; Castillo, Melina; Gomez, Maria Betina; Martinez, Adrian; Mamani Cato, Ruben Herberht; Seghetti Frondizi, Diego
The aim of this review is to address the issue of textile-origin microplastics and to provide possible solutions that can be propose through a scientific and development program. The constant expansion of textile production and consumption, driven by population growth and the ubiquity of fast fashion, has triggered environmental contamination resulting from the release of fiber fragments during the washing and use of clothing and household textiles. These fragments, ranging in size from 1 μm to 5 mm, pose a novel source of pollution that not only threatens the health of aquatic animals when ingested but also risks human food safety by infiltrating the food chain. Despite the growing awareness of the environmental impacts of these plastic microfibers (MP) from synthetic textiles, this study departs from conventional actions focused on mitigating microplastic pollution. Instead, it focuses on proposing specific measures to reduce MP emissions and addresses the even greater challenge of replacing these plastic microfibers with animal-origin textile fibers. This approach emerges as a promising and sustainable alternative to counteract the negative environmental impact of the contemporary fashion industry. The essence of this challenge lies in determining the competitiveness of animal-origin textile fibers against MP. To achieve this goal, specific actions are proposed, including the need to reduce both the environmental impact and costs associated with processing animal fibers. The study also emphasizes the importance of effectively highlighting the biological and textile advantages of these fibers to encourage their acceptance and adoption in the competitive textile market. This project addresses concrete strategies to promote the use of animal-origin textile fibers. It suggests optimizing the cleaning process and genetically improving these fibers, considering key aspects such as quality and color. The research also highlights the potential contribution to sustainability certification and well-being associated with the use of animal-origin textile fibers, providing a solid foundation for their adoption in the textile industry. In conclusion, this work not only departs from traditional measures focused on microplastics to address MP release but ventures into more ambitious territory by proposing increased use of animal-origin textile fibers as a path to a more sustainable fashion. Specific actions are outlined to enhance the competitiveness of these fibers in the current market, emphasizing their potential contribution to reducing textile pollution and thus strengthening the transition to more environmentally responsible practices in the fashion industry.
Hierarchical Bayesian modeling for comparing nonlinear functions and estimating heritability of growth curve parameters in llamas
(Elsevier B.V. en representación de KeAi Communications Co. Ltd., 2026-09-07) Canaza Cayo, Ali William; Mamani Cato, Ruben Herberht; Rodríguez Huanca, Francisco Halley; Churata Huacani, Roxana; Cardenas Minaya, Oscar Efrain; Huacani Pacori, Ferdynand Marcos; Calsin Cari, Maribel; Bueno Filho, Júlio Sílvio de Sousa
Genetic modeling of growth curve parameters in llamas is fundamental for breeding programs; however, previous studies have relied predominantly on two-stage frequentist approaches or conventional MCMC algorithms (Gibbs/Metropolis-Hastings), which present limitations regarding computational efficiency and simultaneous incorporation of multiple information sources. The objective of this study was to compare nonlinear functions (Brody, Gompertz, and von Bertalanffy) and jointly estimate growth curve parameters (asymptotic weight, A; scaling parameter, B; and maturation rate, k), variance components, and heritabilities in young llamas through hierarchical Bayesian modeling implemented with the No-U-Turn Sampler (NUTS) algorithm via Stan/brms. We analyzed 11,409 monthly weight records from birth to 365 days of age from 1000 llamas (456 males and 544 females) of K'ara and Ch'accu breeds from the Quimsachata Experimental Station (Peru). A three-stage hierarchical Bayesian model was adopted: (i) normal likelihood for weights conditioned on individual curves; (ii) multivariate animal model for parameters A, B, and k, including systematic effects (sex and breed) and additive genetic effects; and (iii) normal prior distributions for standard deviations. Posterior sampling (4000 post-warmup iterations) showed adequate convergence according to the Gelman-Rubin, Geweke, and Effective sample size diagnostics. The von Bertalanffy model was selected as the most parsimonious (Watanabe-Akaike Information Criterion (WAIC) = 20104.8; Leave-One-Out Information Criterion (LOOIC) = 27588). Estimated heritabilities for A were high (0.79 - 0.87), while those associated with parameters B and k were close to zero (0.007 – 0.075). We conclude that the hierarchical Bayesian approach with NUTS/brms is computationally efficient and statistically robust for analyzing growth curves in llamas, evidencing high genetic potential for adult weight selection, in contrast to the low heritability of curve shape parameters. This study represents the first application of the NUTS algorithm in hierarchical growth models for South American camelids.
