Analyzing Various Maize Varieties Grown Organically: VIT Vellore's Phenotypic, Yield, and Canopy Data

The dataset presented here is an ensemble of various plant and yield traits collected over a season of maize from the VIT University farm, Vellore. The data consists of 15 columns which are classified under four classes namely vegetative traits, yield traits, canopy temperature, and chlorophyll readings of randomly selected and tagged plants. Artificial Intelligence techniques like Machine Learning and Deep Learning can be applied to optimize the yield of the selected genotypes.

本数据集为于韦洛尔（Vellore）市VIT大学（VIT University）农场采集的一季玉米植株性状与产量性状集合。该数据集共包含15列数据，划分为四大类别，分别为营养生长性状、产量性状、冠层温度以及随机选取并标记植株的叶绿素读数。可通过机器学习（Machine Learning）与深度学习（Deep Learning）等人工智能技术，优化选定基因型的产量。