Scientia Agropecuaria https://revistas.unitru.edu.pe/index.php/scientiaagrop <p><strong>Scientia Ag</strong><strong>ropecuaria</strong> es una revista científica de periodicidad trimestral, que fomenta la generación y diseminación del conocimiento científico, publicando trabajos originales y de revisión en el campo de las ciencias agropecuarias<em>. </em>Actualmente está indizada en: SCOPUS, ESCI (Web of Science), DOAJ, Chemical Abstracts Services, AGRIS/FAO, Redalyc, SciELO, REDIB, DIALNET, BASE, MIAR, LATINDEX, Sherpa Romeo.</p> es-ES <p>Los autores que publican en esta revista aceptan los siguientes términos:</p> <p>a. Los autores conservan los derechos de autor y conceden a la revista el derecho publicación, simultáneamente licenciada bajo una licencia de <a href="https://creativecommons.org/licenses/by-nc/4.0/" target="_blank" rel="noopener">Creative Commons</a> que permite a otros compartir el trabajo, pero citando la publicación inicial en esta revista.</p> <p>b. Los autores pueden celebrar acuerdos contractuales adicionales separados para la distribución no exclusiva de la versión publicada de la obra de la revista (por ejemplo, publicarla en un repositorio institucional o publicarla en un libro), pero citando la publicación inicial en esta revista.</p> <p>c. Se permite y anima a los autores a publicar su trabajo en línea (por ejemplo, en repositorios institucionales o en su sitio web) antes y durante el proceso de presentación, ya que puede conducir a intercambios productivos, así como una mayor citación del trabajo publicado (ver <a href="http://opcit.eprints.org/oacitation-biblio.html" target="_blank" rel="noopener">efecto del acceso abierto</a>).</p> sci.agropecu@unitru.edu.pe (Dr. Raúl Siche) sci.agropecu@unitru.edu.pe (Raúl Siche) mié, 27 mar 2024 12:46:48 +0000 OJS 3.2.1.1 http://blogs.law.harvard.edu/tech/rss 60 Biotechnological tools for genetic improvement of Trichoderma https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5897 <p><em>Trichoderma</em> is a cosmopolitan fungus widely distributed around the world. The different uses of this beneficial fungus are varied in several industries, like agriculture, textile, and paper, including the pharmaceutical industry. The genus <em>Trichoderma</em> has other mechanisms of action, including the production of different enzymes and secreted secondary metabolites used in various industries. The genomes of different <em>Trichoderma</em> species have been sequenced to identify the mechanisms for producing several compounds. The advancement of multiple technologies has allowed the development of transformation tools for the genetic improvement of <em>Trichoderma</em>, thus increasing biomass, primary and secondary metabolites, and enzymes. Therefore, genetic modification aims to increase compound production in several <em>Trichoderma</em> strains. Characterization of <em>Trichoderma</em> through gene expression analysis is essential for biotechnology applications. It helps counteract one of the most challenging problems for agriculture today, including climate change and the appearance of pathogens that attack crops with high commercial and food demand. In conclusion, this review analyzes various strategies to improve <em>Trichoderma</em> strains genetically and their multiple applications in the agricultural, textile, paper, and pharmaceutical industries. As a recommendation for future studies with potential impact, the optimization of specific genetic modifications in <em>Trichoderma</em> strains is recommended to improve their adaptability and effectiveness in combating emerging challenges in agriculture, especially those linked to climate change. Investigating possible synergies between genetically modified <em>Trichoderma</em> strains and environmentally sustainable agricultural practices could contribute to developing solutions for crop protection and yield improvement.</p> Liliana Villao-Uzho, Fernando Espinoza-Lozano, Luis Galarza-Romero, Efrén Santos-Ordóñez Derechos de autor 2024 Scientia Agropecuaria https://creativecommons.org/licenses/by-nc/4.0 https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5897 lun, 08 abr 2024 00:00:00 +0000 Evaluation of soil fertility index in organic, semi-organic, and conventional rice field management systems https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5318 <p>Rice farming in Madiun Regency implements three different management systems, that is organic, semi-organic, and conventional. The different implementation of these rice field management systems impacts soil fertility index and rice productivity. This purpose of this research was to know the effect of rice field management systems on soil fertility index and rice productivity in the Madiun Regency. The research uses an explorative descriptive qualitative method with a survey approach. Soil samples were taken using a random sampling method and 3 types of soil management systems (conventional, semi-organic and organic), and rice production samples were taken using an estimation method. The research results show that the soil fertility index ranges from 0.78 to 0.82, which is high. The highest soil fertility index is in the semi-organic management system and the lowest is in the organic management. The management system of semi-organic gave a response to the highest rice production of 6.89 tons/ha. Management system of semi-organic is a better management for increasing and maintaining soil fertility and crop production than conventional or organic. Farming activities results show that organic management systems increase the highest income, increasing 115.58% and 53.30% in semi-organic compared to conventional. The rice field management system has the effect of increasing the worm population density with the highest in the organic system, namely 4.19 individuals m<sup>-</sup><sup>2</sup>. The <em>Pontoscolex</em> worm type dominates the three management systems. There is a correlation between organic matter content and earthworms.