首页|Study Findings on Machine Learning Are Outlined in Reports from Department of Ag riculture [Genetic Control of Important Yield Attributing Cha racters Predicted Through Machine Learning In Segregating Generations of Intersp ecific Crosses of Tomato ...]

Study Findings on Machine Learning Are Outlined in Reports from Department of Ag riculture [Genetic Control of Important Yield Attributing Cha racters Predicted Through Machine Learning In Segregating Generations of Intersp ecific Crosses of Tomato ...]

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating in West Bengal, India, by NewsRx journalists, research stated, "Skewness and kurtosis were analy sed using mean data from the F2 to F5 generations of three interspecific tomato hybrids, incorporating two feral species: Solanum pimpinellifolium (Currant Toma to) and Solanum lycopersicum var. cerasiformae (Cherry Tomato). The study canter ed on three crucial traits impacting fruit yield, with predictions generated thr ough artificial neural networks and multiple linear regression." Financial support for this research came from National Bureau of Plant Genetic R esources, New Delhi, India. The news reporters obtained a quote from the research from the Department of Agr iculture, "Plant height (PH), fruit weight (FW) and test weight of seeds (TSW) w ere identified as the most sensitive traits influencing fruit yield/plant in the Alisa Craig Aft x Solanum pimpinellifolium (Cross 1) and the Berika x Solanum l ycopersicum var. cerasiformae (Cross 2). In contrast, fruits per plant (FPP), FW and TSW emerged as the key contributors to fruit yield in the BCT 115 dg x Sola num lycopersicum var. cerasiformae (Cross 3). Skewness and kurtosis distribution suggested complementary gene action with fewer number of segregating genes for PH in Cross 1, FW across All three cross combinations, TSW in Cross 1, and FPP i n Cross 3. Duplicate gene action with fewer genes could be predicted for TSW in Cross 2 and Cross 3 while complementary gene action and a greater number of segr egating genes were suggested for PH in Cross 2. Moderate-to-high narrow sense he ritability was determined for All the characters suggesting phenotypic selection to be rewarding. Isolation of seven promising segregates based on the important yield attributers from three inter-specific hybrids in F5 generation establishe d the worth of advancing interspecific hybrids."

West BengalIndiaAsiaCyborgsEmerg ing TechnologiesGeneticsMachine LearningDepartment of Agriculture

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Sep.30)