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Assessment of soil fertility variability for maize production in highland agroecosystems of Peru
(Polish Society of Ecological Engineering (PTIE), 2026-04-01) Garcia Seguil, Erika Janina; Ccopi Trucios, Dennis; Requena Rojas, Edilson Jimmy; Sanabria Quispe, Samuel; Arias Arredondo, Alberto Gilmer; Gavino Lulo, Esthefany Irene; Azabache, Andres; Pizarro Carcausto, Samuel Edwin
Maize (Zea mays L.) is central to food, feed, and rural livelihoods, yet the yields in Peru’s highlands remain modest, underscoring the need for spatially explicit soil diagnostics. This study aimed to characterize the spatial variability of soil fertility in a highland maize production area of the southern Mantaro Valley and translate those patterns into site-specific management zones. The authors sampled the arable layer (0–30 cm) at 100 plots and analyzed pH, electrical conductivity, exchangeable acidity, texture, organic matter (OM), total nitrogen (N), available phosphorus (P), available potassium (K), exchangeable cations (Ca, Mg, Na, K), and calcium carbonate (CaCO₃). Laboratory data were integrated with environmental covariates using geostatistics, Random Forest, and GIS to generate high-resolution maps. Results showed uneven distributions in key attributes about 25% of the area with P deficiency, 15% with localized K shortages, and ~20% with OM < 2% while pH and CEC were comparatively stable. Random Forest achieved strong predictive performance for relatively stable properties (e.g., OM, pH, exchangeable cations), whereas mobile nutrients (available P, exchangeable K) were less predictable. The resulting products constitute the first high-resolution soil-fertility baseline for maize in the southern Mantaro Valley. The maps delineate fertilization management zones and provide a practical basis for preliminary rate recommendations that target constraints while avoiding surpluses. Future work will refine these zoned recommendations through yield-response trials, seasonal monitoring of mobile nutrients, and farmercentered decision-support tools, with the goal of improving nutrient-use efficiency, sustaining maize productivity, and reducing environmental risks across the valley.
Moderate deficit irrigation improves agronomic performance of quinoa (Chenopodium quinoa Willd.) compared to full irrigation in the central highlands of Peru
(Learning Gate, 2026-03-19) Gavino Lulo, Esthefany Irene; Ccopi Trucios, Dennis; Garcia Seguil, Erika Janina; Requena Rojas, Edilson Jimmy; Contreras, Jose; Solórzano Acosta, Richard Andi; Betega, S.D.; Yaranga, Raúl M.; Pizarro Carcausto, Samuel Edwin
This study evaluated the agronomic performance and water productivity of quinoa (Chenopodium quinoa Willd. cv. INIA 433) under three irrigation regimes in the central highlands of Peru: optimal irrigation (Ks = 1.00), moderate deficit (Ks = 0.66), and severe deficit (Ks = 0.49). The experiment combined constant water table lysimeters and field plots, integrating crop coefficient estimation, water balance analysis, and multispectral monitoring (NDVI, NDRE, SRWI) using UAV imagery and ground spectroradiometry. Moderate water stress (Ks = 0.66) significantly improved reproductive performance, producing approximately 8,000 grains per plant compared with ~3,900 grains per plant under optimal irrigation. Grain protein content increased from 4.8% to 6.0%, while evapotranspiration decreased by 37% (from 374.5 to 234.4 mm), markedly improving water use efficiency. In contrast, optimal irrigation promoted maximum vegetative growth (plant height ~110 cm; NDVI 0.7–0.8) but lower reproductive output, whereas severe stress (Ks = 0.49) reduced yield to 4,400 grains per plant and accelerated senescence. Multispectral indices effectively distinguished water stress levels: NDVI reflected canopy vigor, NDRE detected chlorophyll variation, and SRWI captured plant water status. The results demonstrate that regulated deficit irrigation enhances water productivity and grain quality in quinoa. Maintaining Ks values around 0.65–0.70 appears to optimize yield and resource use efficiency in water-limited Andean agroecosystems.
