Urban growth and Land Use/Land Cover (LULC) changes have increased in recent decades due to anthropogenic activities. This study explored past and projected future LULC changes and urban growth patterns in the Bagua Grande and Chachapoyas districts using Landsat imagery, cloud computing, and predictive models for 1990 to 2031. The analysis of satellite images was grouped into four time periods (1990–2000, 2000–2011, 2011–2021 and 2021–2031). The Google Earth Engine (GEE) cloud-based system facilitated the classification of Landsat 5 ETM (1990, 2000, and 2011) and Landsat 8 OLI (2021) images using the Random Forest (RF) model. A simulation model integrating Cellular Automata (CA) and an Artificial Neural Network (ANN) Multilayer Perceptron (MLP) in the MOLUSCE plugin of QGIS was used to forecast urban sprawl to 2031. The resulting maps showed an overall accuracy (OA) of over 92%. A decrease in forested area was observed, from 20,807.97 ha in 1990 to 14,629.44 ha in 2021 in Bagua Grande and from 7,796.08 ha to 3,598.19 ha in Chachapoyas. In contrast, urban areas experienced a significant increase, from 287.49 to 1,128.77 ha in Bagua Grande and from 185.65 to 924.50 ha in Chachapoyas between 1990 and 2021. By 2031, the urban area of Bagua Grande is expected to increase from 1,128.77 to 1,459.25 ha (29%) in a southeast, south, southwest, west, and northwest direction. Chachapoyas expanded from 924.50 to 1138.05 ha (23%) in the southwest, north, northeast, and southeast directions. The study presents an analytical method integrating cloud processing, GIS, and change simulation modeling to evaluate urban growth spatio-temporal patterns and LULC changes. This approach effectively identified the main LULC changes and trends in the study area. In addition, potential urbanization areas are highlighted where there are still opportunities for developing planned and managed urban settlements.

El Altiplano peruano presenta pérdidas crecientes de fertilidad, siendo a su vez susceptible a una erosión natural. Durante muchos años, un manejo agrícola convencional ha generado pérdidas de la capa superficial del suelo y deterioro de sus propiedades, teniendo gran impacto en el rendimiento de los cultivos y profundizando la degradación de este ecosistema vulnerable. El propósito de esta investigación fue evaluar el uso de cultivos de cobertura frente a la erosión, salud del suelo y rendimiento del cultivo de quinua. El ensayo se realizó en las localidades Huancarani y Cahualla, distrito Mañazo, provincia y región Puno. Se utilizó un diseño experimental de bloques completos al azar (DBCA) con cuatro tratamientos: sin cobertura y con coberturas de trébol (Medicago hispida G.), vicia (Vicia villosa) y mulch. Los resultados mostraron que la quinua asociada con coberturas de trébol, mulch y vicia redujeron la erosión del suelo en 59,61%, 51,87% y 49,50%, respectivamente. Asimismo, el uso de coberturas de trébol y vicia aumentó el carbono orgánico (+29,71% y 31,16%) y nitrógeno (+36,94% y 48,65%), y con el trébol, el fósforo disponible (+26,11%). Finalmente, la cobertura de trébol aumentó en 17% el rendimiento de la quinua en grano y redujo significativamente la erosión del suelo. Estos resultados muestran que los cultivos de cobertura presentan gran potencial para el restablecimiento de la salud del suelo y mejora en el rendimiento.

The study was conducted in Juan Guerra district, province and region of San Martin, Peru; it assessed two treatment sets: (1) nitrogen fertilizer dose (FN75, FN100); (2) green manure Crotalaria juncea (CroJ), Canavalia ensiformis (CanE), and without green manure. It was arranged in a split-plot design with four replications. During the experiment, we observed an important fluctuation in soil parameters. Notably, there was a decrease in soil carbon and nitrogen levels, likely attributed to microorganism metabolism. On the other hand, we observed that CanE significantly reduced the diseased tillers through “White Leaf Virus” (RHBV) by 2.82% compared to the control, and significant panicle fertility was achieved by CroJ (91.88%). No significant differences were obtained in yields during this first campaign; however, the highest reported yield was 8.36 t ha-1 with the CanE - FN100 treatment. Additionally, the nutritional quality of the rice was not affected by either green manuring or the application of chemical nitrogen fertilization. These findings allow deeper studies to consider strategic alternatives to reducing dependency on inorganic fertilizers among the poorest communities.

