Artículos científicos

URI permanente para esta colecciónhttps://repositorio.inia.gob.pe/handle/20.500.12955/8

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MultiProduct Optimization of Cedrelinga cateniformis (Ducke) Ducke in Different Plantation Systems in the Peruvian Amazon
(MDPI, 2025-01-16) Baselly-Villanueva, Juan Rodrigo; Fernández-Sandoval, Andrés; Salazar-Hinostroza, Evelin Judith; Cárdenas-Rengifo, Gloria Patricia; Puerta, Ronald; Chuquizuta Trigoso, Tony Steven; Rufasto-Peralta, Yennifer Lisbeth; Vallejos-Torres, Geomar; Goycochea Casas, Gianmarco; Araújo Junior, Carlos Alberto; Quiñónez-Barraza, Gerónimo; Álvarez-Álvarez, Pedro; Garcia Leite, Helio
This study addressed multi-product optimization in Cedrelinga cateniformis plantations in the Peruvian Amazon, aiming to maximize volumetric yields of logs and sawn lumber. Data from seven plantations of different ages and types, established on degraded land, were analyzed by using ten stem profile models to predict taper and optimize wood use. In addition, the structure of each plantation was evaluated using diameter distributions and height–diameter ratios; log and sawn timber production was optimized using SigmaE 2.0 software. The Garay model proved most effective, providing high predictive accuracy (adjusted R2 values up to 0.963) and biological realism. Marked differences in volumetric yield were observed between plantations: older and more widely spaced plantations produced higher timber volumes. Logs of optimal length (1.83–3.05 m) and larger dimension wood (e.g., 25.40 × 5.08 cm) were identified as key contributors to maximizing volumetric yields. The highest yields were observed in mature plantations, in which the total log volume reached 508.1 m3ha−1 and the sawn lumber volume 333.6 m3ha−1 . The findings demonstrate the power of data-driven decision-making in the timber industry. By combining precise modeling and optimization techniques, we developed a framework that enables sawmill operators to maximize log and lumber yields. The insights gained from this research can be used to improve operational efficiency and reduce waste, ultimately leading to increased profitability. These practices promote support for smallholders and the forestry industry while contributing to the long-term development of the Peruvian Amazon.
Crecimiento del “shihuahuaco” Dipteryx ferrea (Ducke) Ducke en plantaciones bajo diferentes espaciamientos y tipos de suelo en Ucayali, Amazonía peruana
(Universidad Nacional Agraria La Molina, Facultad de Ciencias Forestales, 2025-01-10) Flores, Ymber
Se presentan los resultados de los ensayos experimentales con Dipteryx ferrea (Ducke) Ducke, especie forestal conocida como “shihuahuaco”, establecidas bajo cuatro sistemas forestales y agroforestales diferentes en el Centro Experimental Alexander von Humboldt, Ucayali, a una altitud de 225 m.s.n.m, diferenciados por el arreglo espacial implementado, el espaciamiento inicial y tipo de suelo, y con 11 años de edad. Se obtuvieron mediciones de la altura total, el diámetro a la altura del pecho (DAP), el área basal y el volumen maderable de las plantaciones. Los resultados muestran el potencial de D. ferrea en términos de crecimiento, supervivencia y productividad en las plantaciones a campo abierto puras y mixtas. El sistema 1, en suelo Plinthic acrisol, fisiografía plana y distanciamiento de 5 × 5 m, presenta el más alto valor de DAP promedio, altura total promedio y altura dominante, con 20.23 cm, 13.9 m y 16.8 m respectivamente. Estos resultados son estadísticamente superiores (p < 0.05) a los de otras plantaciones analizadas y muestran un rendimiento prometedor. En productividad, el sistema 3, en suelo Plinthic gleysol, fisiografía plana y distanciamiento de 2 × 2 m, presenta el más alto valor de área basal y volumen de madera rolliza con 38.40 m2/ha y 243.3 m3/ha respectivamente, muy superior estadísticamente a los otros sistemas, pero muy influido también por la alta densidad de la plantación. Estos hallazgos sugieren perspectivas alentadoras para el establecimiento de plantaciones de D. ferrea en plantaciones forestales.