</p> Suntoro Suntoro, Ganjar Herdiansyah, Heri Widijanto, Slamet Minardi, Febridita Sari Dewi Derechos de autor 2024 Scientia Agropecuaria https://creativecommons.org/licenses/by-nc/4.0 https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5318 mié, 27 mar 2024 00:00:00 +0000 Identificación del estado fitosanitario de árboles mediante aprendizaje automático e imágenes de muy alta resolución espacial https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5390 <p>Las enfermedades de los árboles contribuyen a importantes pérdidas económicas y de alimentos en el sector agrícola. La detección temprana de problemas fitosanitarios en árboles con métodos no destructivos resulta fundamental para garantizar la producción sostenible de naranja. Este trabajo presenta los resultados de una metodología diseñada para la identificación de árboles de naranja enfermos en una huerta ubicada en el cinturón citrícola de México, particularmente en la región de Rioverde, San Luis Potosí. Para ello, se tomaron imágenes con una cámara multiespectral de muy alta resolución espacial instalada en un vehículo aéreo no tripulado con las que se construyó un ortomosaico georreferenciado. Se emplearon seis clases temáticas para identificar los diferentes niveles de sanidad. Se utilizaron diferentes algoritmos de clasificación supervisada a nivel píxel que incluyen Random Forest (RF), K-Nearest Neighbor (KNN), Spectral Angle Mapper (SAM), Support Vector Machine (SVM), y Maximum Likelihood (ML). Considerando la exactitud de clasificación obtenida por cada uno de los algoritmos, se pueden ordenar de la siguiente manera: Maximum Likelihood (ML) con un 88,10%, Support Vector Machine (SVM) con un 77,38%, Spectral Angle Mapper (SAM) con un 76,19%, K-Nearest Neighbor (KNN) con un 64,68% y Random Forest (RF) con un 61,90%. Los resultados permitieron identificar el estado fitosanitario de todos los árboles de la huerta, con una exactitud aceptable y representan información valiosa de manejo para el productor.</p> Juan Carlos Díaz Rivera, Carlos Arturo Aguirre-Salado, Catarina Loredo-Osti, Martín Escoto-Rodríguez Derechos de autor 2024 Scientia Agropecuaria https://creativecommons.org/licenses/by-nc/4.0 https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5390 lun, 08 abr 2024 00:00:00 +0000 Effective method for simultaneous determination of abscisic acid, 3-indolacetic acid and gibberellic acid in commercial plant biostimulants by capillary electrophoresis with diode array detection https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5489 <p>Phytohormones, also known as plant hormones, are naturally occurring chemical compounds that regulate various physiological processes in plants. In this work, a capillary electrophoretic coupled to a diode array detector (CE-DAD) method was developed and validated for the simultaneous quantification of abscisic acid (ABA), 3-indolacetic acid (IAA), and gibberellic acid (GA3) in commercial plant biostimulants. Sample preparation was carried out by liquid-liquid extraction using ethyl acetate. CE separation was performed in a fused-silica capillary and background electrolyte (BGE) consisting of borate buffer (50 mM, pH 9.3) applying a high voltage of 20 kV, a pressure of 50 mbar, and injection time of 35 s. The ABA, IAA, and GA<sub>3 </sub>were detected at 254, 220 and 195 nm respectively. The CE-DAD method validation results showed acceptable specificity, linearity, accuracy, and precision in the concentration range of 10-100 µg/mL for all compounds according to the (International Conference Harmonisation) ICH guidelines. The proposed method was satisfactory applied to the analysis of cited plant hormones in biostimulants and suggest that sample preparation is a reliable step for extraction of phytohormones containing carboxyl groups. Therefore, the developed and validated method could be implemented as a low-cost and fast analytical tool for quality control purposes.</p> Ivan Chóez-Guaranda, Michael Rendon, Stalin Peralta, Andrea Villegas, Patricia Manzano Derechos de autor 2024 Scientia Agropecuaria https://creativecommons.org/licenses/by-nc/4.0 https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5489 lun, 08 abr 2024 00:00:00 +0000 Xylanase production by Penicillium sp. Pn004 and its application for grass hydrolysis: High value subproduct from non-centrifugal sugarcane bagasse and wheat bran https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5526 <p>Worldwide more than 7 billion tons of lignocellulosic biomass will be produced by 2025. In Colombia, these residues are mainly disposed of in rivers and open fields, and only 10% is reused and recycled. Non-centrifugal sugarcane bagasse (SCB) is a residue obtained after sugarcane juice extraction during the manufacturing process of <em>panela</em> and is mostly used as fuel for boilers at sugar mills. Wheat bran (WB) is the main waste from wheat flour production. Nonetheless, the chemical composition of these by-products makes them suitable for use as substrates for hemicellulolytic enzyme production from fungi. Here, a whole process for production in a solid-state fermentation system, recovery, and ultrafiltration process for concentration of xylanases by <em>Penicillium </em>sp. Pn004 is presented. The higher productivity (26.7 ± 1.59 U gds<sup>-1</sup> day-1) was reached on the fifth day of fermentation with an enzyme activity of 130.0 ± 7.95 U gds<sup>-1</sup>. The batch ultrafiltration process allowed increasing the xylanase activity up to 19-fold in the retentate, from 66.47 U mL<sup>-1</sup> to 1486.83 U mL<sup>-1</sup>, without reaching a steady state flux through the membrane. Finally, the enzymatic extract achieved a 43% release of sugar from kikuyu grass (<em>Cenchrus clandestinus</em>), showing its potential to be used as an additive for silage or for enzymatic saccharification of lignocellulosic materials for sugar production.</p> Anny Daniela Martínez, Amaury Blanco Paz, Vanessa Chavarro-Anzola, Juan Carlos Barrios Murcia, Eddy J. Bautista Derechos de autor 2024 Scientia Agropecuaria https://creativecommons.org/licenses/by-nc/4.0 https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5526 lun, 08 abr 2024 00:00:00 +0000