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Full-Text Articles in Life Sciences
Impact Of Early-Season Postemergence Co-Applications Of Foliar And Residual Herbicides On Crop Injury, Growth, And Yield In 2,4-D- And Dicamba-Tolerant Cotton (Gossypium Hirsutum L.), Logan N. Vallee
LSU Master's Theses
Studies were conducted in 2021 through 2023 at the LSU AgCenter Dean Lee Research and Extension Center near Alexandria, LA to determine the sensitivity of 2,4-D- or dicamba- tolerant cotton (Gossypium hirsutum L.) to an early season application of a Group 15 and foliar-only herbicides. Both studies were randomized complete block designs with a two-factorial arrangement of treatments with four replications. In the dicamba-tolerant cotton study, Factor A consisted of no foliar-herbicide, dicamba alone, glyphosate alone, or dicamba plus glyphosate. Factor B consisted of either no Group 15 residual herbicide, acetochlor, or S-metolachlor. In the 2,4-D- tolerant cotton …
Machine Learning-Based Soybean Yield Prediction And Optimizing Lidar-Mounted Uav Efficiency, Leticia Santos
Machine Learning-Based Soybean Yield Prediction And Optimizing Lidar-Mounted Uav Efficiency, Leticia Santos
LSU Master's Theses
The first chapter of this thesis explores the predictive capabilities of random forests algorithm on datasets obtained from field plot experiments on crop management systems in soybean. Furthermore, the chapter presents a complementary analysis of model performance according to dataset sizes and two techniques on how to impute and deal with missing data. Random forests are being compared with standard statistical techniques such as linear regression on a well-structured, information-rich agronomic experiment. The key findings of this chapter includes the best hyperparameters adjustment and the identification of the dataset threshold for optimal algorithms performance. The second chapter has a research …