Tarwi (Lupinus mutabilis S.) is a legume native to the Andes, recognized for its high nutritional value, which gives it great potential in food security programs. Therefore, understanding and advancing the conservation of its morphological diversity is essential. In this study, 140 accessions from the national germplasm collection of the National Institute of Agrarian Innovation of Peru were evaluated, along with two cultivars ("INIA 445 Masacanchino" and "Andenes 90"). A traditional agro-morphological characterization was conducted using 16 quantitative and 40 qualitative descriptors, complemented by phenological data obtained from time series of reflectance indices generated by Unmanned Aerial Vehicles (UAVs). Additionally, a principal component analysis (PCA) was applied to select the most relevant variables, and a clustering analysis along with a dendrogram was developed to classify ...

El presente trabajo de investigación se realizó en la Estación experimental de Centro Internacional de la Papa-Santa Ana, teniendo como objetivos: a) Evaluar la respuesta de los genotipos de especies silvestres al estrés por déficit hídrico, b) Seleccionar genotipos de especies silvestres de papa que muestren tolerancia al estrés por déficit hídrico. c) Cuantificar el porcentaje de selección de los genotipos dentro de cada especie. Para ello, se cultivaron en invernadero genotipos de 5 especies silvestres papa bajo el diseño experimental de diseño completo al azar (DCA) para cada especie, a los 45 días de la plantación se aplicó los tratamientos: sin estrés, estrés por déficit hídrico “b1, b2” (riego a 250 ml, y 125 ml). Las variables evaluadas fueron: Materia seca (hojas, tallos, tubérculos), concentración de clorofila, longitud radicular, altura de planta, comp...

The Junín Lake basin, a critical high-altitude ecosystem in the central Peruvian Andes, faces severe contamination from potentially toxic elements (PTEs) driven by mining activities, agriculture, and urbanization. This study evaluates the spatial distribution, ecological risk, and human health implications of 14 heavy metals, metalloids, and trace elements in surface soils surrounding the lake. Using 211 soil samples, we integrated remote sensing, land cover classification, and Random Forest machine learning models with spectral, edaphic, topographic, and proximity-based environmental covariates to predict contamination patterns and assess risk. Results reveal extreme contamination, with arsenic (As), lead (Pb), cadmium (Cd), and zinc (Zn) concentrations exceeding ecological thresholds by over 100-fold in agricultural zones. Ecological risk assessments using contamination degree (mCD), ...