Geographic information system applications in bee research
(MDPI, 2026-05-29) Rojas Briceño, Nilton B.; Silva López, Jhonsy O.; Guzman Valqui, Betty Karina; Ix Balam, Manuel A.; Ramos Tejeda, José L.; Oliva Cruz, Manuel; Veneros, Jaris; García, Ligia
Bees play crucial ecological, economic, and environmental roles, and research on them increasingly includes a spatial dimension. Geographic Information Systems (GISs) enable the acquisition, storage, analysis, management, and visualization of spatial data. However, GIS applications in bee research have expanded while remaining dispersed across topics, tools, taxa, and methodological approaches. This study provides a comprehensive and updated review of GIS applications in bee research by integrating bibliometric analysis with a structured synthesis of GIS purposes and techniques. A total of 228 publications were analyzed to assess publication trends, co-authorship patterns, keyword themes, study areas, taxonomic coverage, GIS application themes, and methodological tools. GIS was used to select suitable apiary sites, map floral resources, analyze bee behavior, assess diseases and pests, monitor bee products, evaluate urban and landscape contexts, and predict climate change effects. The main GIS-related approaches included multicriteria decision analysis (MCDA), remote sensing, species distribution models (SDMs), spatial interpolation, WebGIS platforms, and emerging machine-learning applications. The review also identified underrepresented taxa, especially wild bees, stingless bees, and other Apis species. Future advances should integrate MCDA with data-driven models, improve floral-resource mapping with remote sensing, and strengthen reproducibility through standardized spatial data and workflows.
Genomics and reproductive biotechnologies in goat production systems in Peru
(2026-06-01) Romero Avila, Yolanda Madelein; Sessarego Davila, Emmanuel Alexander; Pinazo Herencia, René Alfredo; Cruz Luis, Juancarlos Alejandro
Goat production in Peru is primarily carried out under extensive systems shaped by climatic variability, forage seasonality, infrastructure limitations, and persistent sanitary pressure. In this context, Creole goats represent a strategic animal genetic resource due to their capacity to adapt to arid and high-Andean environments. This review integrates the available evidence on production typologies in the main goat-producing regions of the country, the major sanitary and structural bottlenecks, and the state of the art of genomic, multi-omics, and reproductive biotechnology tools applicable to goats. It discusses how the transition from traditional markers to SNP genotyping, together with functional approaches such as microbiome analysis, transcriptomics, and proteomics, can contribute to understanding the biological basis of complex traits related to resilience, feed efficiency, and reproductive performance. Likewise, the potential of precision livestock farming to generate longitudinal phenotypes and strengthen genetic improvement programs in low-input systems is highlighted. Finally, priorities and considerations are outlined to advance the integration of phenotyping, genomics, and reproductive biotechnologies in extensive contexts, with emphasis on the generation of systematic data, interinstitutional coordination, and technology transfer aimed at the sustainability and conservation of goat resources. These insights may also inform genetic improvement strategies in other developing countries facing similar environmental and structural constraints in low-input goat production systems, particularly in arid and semi-arid regions.
Integrated assessment of water quality and trophic status in High Altitude Andean lagoons: a multi-index and multivariate approach for sustainable fish farming management
(Elsevier Inc., 2026-05-27) Custodio, María; Huarcaya, Javier; Ccopi Trucios, Dennis; Alvarez, Daniel; Pizarro Carcausto, Samuel Edwin; Ortega Quispe, Kevin Abner
High-altitude Andean lagoons are ecologically sensitive systems whose water quality is under increasing pressure from the expansion of aquaculture and other human activities. An integrated assessment of water quality and trophic status was carried out in three lagoons located in the highlands of central Peru, using a multi-index and multivariate approach that combined physicochemical parameters, trophic indices (TRIX, TSI, molar N:P ratio), and heavy-metal indices, evaluated against Peruvian EQS, USEPA, and CCME water-quality standards. Principal component analysis explained 60.1% of the total variability, with the first axis (40.4%) structured by an organic loading and nutrient gradient that consistently separated Tipicocha from the other lagoons. Total phosphorus in Tipicocha reached concentrations well above the Peruvian EQS threshold, and TRIX values classified all lagoons as eutrophic to hypertrophic (5.46–6.21). TSI (TP) classified Tipicocha and Tranca Grande as hypereutrophic, whereas TSI (Chl-a) remained within the eutrophic range (53–60), a pattern consistent with additional environmental constraints on phytoplankton biomass. Molar N:P ratios indicated strong nitrogen limitation in Tipicocha and Tranca Grande, whereas Pomacocha showed a seasonal shift from co-limitation during the dry season to potential nitrogen limitation during the rainy season. Metal contamination was low according to EQS and USEPA criteria, whereas CCME thresholds suggested moderate to high contamination (HPI up to 105.1), with systematic exceedances of Cd, Cu, and Zn at all sites. Taken together, the results point to strong trophic enrichment associated with fish-farming activity as the main pressure on water quality in these ecosystems and show that the choice of regulatory framework has a decisive influence on metal-risk classification.
