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This study introduces a novel Hybrid Ensemble Machine-Learning (HEML) algorithm to merge long-term satellite-based reanalysis precipitation products (SRPPs), enabling the estimation of super drought events in the Lake Victoria Basin (LVB) during the period of 1984 to 2019. This study considers three widely used Machine learning (ML) models, including RF (Random Forest), GBM (Gradient Boosting Machine), and KNN (k-nearest Neighbors), for the emerging HEML approach. The three SRPPs, including CHIRPS (Climate Hazards Group Infra-Red Precipitation with Station), ERA5-Land, and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record), were used to merge for developing new precipitation estimates from HEML model. Additionally, classification and regression models were employed as base learners in developing this algorithm. The newly developed HEML datasets were compared with other ML and SRPP products for super-drought monitoring. The Standardized precipitation evapotranspiration index (SPEI) was used to estimate super drought characteristics, including Drought frequency (DF), Drought Duration (DD), and Drought Intensity (DI) from machine learning and SRPPs products in LVB and compared with RG observation. The results revealed that the HEML algorithm shows excellent performance (CC = 0.93) compared to the single ML merging method and SRPPs against observation. Furthermore, the HEML merging product adeptly captures the spatiotemporal patterns of super drought characteristics during both training (1984-2009) and testing (2010-2019) periods. This research offers crucial insights for near-real-time drought monitoring, water resource management, and informed policy decisions.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11180181 | PMC |
http://dx.doi.org/10.1038/s41598-024-61520-6 | DOI Listing |
Plant Commun
December 2024
Shanghai Agrobiological Gene Center, Shanghai, 201106, China; Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai, 201106, China.
Dissecting the drought resistance (DR) mechanism and designing drought-resistant rice varieties are promising strategies to address the challenge of climate change. Here, we selected a typical drought-avoidant (DA) variety IRAT109 and drought-tolerant (DT) variety Hanhui15 as the parents to develop a stable recombinant inbred line (RIL) population (F, 1,262 lines). The de novo assembled genomes of both parents were released.
View Article and Find Full Text PDFFront Plant Sci
October 2024
Shandong Academy of Forestry, Jinan, China.
Super absorbent polymers (SAP) provide moisture conditions that allow plant growth-promoting rhizobacteria (PGPR) to enter the soil for acclimatization and strain propagation. However, the effects of SAP co-applied with PGPR on the physiological characteristics of leaves and rhizosphere soil enzyme activities of poplar seedlings are not well understood. Here, a pot experiment using one-year-old poplar seedlings with five treatments, normal watering, drought stress (DR), drought stress + SAP (DR+SAP), drought stress + (DR +PGPR) and drought stress + SAP + (DR+S+P), was performed to analyze the contents of non-enzymatic antioxidants, osmotic regulators and hormones in leaves, as well as rhizosphere soil enzyme activities.
View Article and Find Full Text PDFHeliyon
October 2024
College of Agronomy, Henan Agricultural University, Zhengzhou, Henan, 450046, China.
Periodic drought adversely affects the growth and yield of summer crops in the Huang-Huai-Hai Plain. Drought-rewatering practice as one of the important agronomic measures to improve crop drought resistance. A field experiment was conducted to investigate practice physiological, biochemical, and molecular responses of maize seedling after two rounds of repeated drought and rewatering treatments.
View Article and Find Full Text PDFGenome Biol
October 2024
National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070, China.
Background: In response to drought stress (DS), plants undergo complex processes that entail significant transcriptome reprogramming. However, the intricate relationship between the dynamic alterations in the three-dimensional (3D) genome and the modulation of gene co-expression in drought responses remains a relatively unexplored area.
Results: In this study, we reconstruct high-resolution 3D genome maps based on genomic regions marked by H3K9ac, an active histone modification that dynamically responds to soil water variations in rice.
Front Plant Sci
July 2024
Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
Introduction: Rice, one of the major staple food crops is frequently affected by various biotic/abiotic stresses including drought, salinity, submergence, heat, Bacterial leaf blight, Brown plant hopper, Gall midge, Stem borer, Leaf folder etc. Sustained increase of yield growth is highly necessary to meet the projected demand in rice production during the year 2050. Hence, development of high yielding and multiple stress tolerant rice varieties adapted to wider environments will serve the need.
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