ArticleBiology2024
Differences in Physiological and Agronomic Traits and Evaluation of Adaptation of Seven Maize Varieties.
Article in Biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
To better understand the growth adaptability of various maize varieties to the climate of the Alar region in Southern Xinjiang Province, an experiment was conducted using seven distinct maize varieties as test materials. A one-way randomized block design was applied to both experimental groups. In 2021 and 2022, a total of 19 indicators were observed for comparative analysis, including antioxidant enzyme activities and agronomic traits. Principal component analysis and cluster analysis were used to evaluate the adaptability of the maize varieties. The findings revealed that: (1) All seven maize varieties exhibited robust growth, with notable differences in their respective trait profiles. Specifically, the yield traits of Jin'ai 588 and Denghai 3672 showed relatively consistent performance over the two-year period. (2) Five principal components (100-kernel weight, bald tip length, catalase (CAT), number of leaves, and angle of leaf pinch at the ear) were extracted from the 19 traits via principal component analysis, with a cumulative contribution rate of 84.689%. This represented the majority of the information regarding the seven maize varieties. After calculating the comprehensive index F value, the results indicated that Xinyu 66 and Denghai 3672 had high composite scores, suggesting high production potential and suitability for cultivation in this region. Conversely, Xinyu 24 showed the lowest composite score, indicating that it is not suitable for planting in this area. (3) Ultimately, the seven maize varieties were categorized into three groups through cluster analysis; this is the same as the result of principal component analysis. This classification provides a reference for the promotion and utilization of different varieties in the southern border region and aims to optimize the comprehensive trait selection of the varieties studied.
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