Spatial assessment of heavy metal contamination in agricultural soils of the lower Chancay–Huaral valley, Peru
(Wiley, 2026-05-29) Samaniego Vivanco, Tomás Daniel; Ramirez Aparicio, Jorge Adrian; Solórzano Acosta, Richard Andi
Soil contamination by heavy metals (HMs) poses a potential threat to agricultural productivity and food security, particularly in rapidly developing coastal regions. This study evaluates the spatial distribution and contamination levels of cadmium (Cd), copper (Cu), lead (Pb), zinc (Zn), and manganese (Mn) in agricultural soils from the Huaral, Chancay, and Aucallama districts of the Lima region, Peru, an area undergoing urban expansion, mining concessions, and the establishment of a new international port. A total of 88 soil samples were analyzed for metal concentrations using microwave plasma atomic emission spectrophotometry (MP-AES), along with key physicochemical properties. Geostatistical interpolation techniques, including ordinary kriging (OK) and cokriging (CK), were applied to generate spatial prediction maps for each element. The geo-accumulation index (Igeo) and contamination factor (CF) were used to determine the contamination status. Mean Igeo values ranged from −0.59 to −0.46, while mean CF values ranged from 1.09 to 1.21, indicating generally unpolluted to moderately polluted conditions. Although maximum values reached 1.41 for Igeo and 4.21 for CF, these were spatially localized. Results revealed that most metal concentrations remained below the Peruvian Environmental Quality Standards for agricultural soils, suggesting predominantly natural geochemical origins. However, a small proportion of samples showed slight and localized exceedances (4.54% for Cd and 3.41% for Mn). For elements not regulated under national standards, international guidelines were considered, further supporting the absence of widespread anthropogenic contamination. Higher concentrations of Cd, Cu, Zn, Pb, and Mn were spatially clustered in the north-central sector of the study area, suggesting responses to soil properties such as pH, texture, and moisture. Notably, areas of higher concentration did not coincide with zones of higher contamination indices, indicating limited anthropogenic influence. However, proximity to urban expansion, mining activities, and port infrastructure highlights the need for continuous soil monitoring to prevent accumulation and ensure agricultural sustainability.
Sarcocistiosis en alpacas y llamas: manejo para su control y prevención
(Instituto Nacional de Innovación Agraria (INIA), 2026-05-07) Alejo Huarachi, Alexander Onasis
El presente folleto aborda la sarcocistiosis en alpacas y llamas, una enfermedad parasitaria endémica y de alta prevalencia en los camélidos sudamericanos de las zonas altoandinas del Perú, causada por el protozoo Sarcocystis aucheniae. Se describen sus características, mecanismos de transmisión, síntomas, métodos de diagnóstico, opciones de tratamiento y principales recomendaciones para su prevención y control. La publicación fue elaborada en el marco del proyecto "Mejoramiento de los servicios de investigación y transferencia de tecnología en ganadería altoandina en 33 distritos" (CUI 2491159) del INIA-MIDAGRI, con el fin de contribuir a la mitigación de esta enfermedad en los rebaños de camélidos
Ecological risk associated with potentially toxic elements in agricultural soils across coastal and highland valleys
(Elsevier Ltd., 2026-05-06) Pérez Porras, Wendy Elizabeth; Ccopi Trucios, Dennis; Flores Marquez, Ricardo; Carbajal Llosa, Carlos Miguel; Pizarro Carcausto, Samuel Edwin
Soil elemental composition in heterogeneous agroecosystems is shaped by interacting environmental and anthropogenic controls. This study evaluated the spatial variability of potentially toxic elements (PTEs: Cu, Cr, Fe, Mn, Mo, Ni, Pb, V, Zn, As, and Cd) across coastal (Chancay and Pativilca) and highland (Mantaro and Tarma) agricultural valleys of Peru. A stratified sampling design was combined with multivariate analyses (PCA, PERMANOVA, PERMDISP, and variance partitioning) and ecological risk assessment using integrated indices (PLI, mCd, SRI, and Nemerow index). The first two principal components explained 50.2% of total variance (PC1 = 36.8%; PC2 = 13.4%), reflecting distinct soil–geochemical and climatic–spatial gradients. The Valley × Zone interaction significantly structured elemental composition (R² = 0.049, p = 0.011), whereas crop type showed no significant effect (p = 0.838). Variance partitioning indicated that soil physicochemical, climatic, and spatial/topographic predictors jointly explained 60% of total variation (adjusted R² = 0.597), with the three-way shared fraction accounting for 28%, highlighting strong coupling among pedogenic, climatic, and topographic drivers. Ecological risk indices revealed clear spatial differentiation between systems. Highland valleys exhibited greater contamination intensity, spatial heterogeneity, and more frequent high-risk categories according to PLI, mCd, and SRI. In contrast, coastal valleys showed more homogeneous and diffuse accumulation patterns associated with long-term agricultural intensification. These findings underscore the need for regionally adapted soil monitoring frameworks that incorporate environmental gradients in the assessment and management of PTE-related ecological risk in agricultural landscapes.
