Examinando por Materia "Models"

Mostrando 1 - 3 de 3

A tool for predicting live weight in Huacaya alpacas from southern Peru
(ResearchersLinks Ltd, England, UK, 2026-07-23) Churata Huacani, Roxana; Canaza Cayo, Ali William; Amarilho Silveira, Fernando; Rodriguez Huanca, Francisco Halley; Marchezan Barchet, Fernanda; Fonseca de Freitas, Rilke Tadeu; Núñez Pérez, Herbert Jesús
The aim of this study was to identify the most suitable model for predicting live weight using both original body measurements (BM) and principal component scores (PC), and to assess the relationship between body measurements (BM) and live weight (LW). LW and BM of Huacaya alpacas (n = 117) were collected from the Quimsachata Center of the National Institute of Agricultural Innovation in Peru. The following BM, including LW, withers height (WH), croup height (CH), thoracic circumference (TC), abdominal circumference (AC), cannon-bone length (CL), neck-base circumference (NBC), cannon circumference (CC), tail insertion length (TIL), rump width (RW), tail insertion circumference (TIC), body width (BDW), rump length (RL), forelimb length (FL), body length (BDL), back length (BKL), were taken. Principal component analysis (PCA) was utilized to extract and clarify the correlation between LW and their BMs. Regression equations relating LW to BM and their PCs were computed. Additionally, the root mean squared error (RMSE), Bayesian information criterion (BIC), Akaike information criterion (AIC), and coefficients of multiple determination (R²) were used to assess the models. Four components were extracted from the PCA of BM and LW, which accounted for 67.3% of the total variance. The prediction model for LW, utilizing two PCs, showed the highest R² as well as the lowest BIC, AIC and RMSE values in contrast to models based on the original measurements. The findings suggest that this method is a viable alternative for predicting live weight and may be useful in breeding programs, as well as in the design of management and selection strategies for Huacaya alpacas from Peru.
Effect of climate variability on Collaria scenica (Hemiptera: Miridae) on the Bogotá plateau
(Universidad Nacional de Colombia, 2019-01-01) Rodríguez Roa, Andrea; Arce Barboza, Blanca; Boshell Villamarin, Francisco; Barreto Triana, Nancy
The aim of this research was to study the effect of climatic conditions on the population of the grass bug Collaria scenica (Stal, 1859) using agroclimatic models and analyzing its behavior under interannual variability scenarios related to El Niño-Southern Oscillation (ENSO) events. The population fluctuations of this grass bug were modeled, estimating significant climatic variables in the presence of nymphs and adults with a multiple linear regression analysis. The population distribution of this insect in relation to the occurrence of the El Niño and La Niña phenomena on the Bogota plateau was analyzed based on variations of the sea surface temperature (SST) in the tropical Pacific and their impact on climate variables. The maximum and minimum temperatures, precipitation and evapotranspiration showed higher significance for this pest than the other variables. The optimal growth and development conditions for this grass bug occurred during periods with a higher daily thermal amplitude and high precipitation values, which highlights the positive effect of abundant, but not excessive, rain. This study helped to determine the population growth during the two seasons of the year with higher rainfall in the area, which correspond to March-May (MAM) and September-November (SON), mainly in the following season after the dry quarter of December-February (DJF). Important increases occur in the El Niño event because of the greater accumulation of heat units during this phenomenon based on increases in air temperature that favor insect growth.
Optimizing landfill site selection using Fuzzy-AHP and GIS for sustainable urban planning
(Salehan Institute of Higher Education, 2024-06-01) Zabaleta Santisteban, Jhon Antony; Salas López, Rolando; Rojas Briceño, Nilton Beltrán; Gómez Fernández, Darwin; Medina Medina, Angel James; Tuesta Trauco, Katerin Meliza; Rivera Fernandez, Abner Shelser; Lévano Crisóstomo, José; Oliva Cruz, Manuel; Silva López, Jhonsy Omar
Careful landfill selection with minimal environmental impact is vital for urban planners. This study aims to identify suitable sites for controlled landfills using Fuzzy-AHP integrated with Remote Sensing and GIS, considering a 20-year projection of population and solid waste generation. Initially, twelve sub-criteria were identified, grouped into environmental, socio-economic, and physical categories, and then weighted using paired comparison matrices involving nine experts. The sub-criteria were rasterized and classified into four suitability levels. The weighted overlay of sub-criteria maps generated a territorial suitability model. Within the Alto Utcubamba Commonwealth (Amazonas, Peru), 0.069%, 41.70%, 66.934%, 0.20%, and 12.4% of the territory are suitable, moderately suitable, less suitable, unsuitable, and restricted, respectively, for landfill establishment. Subsequently, 16 highly suitable sites were selected based on the required area (S4 polygons ≥ 0.505 ha) in line with the projected solid waste generation over 20 years. Of the 16 selected areas, only 15 met the shape index. The model showed high accuracy (AUC = 0.784) during validation. Furthermore, this study provides a comprehensive framework for making decisions about waste management in developing countries, enhancing understanding of key factors in selecting landfill sites. It also offers a deeper insight into global and local factors that determine the suitability of landfill sites.