Influence of thermal comfort in housing facilities on the increase in live weight of guinea pigs (Cavia porcellus) in the high Andean region of Puno, Peru
(Malque Publishing, 2026-08-03) Calatayud Mendoza, Alfredo Pelayo; Belisario Quispe, German; Huaquisto Ramos, Edilberto; Mamani Cato, Ruben Herberht; Coaquira Yucra, Martha Adela; Zeballos Cabana, Julio Cesar; Mamani Flores, Adderly
The high-altitude region of Puno is characterized by a pronounced daily thermal oscillation, which poses a challenge for the production of guinea pigs (Cavia porcellus), a species that is highly sensitive to microclimatic variability. This study analyzed the association between the thermal conditions of the houses and the weight gain of guinea pigs, considering both the mean level of the Temperature-Humidity Index (THI) and its intraday stability, measured by the thermal amplitude THI. The research followed a quantitative, non-experimental and longitudinal design, using productive and environmental data from INIA's Illpa Experimental Center. A total of 36 Peru breed guinea pigs housed in three pre-existing and independent facilities were evaluated, with weight records collected every 14 days between November 2023 and February 2024 (216 observations). The climatic variables were monitored by digital sensors that recorded measurements every 15 minutes. The results show that a higher intraday thermal amplitude of the Temperature and Humidity Index (THI) is negatively and statistically significantly associated with weight gain. On the other hand, no statistically significant association was detected between the mean level of the THI and weight gain under the observed conditions. This result does not imply the absence of a possible biological effect of the average THI, but rather that this effect could not be statistically identified within the thermal range and the period analyzed. Likewise, males showed greater weight gains than females, while the estimated coefficient for age was negative, although it did not reach statistical significance in the linear mixed model. Overall, the results suggest that intraday thermal stability may be related to productive performance; however, they do not allow us to conclude that it is more important than the average level of the THI or that it constitutes the only determining factor of weight gain (p<0.001).
Morphometric evaluation of guinea pigs (Cavia porcellus) in Southern Peru
(Learning Gate, 2024-07-19) Quispe Condori, Dennis; Huacani Pacori, Ferdynand Marcos; Mamani Paredes, Javier; Mamani Cato, Ruben Herberht
The aim of this study was the morphometric evaluation of guinea pigs in southern Peru. The study was carried out at the Agrarian Experimental Station Illpa (AESI) of the National Institute of Agrarian Innovation (NIAI) in Puno at 3824 meters above sea level. 120 guinea pigs were used (females n = 60 and males n = 60) with an average age of 22 days. The morphometric characteristics evaluated were: body weight (BW), chest circumference (CC), abdominal perimeter (AP), neck perimeter (NP), head length (HL) and head width (HW). To evaluate the effect of sex on morphometric characteristics, a completely randomized design was used. To determine the equation that best predicts body weight, stepwise regression was used, and correlations between morphometric characteristics were obtained using Pearson's correlation. The results show that the sex factor does not significantly influence BW, CC, AP, NP, HL, and HW (p≥0.05); likewise, the equation that best predicts the body weight of the guinea pigs was: BW = -530.50 + 21.98(CC) + 12.72(AP) + 10.16(NP) + 57.23(HW), with R2 = 84%. Pearson correlations between morphometric characteristics were of high magnitude, positive, and statistically significant (p<0.001). It is concluded that in conditions of the Peruvian highlands, the sex factor does not influence the morphometric characteristics. It is also possible to predict body weight from CC, AP, NP, and HW, and the correlations were high and positive.