Variables climáticas y rendimiento de arroz (Oryza sativa L.) en la región Loreto, periodo 2021–2024
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Universidad Nacional de la Amazonía Peruana
Abstract
El cultivo de arroz (Oryza sativa L.) es una actividad para la seguridad. No obstante, su productividad depende de las condiciones climáticas, especialmente de la temperatura y la humedad relativa. La investigación tuvo como objetivo analizar la relación entre estas variables climáticas y el rendimiento del arroz durante el periodo 2021–2024, con el propósito de identificar condiciones de riesgo y generar información útil para mejorar el manejo agronómico y la sostenibilidad del sistema productivo. El estudio se desarrolló bajo un enfoque cuantitativo, correlacional y diseño no experimental. Se utilizaron series temporales mensuales construidas a partir de datos secundarios de rendimiento y registros climáticos. La información fue procesada mediante estadística descriptiva, análisis de correlación, regresión lineal múltiple y pruebas diagnósticas para evaluar la validez del modelo. Los resultados mostraron que la humedad relativa y la temperatura influyen diferenciadamente sobre el rendimiento del cultivo. Los mayores niveles de producción se observaron cuando la humedad relativa fue alta y las temperaturas se mantuvieron en rangos moderados. En contraste, los periodos caracterizados por baja humedad relativa y temperaturas elevadas estuvieron asociados con menores rendimientos y mayores riesgos productivos. Además, el análisis permitió identificar una etapa crítica entre agosto y noviembre. Se concluye que la variabilidad climática constituye un factor determinante en la productividad arrocera de Loreto. Por ello, se recomienda fortalecer el manejo del riego, la planificación agrícola estacional y el monitoreo climático, así como desarrollar estudios que incorporen otras variables y modelos predictivos para optimizar la toma de decisiones.
Rice cultivation (Oryza sativa L.) is a safety activity. However, their productivity depends on climatic conditions, especially temperature and relative humidity. The research aimed to analyze the relationship between these climatic variables and rice yield during the period 2021–2024, with the purpose of identifying risk conditions and generating useful information to improve agronomic management and the sustainability of the production system. The study was developed under a quantitative, correlational approach and non experimental design. Monthly time series constructed from secondary performance data and climate records were used. The information was processed using descriptive statistics, correlation analysis, multiple linear regression and diagnostic tests to evaluate the validity of the model. The results showed that relative humidity and temperature have a differentiated influence on crop yield. The highest production levels were observed when relative humidity was high and temperatures remained in moderate ranges. In contrast, periods characterized by low relative humidity and high temperatures were associated with lower yields and higher production risks. In addition, the analysis made it possible to identify a critical stage between August and November. It is concluded that climatic variability is a determining factor in rice productivity in Loreto. Therefore, it is recommended to strengthen irrigation management, seasonal agricultural planning and climate monitoring, as well as to develop studies that incorporate other variables and predictive models to optimize decision-making.
Rice cultivation (Oryza sativa L.) is a safety activity. However, their productivity depends on climatic conditions, especially temperature and relative humidity. The research aimed to analyze the relationship between these climatic variables and rice yield during the period 2021–2024, with the purpose of identifying risk conditions and generating useful information to improve agronomic management and the sustainability of the production system. The study was developed under a quantitative, correlational approach and non experimental design. Monthly time series constructed from secondary performance data and climate records were used. The information was processed using descriptive statistics, correlation analysis, multiple linear regression and diagnostic tests to evaluate the validity of the model. The results showed that relative humidity and temperature have a differentiated influence on crop yield. The highest production levels were observed when relative humidity was high and temperatures remained in moderate ranges. In contrast, periods characterized by low relative humidity and high temperatures were associated with lower yields and higher production risks. In addition, the analysis made it possible to identify a critical stage between August and November. It is concluded that climatic variability is a determining factor in rice productivity in Loreto. Therefore, it is recommended to strengthen irrigation management, seasonal agricultural planning and climate monitoring, as well as to develop studies that incorporate other variables and predictive models to optimize decision-making.
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