Sex-induced changes in microbial eukaryotes and prokaryotes in gastrointestinal tract of simmental cattle
(MDPI, 2024-11-15) Rojas Cruz, Diorman; Estrada Cañari, Richard; Romero Avila, Yolanda Madelein; Figueroa Venegas, Deyanira Antonella; Quilcate Pairazamán, Carlos Enrique; Ganoza Roncal, Jorge Juan; Maicelo, Jorge L.; Coila, Pedro; Alvarado, Wigoberto; Cayo Colca, Ilse S.
This study investigates gender-based differences in the gut microbiota of Simmental cattle, focusing on bacterial, archaeal, and fungal communities. Fecal samples were collected and analyzed using high-throughput sequencing, with taxonomic classification performed through the SILVA and UNITE databases. Alpha and beta diversity metrics were assessed, revealing significant differences in the diversity and composition of archaeal communities between males and females. Notably, females exhibited higher alpha diversity in archaea, while beta diversity analyses indicated distinct clustering of bacterial and archaeal communities by gender. The study also identified correlations between specific microbial taxa and hematological parameters, with Treponema and Methanosphaera showing gender-specific associations that may influence cattle health and productivity. These findings highlight the importance of considering gender in microbiota-related research and suggest that gender-specific management strategies could optimize livestock performance. Future research should explore the role of sex hormones in shaping these microbial differences.
Changes in gut microbiota in peruvian cattle genetic nucleus by breed and correlations with beef quality
(MDPI, 2024-11-29) Quilcate Pairazamán, Carlos Enrique; Estrada Cañari, Richard; Romero Avila, Yolanda Madelein; Rojas Cruz, Diorman; Mamani Chullo, Rolando; Hañari Quispe, Renán Dilton; Aliaga, Mery; Galindo, Walter; Vásquez, Héctor V.; Maicelo, Jorge L.; Arbizu, Carlos I.
This study evaluated the gut microbiota and meat quality traits in 11 healthy female cattle from the Huaral region of Peru, including 5 Angus, 3 Braunvieh, and 3 F1 Simmental × Braunvieh. All cattle were 18 months old and maintained on a consistent lifelong diet. Meat quality traits, including loin area, fat thickness, muscle depth, and marbling, were assessed in vivo using ultrasonography. Fecal samples were collected for microbiota analysis, and DNA was extracted for 16S and 18S rRNA sequencing to characterize bacterial, fungal, and protist communities. Significant correlations were observed between microbial genera and meat traits: Christensenellaceae R-7 and Alistipes were positively associated with marbling and muscle area, while Rikenellaceae RC9 showed a negative correlation with fat thickness. Among fungi, Candida positively correlated with marbling, while Trichosporon was negatively associated with muscle depth. For protists, Entodinium negatively correlated with fat thickness and marbling. Alpha diversity varied by breed, with Angus showing greater bacterial diversity, and beta diversity analyses indicated a strong breed influence on microbial composition. These findings suggest that microbial composition, shaped by breed and dietary consistency, could serve as an indicator of meat quality, offering insights into gut microbiota’s role in optimizing cattle production.
Development and application of microsatellite markers for genetic diversity assessment and construction of a core collection of Myrciaria dubia (Kunth) Mcvaugh germplasm from the peruvian Amazon
(MDPI, 2024-10-25) Castro, Juan C.; Vasquez Guizado, Stalin J.; Vigil, Bianca E.; Ascue, Francisco; Rojas Villa, Naysha; Paredes, Jae D.; Cobos, Marianela; Castro, Carlos G.; Motta, Daniel E.; Adrianzén, Pedro M.; Imán Correa, Sixto Alfredo; Maddox, J. Dylan
The Amazonian shrub Myrciaria dubia (camu-camu) produces vitamin C-rich fruits of growing commercial interest. However, sustainable utilization requires assessment and protection of the genetic diversity of the available germplasm. This study aimed to develop and apply microsatellite markers to assess genetic diversity and construct a core collection of M. dubia germplasm from the Peruvian Amazon. Sixteen polymorphic microsatellite loci were developed using an enrichment approach. The evaluation of 336 genotypes from 43 accessions of the germplasm bank, originating from eight river basins, was conducted using these newly developed markers. Genetic diversity parameters, including observed and expected heterozygosity, were calculated. Analysis of molecular variance (AMOVA) was performed to assess the distribution of genetic variation within and among accessions and river basins. Bayesian clustering analysis was employed to infer population structure. A core collection was constructed to maximize allelic richness. High genetic diversity was observed, with heterozygosity values ranging from 0.468 to 0.644 (observed) and 0.684 to 0.817 (expected) at the river basin level. AMOVA indicated significant genetic variation within (73–86%) compared to among (14–27%) accessions and river basins. Bayesian clustering detected ten genetic clusters, with several degrees of admixture among river basins, except for the genetically homogeneous Putumayo River basin. A core collection comprising 84 plant genotypes (25% of the full collection) was established, representing 90.82% of the overall allelic diversity. These results have important implications for M. dubia conservation strategies and breeding programs, in demonstrating a need for genetic connectivity between populations but preserving unique genetic resources in isolated basins. These results validate the expected levels of diversity and population subdivision in a crop and stress the need to secure genetically diverse germplasms, underscoring the importance of thorough genetic characterization for ex situ germplasm management.
