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An ecological modelling approach to support Peru wildlife conservation planning based on geospatial datasets and remote sensing information
(John Wiley & Sons Ltd., 2026-05-05) Cotrina Sanchez, Alexander; Rojas Briceño, Nilton; Guzman Valqui, Betty Karina; Valentini, Riccardo; Vaglio Laurin, Gaia
Peru, a megadiverse country, has developed conservation plans for some threatened wildlife species. This study produced spatially explicit data integrating Species Distribution Models (SDMs) into a geospatial analysis of connectivity within the protected areas (PAs) network. In addition, a deforestation analysis around selected PAs was performed evaluating the related conservation implications. The use of lidar-derived vegetation vertical structure metrics from the spaceborne Global Ecosystem Dynamics Investigation (GEDI) mission was tested as an innovative data source to support ecological modelling. This country-level analysis is a useful approach to support conservation in high-biodiversity areas. Location: Peru. Methods: Occurrence data of seven threatened wildlife species were used to compute SDMs in MaxEnt using three variable sets: (i) bioclimatic and topographic, (ii) GEDI vegetation structure metrics joined with Normalized Difference Vegetation Index (NDVI), and (iii) a combination of both. MaxEnt was explicitly calibrated by testing 126 candidate models per species across feature-class and regularization multiplier combinations. SDMs combined with auxiliary data were used to identify core areas, then connected through main ecological corridors (ECs) using geospatial analysis. Deforestation rates were computed in the buffer zones (BZ) of Protected Natural Areas (PNAs) identified as core areas. GEDI lidar-derived data were also used to compare forest degradation between two PNAs and their BZ. Results: This ecological modelling effort identified several core conservation areas, as well as the main ecological corridors interconnecting them. The study showed that highly suitable habitats are currently poorly represented by the present Peru protected areas network, particularly for primates. Test Area Under Curve (AUC) values ranged from 0.867 to 0.995; the Biotopveg set, integrating bioclimatic, topographic, GEDI, and NDVI variables was optimal for three species and the bioclimatic-topographic set for four, suggesting a species-specific contribution of vegetation structural data. GEDI data were used to detect forest degradation gradients, in accordance with known anthropogenic impacts. Deforestation analysis showed that even if indirect use protected areas resulted in less affected by deforestation in their surroundings, notable exceptions occur, calling for additional measures to support human-wildlife coexistence. Main Conclusions: Ecological modelling based on SDMs and spatial analyses can support species conservation plans and landscape connectivity at broader planning scales. GEDI provides valuable data as input in SDMs and supports detecting forest degradation.
Phenotypic variability and yield component analysis of lima bean (Phaseolus lunatus L.) genotypes under coastal conditions of Peru
(Agricultural Research Communication Centre (ARCC), 2026-05-05) Camargo Cobeñas, Marcos Antonio; Almidon Ramirez, Karen Karina; Rojas Meza, María Elena; Terán Rojas, José Alfonso
Background: Lima bean (Phaseolus lunatus L.) is an important grain legume cultivated in tropical and subtropical regions and contributes significantly to food security and local agriculture, particularly in Peru. However, information on the agronomic variability of lima bean germplasm under coastal conditions of Peru remains limited. This study aimed to evaluate the phenotypic variability and yield-related traits of lima bean genotypes from the INIA Germplasm Bank. Methods: Seven genotypes were evaluated under field conditions in Pisco, Ica (Peru), using a randomized complete block design with four replications. Twelve agronomic and morphological traits related to pod, seed and yield components were recorded. Data were analyzed using analysis of variance, Pearson correlation, principal component analysis and hierarchical clustering. Result: Significant differences among genotypes were observed for most traits, indicating considerable phenotypic variability. Grain yield per plant showed positive correlations with the total number of pods per plant and the number of marketable pods. The first two principal components explained 51.14% of the total variation and separated genotypes mainly according to yield components and morphological traits. Cluster analysis grouped the genotypes into three clusters, identifying genotype Ac4 as the most promising material due to its favorable association with yield-related traits and lower incidence of pest-infested pods.
