RESUMEN
This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980-81 to 2020-21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices.
Asunto(s)
Oryza , Oryza/crecimiento & desarrollo , Análisis Multivariante , Modelos Logísticos , India , Productos Agrícolas/crecimiento & desarrollo , Agricultura/métodos , Tiempo (Meteorología) , Conceptos MeteorológicosRESUMEN
Mitochondria are central to endothelial cell activation and angiogenesis, with the RNA polymerase mitochondrial (POLRMT) serving as a key protein in regulating mitochondrial transcription and oxidative phosphorylation. In our study, we examined the impact of POLRMT on angiogenesis and found that its silencing or knockout (KO) in human umbilical vein endothelial cells (HUVECs) and other endothelial cells resulted in robust anti-angiogenic effects, impeding cell proliferation, migration, and capillary tube formation. Depletion of POLRMT led to impaired mitochondrial function, characterized by mitochondrial depolarization, oxidative stress, lipid oxidation, DNA damage, and reduced ATP production, along with significant apoptosis activation. Conversely, overexpressing POLRMT promoted angiogenic activity in the endothelial cells. In vivo experiments demonstrated that endothelial knockdown of POLRMT, by intravitreous injection of endothelial specific POLRMT shRNA adeno-associated virus, inhibited retinal angiogenesis. In addition, inhibiting POLRMT with a first-in-class inhibitor IMT1 exerted significant anti-angiogenic impact in vitro and in vivo. Significantly elevated expression of POLRMT was observed in the retinal tissues of streptozotocin-induced diabetic retinopathy (DR) mice. POLRMT endothelial knockdown inhibited pathological retinal angiogenesis and mitigated retinal ganglion cell (RGC) degeneration in DR mice. At last, POLRMT expression exhibited a substantial increase in the retinal proliferative membrane tissues of human DR patients. These findings collectively establish the indispensable role of POLRMT in angiogenesis, both in vitro and in vivo.