Comparación de características testiculares mediante ultrasonografía B mode y Doppler en alpacas (Vicugna pacos) tui y adultos
(Universidad Nacional Mayor de San Marcos, Facultad de Medicina Veterinaria, 2024-10-31) Pérez Durand, Manuel G.; Quispe Barriga, Yesenia M.; Mamani Macedo, Edilberto; Gandarillas Espezúa, Daniel; Luque Mamani, Natalio; Medina Suca, Guido; Mamani Cato, Rubén Herberht; Perez Guerra, Uri H.
El objetivo de estudio fue comparar las características testiculares mediante la ultrasonografía B mode y Doppler en alpacas tui y adultos. El estudio fue realizado en el Centro Experimental Chuquibambilla de la Universidad Nacional del Altiplano, Puno, Perú, durante la época reproductiva (marzo). Se utilizaron 15 tui machos (G1) de 12 a 14 meses de edad y 14 adultos (G2) de 24 a 36 meses. Se evaluaron las características ultrasonográficas B mode (largo [mm], ancho [mm], área [cm2] y volumen testicular [cm3]) y Doppler (índice de resistencia [IR], índice de pulsatibidad [IP] y área vascular testicular [AVT]) con un equipo Draminski 4Vet® y un transductor micro convexo y lineal con una frecuencia de 9 MHz. Lo datos fueron analizados mediante un diseño factorial de 2x2. El largo, ancho, volumen y área testicular dentro de cada grupo etario no presentó diferencias significativas entre el testículo derecho e izquierdo; sin embargo, las medidas de las alpacas adultos fueron significativamente mayores que en las tuis (p<0.05). El IR fue similar en ambos grupos etarios, pero el AVT fue superior en los tuis en comparación con los adultos.
Intake and digestibility of four rations with different fiber levels in alpacas (Vicugna pacos)
(Springer Nature, 2024-10-01) Obregón Cruz, Ana B.; Gómez, Carlos A.; Osorio Zavala, Cesar Mauro; Van Saun, Robert J.
The aim of this study was to evaluated the impact of different fibre levels in alpaca diet on voluntary feed intake and apparent digestibility, and to estimate the digestibility of organic matter (OMD) from the content of crude protein (CP) in feces. The study was carried out with twelve alpacas (36.7 ± 6.4 kg body weight- BW), which were offered 4 treatments with different neutral detergent fiber content (NDF. T1: 40.3%; T2: 62%; T3: 68%; T4: 72%) under a switch back design. Absolute daily dry matter intake (DMI) was higher for T1 (678 g/d) than T4 (312 g/d) (p ≥ 005). NDF intake was similar between treatments when related to BW or MW (on average 1% BW and 22 g/kg MW. p ≥ 0.05). Water intake (L/kg DMI) was higher in T1 compared to the other treatments, with values ranging from 2.9 L/kg DMI(T1) to 2.8 L/kg DMI(T4), respectively (p ≤ 0.05). Digestibility of dry matter, organic matter and CP was higher in T1 than in the other treatments, with average values ranging from 72% for T1 to 32% for T4 (p ≤ 0.05). NDF digestibility was similar among treatments (p ≥ 0.05). The regression equation generated to predict OMD (y) was as follows: y = 0.360 + 0.08294*fecal CP (g/kg OM). Further studies will indicate whether faecal nitrogen can be used to estimate digestibility and hence diet quality in South American camelids.
