Subsistence family farming in Peru is increasingly constrained by ecosystem degradation, climate variability, and limited access to productive services, particularly where environmental exposure is high. This study develops an Agro-productive and Territorial Vulnerability Index (IVAPT) to evaluate environmental, ecosystem, and socioeconomic vulnerability of subsistence agriculture at the district level nationwide. The index integrates district-level agricultural survey data (ENA-2024) with multi-temporal MODIS NDVI series (2000–2024) and comprehensive climatic, topographic, land-cover, and accessibility indicators, processed through multivariate statistics. Three objective weighting schemes (ENTROPY, CRITIC, PCA) construct thematic sub-indices of Environmental Exposure (EnvExp), Ecosystem Condition (EcoCond), and Socioeconomic Capacity (SocioCap). Results show more than half of Peru's ...

La investigación tuvo como objetivo evaluar y obtener datos de la producción de forraje (t/ha) y de la calidad nutricional de especies de leguminosas, gramíneas y sus consociados en la sierra central del Perú. El estudio se desarrolló en el centro experimental de Casaracra de la Universidad Nacional Daniel Alcides Carrión, sierra central del Perú, a 3786 msnm. Se obtuvo los valores de producción de forraje en materia seca, materia verde y el porcentaje de materia seca, así como los valores de calidad nutricional: Proteína total (PT%), Grasa (G%), Fibra cruda (FC%), Ceniza (C%), Calcio (Ca%), Fósforo (P%), Extracto libre de nitrógeno (ELN%) y la Energía bruta (EB kcal/100 g). Se encontraron diferencias significativas entre tratamientos para biomasa forrajera y calidad nutricional. Se construyó un dendograma donde los tratamientos fueron agrupados en tres grupos por sus carac...

La investigación tuvo como objetivo evaluar y obtener datos de la producción de forraje (t/ha) y de la calidad nutricional de especies de leguminosas, gramíneas y sus consociados en la sierra central del Perú. El estudio se desarrolló en el centro experimental de Casaracra de la Universidad Nacional Daniel Alcides Carrión, sierra central del Perú, a 3786 msnm. Se obtuvo los valores de producción de forraje en materia seca, materia verde y el porcentaje de materia seca, así como los valores de calidad nutricional: Proteína total (PT%), Grasa (G%), Fibra cruda (FC%), Ceniza (C%), Calcio (Ca%), Fósforo (P%), Extracto libre de nitrógeno (ELN%) y la Energía bruta (EB kcal/100 g). Se encontraron diferencias significativas entre tratamientos para biomasa forrajera y calidad nutricional. Se construyó un dendograma donde los tratamientos fueron agrupados en tres grupos por sus carac...

In this study, the quality of sediment and surface water in two natural wetlands, Paca and Tragadero, in the central region of Peru was evaluated using pollution indices, including the geoaccumulation index, pollutant load index, modified pollution degree, potential ecological risk index, and site rank index, for four heavy metals. Principal component analysis was used to identify potential metal contaminant sources. The determination of Fe, Zn, Pb, and As was performed by flame atomic absorption spectrophotometry. The average concentrations of metals in the sediments of both lagoons decreased in the order Fe > Zn > Pb > As. The analysis of the contamination indices determined that As and Pb are the elements that contribute the most to environmental degradation in both wetlands. There is a strong correlation between the values of potential ecological risk and the modified degree of conta...

The underutilization of remote sensing technology has compromised sustainable forage resource management, impeding the progress of livestock farmers in the northern Peruvian highlands. To accurately predict forage biomass in six high-altitude (2600-2800 m) ryegrass (Lolium multiflorum Lam) -clover (Trifolium repens) paddocks, we applied machine learning models implemented in Google Earth Engine using spectral indices derived from UAV-based multispectral imagery captured by a Micasense RedEdge MX camera mounted on a DJI Matrice 600. A total of 75 forage samples were collected from precisely geo-referenced plots to train and validate machine learning models based on 13 spectral indices. The Random Forest (RF) model, comprising 500 trees for green forage and dry matter, demonstrated high accuracy and efficiency. UAV-based biomass prediction using GEE and ML techniques was validated, achievi...

The growing global loss of genetic diversity, phenotypic characterization becomes essential for identifying resilient varieties capable of diversifying and strengthening the agricultural production of underutilized crops such as tarwi (Lupinus mutabilis S.). This study aimed to characterize the phenotypic variability of 41 tarwi accessions conserved in the germplasm bank of the National Institute of Agricultural Innovation (INIA) of Peru. The accessions were evaluated over two consecutive agricultural seasons at the Santa Ana Agrarian Experimental Station under local conditions. Thirty morphological descriptors (17 qualitative and 13 quantitative) were used following IBPGR guidelines. Data were analyzed using descriptive statistics, principal component analysis, hierarchical clustering and correlation analysis for quantitative descriptors, as well as frequency tables and the Shannon-Weav...