Biorremediación del suelo con acidez y metales pesados (As, Cd) en un ecosistema altoandino con influencia minera mediante biochar de estiércol de cuy y consorcios microbianos
(DEEV MINAS, 2026-04-24) Arias Arredondo, Alberto; Cruz Luis, Juancarlos Alejandro; López Rodríguez, Melina; Solórzano Acosta, Richard Andi
Los suelos de pastizales altoandinos en zonas con influencia minera (Pasco, Perú, 4125 m) presentan acidez y contaminación por arsénico (As: 5.77 mg kg⁻¹) y cadmio (Cd: 1.71 mg kg⁻¹), lo que genera riesgo de transferencia de metales a la cadena trófica ganadera. Evaluamos el efecto del biochar de estiércol de cuy inoculado con consorcios microbianos (Bacillus subtilis, Pseudomonas putida, Trichoderma sp.) sobre la inmovilización de As y Cd y la calidad nutricional de pastos nativos (Festuca dolichophylla, Carex sp.) y cultivados (Lolium perenne, Dactylis glomerata). Establecimos un experimento factorial 4×4 en bloques completos al azar (48 parcelas). Determinamos factores de bioconcentración (BCF) y calidad nutricional, analizando mediante GLM y PCA. Los resultados evidenciaron una interacción significativa especie×tratamiento. Destacó la reversión fenotípica de Festuca dolichophylla frente a As, que pasó de acumuladora (BCF>1) a exclusora efectiva (BCF<<0.01) bajo inoculación con Trichoderma sp. Asimismo, Trichoderma sp. y P. putida redujeron la translocación de Cd en Lolium perenne (BCF<<0.1), manteniendo niveles seguros para consumo animal. El uso sinérgico de biochar y consorcios microbianos mitigó la transferencia de metales y preservó la calidad nutricional del forraje.
Peruvian national current research information system: implementation status and interoperability between PeruCRIS and institutional CRIS/RIM systems
(Taylor & Francis, 2026-05-09) Alhuay Quispe, Joel; Brañes Gutiérrez, Vanessa; Velarde Gutierrez, Renato; Zulueta Rafael, Hilda; Peña Pineda, Karla Mónica
PeruCRIS, the national Current Research Information System (CRIS) of Peru, represents a significant step toward consolidating scientific information management and enhancing research visibility across the country. In South American countries that have implemented open access legislation and institutional repositories, the development of integrated research information systems remains limited. This study offers a first comprehensive overview of PeruCRIS implementation status, focusing on its technical architecture, institutional adoption, and interoperability mechanisms. The study reports that 120 institutions are currently sending data to the national CRIS, either through manual uploads or via interoperability mechanisms. A sample of 60 CRIS/RIM cases were examined from May 2019 to December 2025, exploring the interaction between national and institutional CRIS platforms, addressing the practical challenges in aligning them. Findings reveal disparities in adoption levels, reliance on proprietary technologies, and limited interoperability coverage. The study also highlights the critical role of research managers and information professionals in sustaining CRIS systems. Finally, it outlines lessons learned and provides recommendations for similar national initiatives in developing countries.