Cloud computing application for the analysis of land use and land cover changes in dry forests of Peru
(International Information and Engineering Technology Association (IIETA), 2024-09-30) Barboza, Elgar; Salazar Coronel, Wilian; Gálvez Paucar, David; Valqui Valqui, Lamberto; Valqui, Leandro; Zagaceta, Luis H.; Gonzales, Jhony; Vásquez, Héctor V.; Arbizu, Carlos I.
Dry forests are ecosystems of great importance worldwide, but in recent decades they have been affected by climate change and changes in land use. In this study, we evaluated land use and land cover changes (LULC) in dry forests in Peru between 2017 and 2021 using Sentinel-2 images, and cloud processing with Machine Learning (ML) models. The results reported a mapping with accuracies above 85% with an increase in bare soil, urban areas and open dry forest, and reduction in the area of crops and dense dry forest. Protected natural areas lost 2.47% of their conserved surface area and the areas with the greatest degree of land use impact are located in the center and north of the study area. The study provides information that can help in the management of dry forests in northern Peru.
Optimizing landfill site selection using fuzzy-AHP and GIS for sustainable urban planning
(Salehan Institute of Higher Education, 2024-06-01) Zabaleta Santisteban, Jhon Antony; Salas López, Rolando; Rojas Briceño, Nilton B.; Gómez Fernández, Darwin; Medina Medina, Angel J.; Tuesta Trauco, Katerin M.; Rivera Fernandez, Abner S.; Lévano Crisóstomo, José; Oliva Cruz, Manuel; Silva López, Jhonsy O.
Careful landfill selection with minimal environmental impact is vital for urban planners. This study aims to identify suitable sites for controlled landfills using Fuzzy-AHP integrated with Remote Sensing and GIS, considering a 20-year projection of population and solid waste generation. Initially, twelve sub-criteria were identified, grouped into environmental, socio-economic, and physical categories, and then weighted using paired comparison matrices involving nine experts. The sub-criteria were rasterized and classified into four suitability levels. The weighted overlay of sub-criteria maps generated a territorial suitability model. Within the Alto Utcubamba Commonwealth (Amazonas, Peru), 0.069%, 41.70%, 66.934%, 0.20%, and 12.4% of the territory are suitable, moderately suitable, less suitable, unsuitable, and restricted, respectively, for landfill establishment. Subsequently, 16 highly suitable sites were selected based on the required area (S4 polygons ≥ 0.505 ha) in line with the projected solid waste generation over 20 years. Of the 16 selected areas, only 15 met the shape index. The model showed high accuracy (AUC = 0.784) during validation. Furthermore, this study provides a comprehensive framework for making decisions about waste management in developing countries, enhancing understanding of key factors in selecting landfill sites. It also offers a deeper insight into global and local factors that determine the suitability of landfill sites.
Multicriteria evaluation and remote sensing approach to identifying degraded soil areas in northwest Peru
(Taylor & Francis Group, 2024-12-23) Arce Inga, Marielita; Atalaya Marin, Nilton; Barboza Castillo, Elgar; Tarrillo Julca, Ever; Chuquibala Checan, Beimer; Tineo Flores, Daniel; Fernandez Zarate, Franklin Hitler; Cruz Luis, Juancarlos Alejandro; Goñas Goñas, Malluri; Gómez Fernández, Darwin
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.
Analyzing urban expansion and land use dynamics in Bagua Grande and Chachapoyas using cloud computing and predictive modeling
(Springer Nature, 2024-09-26) Barboza, Elgar; Turpo, Efrain Y.; Salas Lopez, Rolando; Silva López, Jhonsy O.; Cruz Luis, Juancarlos Alejandro; Vásquez, Héctor V.; Purohit, Sanju; Aslam, Muhammad; Tariq, Aqil
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.
Green manuring and fertilization on rice (Oryza sativa L.): a peruvian Amazon study
(Instituto Nacional de Innovación Agraria, 2024-12-02) Arévalo Aranda, Yuri Gandhi; Rodríguez Toribio, Elmer; Rosillo Cordova, Leodan; Díaz Chuquizuta, Henry; Torres Chávez, Edson Esmith; Cruz Luis, Juancarlos; Siqueira Bahia, Rita de Cássia; Pérez Porras, Wendy Elizabeth
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.
Use of vegetable covers as a strategy to reduce soil erosión and increase the yield of corn (Zea mays L.)