Monitoring and evaluation of landscape fragmentation is important in numerous research areas, such as natural resource protection and management, sustainable development, and climate change. One of the main challenges in image classification is the intricate selection of parameters, as the optimal combination significantly affects the accuracy and reliability of the final results. This research aimed to analyze landscape change and fragmentation in northwestern Peru. We utilized accurate land cover and land use (LULC) maps derived from Landsat imagery using Google Earth Engine (GEE) and ArcGIS software. For this, we identified the best dataset based on its highest overall accuracy, and kappa index; then we performed an analysis of variance (ANOVA) to assess the differences in accuracies among the datasets, finally, we obtained the LULC and fragmentation maps and analyzed them. We generated 31 datasets resulting from the combination of spectral bands, indices of vegetation, water, soil and clusters. Our analysis revealed that dataset 19, incorporating spectral bands along with water and soil indices, emerged as the optimal choice. Regarding the number of trees utilized in classification, we determined that using between 10 and 400 decision trees in Random Forest classification doesn't significantly affect overall accuracy or the Kappa index, but we observed a slight cumulative increase in accuracy metrics when using 100 decision trees. Additionally, between 1989 and 2023, the categories Artificial surfaces, Agricultural areas, and Scrub/ Herbaceous vegetation exhibit a positive rate of change, while the categories Forest and Open spaces with little or no vegetation display a decreasing trend. Consequently, the areas of patches and perforated have expanded in terms of area units, contributing to a reduction in forested areas (Core 3) due to fragmentation. As a result, forested areas smaller than 500 acres (Core 1 and 2) have increased. Finally, our research provides a methodological framework for image classification and assessment of landscape change and fragmentation, crucial information for decision makers in a current agricultural zone of northwestern Peru.

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.

The purpose of this study is to evaluate the phenotypic characteristics and typification of Creole goats in five localities of the Ayacucho region in south-central Peru. Materials and Methods: Data from 149 goats (25 males and 124 females) were collected, excluding animals under 2 years of age, pregnant, and sick. Seven qualitative characteristics and 11 zometric measurements were evaluated, and then 9 zometric indices were estimated. Results: In the region, goats with composite colors predominated (76.50%). Additionally, supernumerary (24.20%) and divergent teats (22.60%) were observed in females, while males exhibited a scrotal bifurcation (32.00%). The origin of the flock had a significant effect (p < 0.05) on body measurements, as well as on pelvic index, transverse pelvic index, longitudinal pelvic index, compactness index, and load cannon bone index, except for body index (BOI), proportionality index, dactyl thorax index (DTI), and relative cannon bone thickness index (p > 0.05). In the Ayacucho region, there is a predominance of light animals (57.72%) with a significant DTI (p < 0.05) among the populations, including goats with good balance and capable of walking long distances. Furthermore, there are compact animals (47.65%) with a significant BOI (p < 0.05) among the flock populations, which animals are of the biotype of meat. Conversely, the strongest positive correlation (r = 0.89) was discovered between chest girth and body weight. Conclusion: In the Ayacucho region, there are various creole goat biotypes range from light to very compact heavy goats, with a predominance of meat biotype animals, as well as a marked size dimorphism between localities of origin.

This study evaluated the seasonal variability of water quality in the Tilacancha River, the water source that supplies Chachapoyas, and the rural communities of Levanto and San Isidro del Maino of Perú. Eighteen physical, chemical, and microbiological water parameters were evaluated at five sampling points in two seasons (rainy and dry). To determine water quality, the results obtained for the parameters evaluated were compared with the Maximum Permissible Limits (MPL) established in the Regulation on Water Quality for Human Consumption (DS Nº 031-2010-SA), approved by the Environmental Health Directorate of the Ministry of Health. In addition, a Pearson correlation was performed to estimate the correlation between the variables evaluated. The results showed that microbiological parameters exceeded the MPLs in both periods evaluated, such as the case of total coliforms (44 MPN.100 mL-1), fecal coliforms (25 MPN.100 mL-1), and E. coli (5.45 MPN.100 mL-1), these microbiological parameters reported a positive correlation with turbidity, temperature, total dissolved solids, and flow rate. In addition, aluminum (Al) and manganese (Mn) exceeded the MPL in the rainy (0.26 mg Al.L-1) and dry (1.41 mg.Mn-1.L-1) seasons, respectively. The results indicated that the water of the Tilacancha River is not suitable for human consumption. Therefore, it must be treated in drinking water treatment plants to be used as drinking water.