Critical edaphic and altitudinal factors influencing cation exchange capacity in coffee-growing soils of northeastern Peru: implications for sustainable fertility management
(Frontiers Media SA, 2026-05-05) Díaz Chuquizuta, Henry; Manrique Gonzales, Luis Fernando; Sánchez Ojanasta, Martín; Cuevas Giménez, Juan Pablo; Carbajal Llosa, Carlos Miguel; Cuellar Condori, Néstor Edwin; Martínez Zapata, Boris Guillermo; Vallejos Torres, Geomar
Introduction: Effective cation exchange capacity (ECEC) is a key indicator of soil fertility and sustainable soil management assessment in coffee-growing systems. Methods: This study aimed to identify the principal edaphic and altitudinal factors explaining ECEC variability in 69 soil samples collected from coffee farms in northeastern Peru. Results: ECEC results exhibited substantial variation, ranging from 0.14 to 55.49 cmol(+)·kg⁻¹ (mean = 15.21; SD = 12.47), and were significantly correlated with organic matter (r = 0.71), clay content (r = 0.62), exchangeable acidity (r = -0.63), and altitude (r = 0.33). Principal component analysis accounted for 64.3% of the edaphic variability, identifying Ca²⁺, pH, Mg²⁺, and exchangeable acidity as the most influential variables. The Random Forest model demonstrated high predictive accuracy (R² = 0.93; root mean square error (RMSE) = 2.1 cmol(+)·kg⁻¹), outperforming the generalized additive model (GAM) and identifying Ca²⁺ as the most important predictor (IncMSE% = 3177.37). A functional altitudinal gradient was also evident: areas above 1150 m.a.s.l. showed higher acidity and aluminium content, whereas areas below 900 m.a.s.l. exhibited greater base saturation and higher ECEC. Discussion: These findings support the development of site-specific fertilization strategies and soil–climate zoning, emphasizing the value of integrating multivariate analyses with machine-learning models as key tools for optimizing fertility management and coffee crop productivity in tropical mountain ecosystems; where soil texture represents a key factor influencing coffee sustainability, as greater nutrient retention capacity and improved nutritional balance are associated with enhanced potential for sustainable production and reduced environmental impact.
Manejo agronómico del maíz blanco duro INIA 610 NUTRIMAIZ
(Instituto Nacional de Innovación Agraria (INIA), 2026-04) Campos Amasifuen, Héctor Manuel
La variedad INIA 610 – Nutrimaíz es importante para la alimentación humana y animal porque contiene alta calidad de proteína, se puede aprovechar en tres estados de desarrollo de la planta: consumo tierno, choclo y grano seco. El manejo del maíz blanco es similar al maíz amarillo; es decir, las condiciones de producción y los métodos de cultivo son idénticos.
Manejo agronómico del maíz amarillo duro INIA 616-Ucayali
(Instituto Nacional de Innovación Agraria (INIA), 2026-04) Campos Amasifuen, Héctor Manuel
El maíz amarillo duro es el cultivo de mayor importancia en de la canasta alimenticia básica de la población ucayalina, la rentabilidad aumenta cuando se utilizan cultivares mejorados en condiciones favorables y manejo adecuado. La variedad INIA 616 - Ucayali se ha generado en la Estación Experimental Agraria Pucallpa, principalmente para condiciones de suelos de restinga.
Desempeño agronómico de líneas de frijol común (Phaseolus vulgaris L.) bajo abonamiento orgánico en condiciones de casa malla, Chincha, Perú
(Decanato de Agronomía, Universidad Centroccidental Lisandro Alvarado (UCLA), Venezuela, 2026-05-01) Camargo Cobeñas, Marcos Antonio; Almidon Ramirez, Karen Karina; Rojas Meza, María Elena; Aybar Peve, Leandro Joel; Terán Rojas, José Alfonso
El frijol común (Phaseolus vulgaris L.) es un cultivo estratégico por su valor nutricional y su asociación con microorganismos fijadores de nitrógeno, aunque en regiones como Chincha (Perú) los rendimientos permanecen bajos, lo que demanda alternativas de manejo. Se evaluó la respuesta agronómica de las líneas Larán Mejorado y Waf 78/20 a la aplicación de compost y BlackSoil en dosis de 8 y 16 % (p/p), bajo un Diseño en Bloques Completos al Azar (DBCA) con arreglo factorial 2 × 2 × 2 y dos testigos, con cuatro bloques en condiciones de casa malla. Se evaluaron 12 variables agromorfológicas y la densidad aparente del sustrato, analizadas mediante efectos principales e interacciones, pruebas paramétricas y no paramétricas, coeficientes de correlación de Pearson y análisis de componentes principales (ACP). Se obtuvo que el factor genético fue la principal fuente de variación. Larán Mejorado destacó por una respuesta más uniforme, mayor precocidad y mejores componentes de rendimiento, favorecidos por la aplicación de compost; mientras que Waf 78/20 se asoció con mayor crecimiento vegetativo y mayor sensibilidad a cambios en la densidad aparente del sustrato; en esta línea, la aplicación de BlackSoil se relacionó con ciclos fenológicos más prolongados y menor peso de semilla. Los hallazgos evidencian que la genética determina en mayor medida la respuesta al abonamiento orgánico, resaltando la importancia del genotipo en prácticas de manejo; sin embargo, estos resultados deben validarse en condiciones de campo y múltiples ambientes.