(Universidad de Tarapaca, 2023-12-31) Sanabria Quispe, Samuel; Mendoza Dávalos, Katia; Palomino Paccua, Luz Angélica; Figueroa Venegas, Deyanira Antonella; Pocomucha, Vicente; Cosme de la Cruz, Roberto Carlos
Soil degradation is a problem facing agriculture, with water being the most important erosive agent, affecting, among others, crop yields. The objective of this study was to know the effect of four plant covers on soil erosion and starchy corn yield, in three locations in the Ayacucho region (Peru) during the 2018 - 2019 agricultural season. Five treatments were assigned: control, clover cover, vetch cover, vetch-oat cover, and mulch, in corn plots under a randomized complete block design (RCBD), with four blocks. Combined analysis of variance was used to evaluate the results. It was observed that soil erosion and corn yield were significantly (P < 0.001) influenced by plant cover and locations. Vetch-oat and clover cover significantly reduced soil erosion (–53 and –36%, respectively) due to the higher leaf biomass produced by both (6131 and 6052 kg ha–1, respectively). Clover cover produced the highest corn yield (3749 kg ha–1; +78%); while vetch-oats produced the lowest (1955 kg ha–1), without significant differences with the control. The highest production of biomass, N and C of the foliar coverages was produced in the location with the least slope; while the highest performance occurred in steeper areas. Clover cover turned out to be a better option to reduce soil erosion and increase corn yield.
Characterization and typification of small-scale goat production systems in the highlands of southeast Peru
(Frontiers Media, 2024-11-14) Palomino Guerrera, Walter; Godoy Padilla, David; Huaripaucar Huancahuari, Joseen; Sessarego Dávila, Emmanuel; Trillo Zárate, Fritz; Cruz Luis, Juancarlos
Goat breeding in Peru is one of the main activities of smallholders. Goats are distributed in different agroecological zones and regions of the country, developing under heterogeneity of production systems, making it difficult to understand goat breeders’ socioeconomic, technological, and productive situations. This study aimed to characterize and typify the goat production systems in the highlands of southeast Peru. A survey was conducted with 91 goat farmers from five districts of Ayacucho, Peru, using a structured and individualized questionnaire administered on their farms. The socio-economic, productive, and commercial characteristics of the goat production systems were recorded. A multiple correspondence analysis (MCA) and hierarchical classification analysis (HCA) were performed to establish a typology of the smallholders. The results reveal that the breeding system is extensive, where there is no breeding program, with natural pastures and crop stubble being the source of food for the herds. Only slightly more than half (54%) carry out a deworming program. Farmers were categorized into three different groups, corresponding to three different farming systems: Group 1 farmers raised goats solely for home consumption; Group 2 breeders raised goats for both consumption and marketing of surplus products (cheese, milk, and meat), and Group 3 farmed focused on producing cheese and goat kids and selling to local markets. The study provides valuable insights that will help design effective breeding strategies to develop sustainable goat farming in the region, considering different production systems and their respective socio-economic and trade dynamics. This classification will be essential for tailoring development programs to the specific needs of each group, promoting better use of resources, improving productivity, and enhancing the livelihoods of smallholder goat producers in Peru
Using UAV images and phenotypic traits to predict potato morphology and yield in Peru
(MDPI, 2024-10-24) Ccopi Trucios, Dennis; Ortega Quispe, Kevin; Castañeda Tinco, Italo; Rios Chavarria, Claudia; Enriquez Pinedo, Lucia; Patricio Rosales, Solanch; Ore Aquino, Zoila; Casanova Nuñez-Melgar, David; Agurto Piñarreta, Alex; Zúñiga López, Luz Noemí; Urquizo Barrera, Julio
Precision agriculture aims to improve crop management using advanced analytical tools.In this context, the objective of this study is to develop an innovative predictive model to estimate the yield and morphological quality, such as the circularity and length–width ratio of potato tubers, based on phenotypic characteristics of plants and data captured through spectral cameras equipped on UAVs. For this purpose, the experiment was carried out at the Santa Ana Experimental Station in the central Peruvian Andes, where advanced potato clones were planted in December 2023 under three levels of fertilization. Random Forest, XGBoost, and Support Vector Machine models were used to predict yield and quality parameters, such as circularity and the length–width ratio. The results showed that Random Forest and XGBoost achieved high accuracy in yield prediction (R2 > 0.74). In contrast, the prediction of morphological quality was less accurate, with Random Forest standing out as the most reliable model (R2 = 0.55 for circularity). Spectral data significantly improved the predictive capacity compared to agronomic data alone. We conclude that integrating spectral índices and multitemporal data into predictive models improved the accuracy in estimating yield and certain morphological traits, offering key opportunities to optimize agricultural management.