Mathematical modeling of the germination and growth of Leucaena leucocephala under different substrates and nursery conditions
(Polish Society of Agricultural Engineering, 2026-05-28) Sauceo Uriarte, José Américo; Milla Pino, Manuel Emilio; Quispe Ccasa, Hurley Abel; Segura Portocarrero, Gleni Tatiana; Vásquez Pérez, Héctor Vladimir; Gongora Bardales, Deiner Jhonel; Maicelo Quintana, Jorge Luis
Livestock production in tropical regions is predominantly extensive and relies heavily on native or monoculture pastures, which often prove insufficient for ruminant nutrition. The incorporation of Leucaena leucocephala into silvopastoral systems represents a promising strategy due to its high forage quality; however, information on its early establishment under nursery conditions remains limited. This study aimed to model the germination dynamics and early seedling growth of L. leucocephala under different substrate compositions during the nursery phase. Germination percentage and daily plant height were recorded over a 30-day period. Treatment effects were evaluated using analysis of variance (ANOVA) and growth dynamics were described using non-linear sigmoidal models (Gompertz, Logistic, von Bertalanffy, and Brody). Significant differences in germination rate among substrates were detected (p<0.05), whereas no significant effect of substrate on plant height was observed during the evaluation period (p>0.05). Among the evaluated models, von Bertalanffy, Gompertz, and Logistic functions provided the best fit for plant height based on R² and AIC criteria. Although some models showed high R² values for germination, elevated AIC values suggest limited biological adequacy. These findings highlight the usefulness of predictive modeling to support nursery management decisions, optimize substrate selection, and facilitate the establishment of L. leucocephala in sustainable silvopastoral systems.
Metabarcoding reveals rhizosphere microbiome differences in healthy and basal rot-affected dragon fruit plants
(Elsevier B.V., 2026-02-18) Guelac Santillan, Marly; Fernandez Castro, Paul; Huaman Pilco, Angel F.; Estrada Cañari, Richard; Rodríguez Grados, Pedro; Arbizu, Carlos I.
The rhizosphere microbiome plays a crucial role in plant health, yet its dynamics in Selenicereus megalanthus (yellow dragon fruit) remain poorly understood. This study employed high-throughput sequencing to characterize the bacterial and fungal communities in the rhizosphere of healthy and basal rot-affected plants across four commercial production sites in Amazonas department from Peru. Amplicon sequencing Metagenomics Sequencing (WOBI) targeting to 16S rRNA (for bacteria) and ITS (for fungi) gene regions show differences in microbial community structure associated with plant health status. Multivariate analyses revealed a clear disease-driven reassembly of the bacterial microbiome, marked by the loss of health-associated taxa (Xanthobacteraceae, Geminicoccaceae, Nocardioidaceae) and enrichment of oligotrophic and stress-tolerant groups (Nitrososphaeraceae, Acidobacteriaceae Subgroup 1). In contrast, fungal assemblages displayed structural inertia, responding primarily through pathogen-associated increases in Nectriaceae. Soil physicochemistry particularly pH, exchangeable aluminum, and nutrient levels modulated the strength of bacterial differentiation, highlighting the role of edaphic filters in microbiome resilience. Our findings provide evidence of a bacterial-centered dysbiosis associated with basal stem rot in S. megalanthus, while positioning fungal communities as structurally resilient components of the holobiont. Together, these results outline a framework in which disease is linked to altered plant microbe soil feedbacks rather than pathogen presence alone, and suggest that bacterial assemblages could inform the development of microbiome-based early-warning indicators and soil health strategies for sustainable dragon fruit management.