Agronomic variables outperform multispectral indices for individual plant yield prediction in Andean quinoa
(Elsevier B.V., 2026-04-18) Pizarro Carcausto, Samuel Edwin; García Seguil, Erika Janina; Gavino, Esthefany; Requena Rojas, Edilson Jimmy; Ortega Quispe, Kevin Abner; Cccopi Trucios, Dennis
Accurate pre-harvest yield estimation is essential for decision-making in high-altitude agriculture. This study evaluated agronomic and multispectral UAV variables for near-harvest prediction of individual quinoa grain weight, with data collected across six phenological stages to identify when predictors achieve reliable performance, under Andean conditions. A total of 374 plants were monitored across six phenological stages at Santa Ana Experimental Station (Huancayo, Peru, 3280 m a.s.l.) during 2024. OLS, Random Forest, Support Vector Machine, and Neural Network models were trained using agronomic-only (AGRO), spectral-only (IND), and combined (COMP) predictor sets, evaluated through 5-fold cross-validation reporting mean ± standard deviation. Agronomic and combined models achieved moderate performance (R² = 0.22–0.25, RPD = 1.10–1.15), suitable for relative plant ranking in breeding programs, while spectral-only models failed across all algorithms (R² ≤ 0.044, CCC ≤ 0.080), constrained by saturation, phenological decoupling, and canopy heterogeneity. Variable importance analysis confirmed that late-season structural traits dominated predictions, while spectral indices contributed marginally despite including red-edge bands. These results challenge spectral-only approaches for individual plant phenotyping in heterogeneous canopies, demonstrating that integrating simple ground measurements with UAV spectral data is essential for reliable quinoa yield estimation.
Electrophoretic profiles of alpaca seminal plasma proteins and their association with sperm quality parameters during cryopreservation processes
(John Wiley & Sons Ltd., 2026-03-24) Guillen Palomino, Crissthel Yverlin; Mujica Lengua, Fidel Rodolfo; Contreras Huamaní, Mijail; Carretero , María Ignacia; Rueda Alfonso, Fabian Leonardo; Orellana Berrocal, Harumi
The aim of the study was to characterize the electrophoretic profiles of alpaca seminal plasma (SP) proteins and establish their association with sperm quality parameters at different cryopreservation stages. Sperm quality was assessed in raw, cooled, and thawed semen from 128 ejaculates collected from 16 Huacaya alpacas, and SP proteins were analysed by SDS-PAGE in raw samples. Statistical associations were determined using Spearman's rank correlation (p ≤ 0.05). Twenty-three protein bands were identified: 21 bands ranging from 9.23 to 138.38 kDa, and 2 below 6.5 kDa. Notably, the 21.03 kDa protein was absent in six males, five of whom also lacked the 18.88 kDa band. These individuals exhibited superior post-thaw sperm quality, particularly higher motility. The 21.03 kDa protein showed a negative correlation (p ≤ 0.05) with sperm motility and membrane function in raw, cooled, and thawed semen, and a positive correlation with acrosome integrity in thawed semen. Similarly, the 18.88 kDa protein showed a negative correlation with sperm motility and membrane function, but a positive correlation with acrosome integrity in thawed semen (p ≤ 0.05). In conclusion, these findings suggest that specific SP proteins may serve as potential biomarkers for sperm quality and cryotolerance in alpacas, reflecting individual variability in response to cryopreservation.