Phenotypic diversity of morphological traits of pitahaya (Hylocereus spp.) and its agronomic potential in the Amazonas region, Peru
(MDPI, 2024-11-02) Santos Pelaez, Julio Cesar; Saravia Navarro, David; Cruz Delgado, Julio H. I.; Del Carpio Salas, Miguel Angel; Barboza, Elgar; Casanova Núñez-Melgar, David Pavel
Pitahaya (Hylocereus spp.) is an economically significant cactus fruit in Peru, renowned for its rich nutritional profile and antioxidant properties while exhibiting wide biological diversity. This study aimed to morphologically characterize seven pitahaya accessions using qualitative and quantitative descriptors related to the cladodes, flowers, and fruits. Univariate and multivariate (FAMD, PCA, MCA, and clustering) analyses were employed to identify and classify the accessions based on their morphological traits. The analyses revealed three distinct groups: one consisting solely of AC.07; another with AC.02, AC.04, and AC.06; and a third including AC.01, AC.03, and AC.05. The first group exhibited superior characteristics, particularly in fruit traits such as the stigma lobe count (23.3), number of bracts (26.5 mm), and length of apical bracts (15.75 mm). The second group recorded the highest spine count (3.21), bract length (16.95 mm), and awn thickness (5.12 mm). The third group had the highest bract count (37) and an average locule number (23.65). These findings highlight the significant morphological diversity among the accessions, indicating the potential for classification and selection in pitahaya cultivation. The potential of AC.07 stands out in terms of its agronomic qualities, such as its fruit weight (451.93 g) and pulp weight (292.5 g), surpassing the other accessions.
Draft genome sequence data of Fusarium verticillioides strain REC01, a phytopathogen isolated from a Peruvian maize
(Elsevier, 2024-09-23) Estrada Cañari, Richard; Aragón, Liliana; Pérez Porras, Wendy E.; Romero Avila, Yolanda; Martínez Vidal, Gabriel; García, Karina; Cruz Luis, Juancarlos; Arbizu Berrocal, Carlos I.
Fusarium verticillioides represents a major phytopathogenic threat to maize crops worldwide. In this study, we present genomic sequence data of a phytopathogen isolated from a maize stem that shows obvious signs of vascular rot. Using rigorous microbiological identification techniques, we correlated the disease symptoms observed in an affected maize region with the presence of the pathogen. Subsequently, the pathogen was cultured in a suitable fungal growth medium and extensive morphological characterization was performed. In addition, a pathogenicity test was carried out in a DCA model with three treatments and seven repetitions. De novo assembly from Illumina Novaseq 60 0 0 sequencing yielded 456 contigs, which together constitute a 42.8 Mb genome assembly with a GC % content of 48.26. Subsequent comparative analyses were performed with other Fusarium genomes available in the NCBI database.
Inoculation with Azospirillum brasilense as a strategy to reduce nitrogen fertilization in cultivating purple maize (Zea mays l.) in the Inter-andean valleys of Peru
(MDPI, 2024-10-21) Condori Ataupillco, Tatiana; Alarcón Romani, Susan; Huasasquiche Sarmiento, Lucero; García Blásquez, Cayo; Padilla Castro, César; Velásquez Mantari, José; Solórzano Acosta, Richard
Purple maize has gained global significance due to its numerous nutraceutical benefits. However, sustaining its production typically requires high doses of nitrogen fertilizers, which, when applied in excess, can contaminate vital resources such as soil and water. Inoculation with nitrogenfixing microorganisms, such as those from the Azospirillum genus, has emerged as an alternative to partially or fully replace nitrogen fertilizers. This study aimed to evaluate the inoculation effect with A. brasilense and varying nitrogen fertilization levels on the yield and quality of purple maize. The experiment was carried out using a randomized complete block design (RCBD) with a 2 × 5 factorial arrangement and five replications. Treatments comprised two inoculation levels (control without inoculation and inoculation with A. brasilense) under five nitrogen doses (0, 30, 60, 90, and 120 kg・ha−1, applied as urea). Inoculation with A. brasilense resulted in a 10.5% increase in plant height, a 16.7% increase in root length, a 21.3% increase in aboveground fresh biomass, a 30.1% increase in root fresh biomass, and a 27.7% increase in leaf nitrogen concentration compared to the no inoculated control. Regarding yield, the inoculated plants surpassed the control in both purple maize yield (kg・ha−1) and cob weight by 21.8% and 11.6%, respectively. Across all fertilization levels and parameters assessed, the inoculated treatments outperformed the control. Furthermore, for parameters, namely plant height, leaf nitrogen content, and cob dimensions (length, diameter, and weight), the A. brasilense inoculation treatment with 90 kg N・ha−1 was statistically equivalent or superior to the non-inoculated control with 120 kg N・ha−1. These results indicate that inoculation with A. brasilense positively impacted purple maize at all nitrogen levels tested and improved nitrogen use efficiency, enabling a reduction of 30 kg N・ha-1 without compromising performance in key parameters.
Estimation of forage biomass in oat (Avena sativa) using agronomic variables through UAV multispectral imaging
(MDPI, 2024-10-06) Urquizo Barrera, Julio Cesar; Ccopi Trucios, Dennis; Ortega Quispe, Kevin; Castañeda Tinco, Italo; Patricio Rosales, Solanch; Passuni Huayta, Jorge; Figueroa Venegas, Deyanira; Enriquez Pinedo, Lucia; Ore Aquino, Zoila; Pizarro Carcausto, Samuel
Accurate and timely estimation of oat biomass is crucial for the development of sustainable and efficient agricultural practices. This research focused on estimating and predicting forage oat biomass using UAV and agronomic variables. A Matrice 300 equipped with a multispectral camera was used for 14 flights, capturing 21 spectral indices per flight. Concurrently, agronomic data were collected at six stages synchronized with UAV flights. Data analysis involved correlations and Principal Component Analysis (PCA) to identify significant variables. Predictive models for forage biomass were developed using various machine learning techniques: linear regression, Random Forests (RFs), Support Vector Machines (SVMs), and Neural Networks (NNs). The Random Forest model showed the best performance, with a coefficient of determination R2 of 0.52 on the test set, followed by Support Vector Machines with an R2 of 0.50. Differences in root mean square error (RMSE) and mean absolute error (MAE) among the models highlighted variations in prediction accuracy. This study underscores the effectiveness of photogrammetry, UAV, and machine learning in estimating forage biomass, demonstrating that the proposed approach can provide relatively accurate estimations for this purpose.
Forage yield and nutritive value of plantain and chicory for livestock feed at high altitudes in Peru
(John Wiley & Sons Inc., 2024-10-10) Vallejos Fernández, Luis A.; Guillén, Ricardo; Pinares Patiño, César; García Ticllacuri, Rubén; Muñoz Vilchez, Yudith Yohany; Quilcate, Carlos Enrique; Alvarez García, Wuesley Yusmein
Background: Evaluation of forage resources is vital for the sustainability of livestock farming in the South American Andes, especially under conditions of low water availability for irrigation and acid soils. Methods: We evaluated the productivity and nutritive value of two cultivars of chicory (Cichorium intybus L.) and one of plantain (Plantago lanceolata L.) in three high‐altitude sites (AL) of the northern highlands of Peru: AL‐I: 2300–2800 m.a.s.l, AL‐II: 2801–3300 m.a.s.l. and AL‐III: 3301–3800 m.a.s.l., for 1 year. The parameters evaluated were dry matter yield (DMY), plant height (PH), growth rate (GR) and nutritional value. Results: Plantain achieved the greatest annual DMY (ADMY), PH and GR compared to the two chicory cultivars (9.34, 9.56 and 13.39 Mg ha−1 for Puna II and Sese 100 chicory and Tonic plantain, respectively; p = 0.0019). The greatest ADMY and GR occurred at AL‐I. Regarding nutritional value, differences were observed only for in vitro digestibility of dry matter and metabolisable energy with chicory cultivars higher than plantain. Conclusions: The results indicate that the three cultivars evaluated may be used as a nutritional supplement in cattle feed, associated with grasses because they have high nutritive value suitable for milk production in the mountain regions of Peru.

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