Maize Genomics and Genetics 2025, Vol.16, No.1, 34-44 http://cropscipublisher.com/index.php/mgg 37 4 Evaluation of Fresh Corn Germplasm Resources 4.1 Morphological and agronomic traits evaluation The evaluation of fresh corn germplasm resources involves assessing key morphological and agronomic traits such as yield, plant height, and flowering time. Yield is a critical trait, often influenced by various genetic and environmental factors. For instance, studies have shown that grain yield in maize can be significantly affected by plant density and environmental stress levels, with certain hybrids demonstrating substantial tolerance to high plant densities (Mansfield anf Mumm, 2014). Plant height and flowering time are also essential traits, with plant height showing a positive linear relationship to crude fiber content and flowering time correlating with other nutritional traits such as crude protein and starch (Alves and Filho, 2017). Additionally, the use of advanced phenotyping methods, such as UAV-based hyperspectral data, has proven effective in estimating grain yield and flowering time with high accuracy, thus aiding in the efficient selection of desirable traits (Fan et al., 2022). Ear characteristics and grain quality are pivotal in the evaluation of fresh corn germplasm. Traits such as kernel rows per ear, kernel length, and the number of ears per plant are crucial for determining overall grain quality and yield potential. Research has identified quantitative trait loci (QTLs) associated with these traits, highlighting the importance of genetic factors in improving ear characteristics. Moreover, the stability of these QTLs across different environments underscores the potential for breeding programs to develop maize varieties with superior grain quality and yield (Ragot et al., 1995). 4.2 Nutritional and quality traits evaluation The nutritional and quality traits of fresh corn germplasm are evaluated based on sugar content, texture, and flavor compounds. These traits are essential for consumer acceptance and marketability. The sugar content in maize, for example, is a key determinant of its sweetness and overall flavor profile. Advanced phenotyping technologies, such as hyperspectral imaging, enable monitoring of key growth stages in maize canopies, with a particular focus on the distribution and growth dynamics of tassels (Figure 2). By analyzing images from different growth stages, tassel regions and their spectral reflectance characteristics can be effectively identified. This provides data support for evaluating maize growth, optimizing fertilizer application, and predicting harvests, assisting breeders in selecting varieties with optimal sugar content and ideal texture (Fan et al., 2022). Additionally, the texture and flavor compounds of maize are influenced by its genetic makeup and environmental conditions, necessitating comprehensive evaluation across different growing environments (Mansfield and Mumm, 2014). Figure 2 Monitoring maize canopy growth stages based on hyperspectral imaging (Adopted from Fan et al., 2022) Image Caption: Canopy images of a maize plot at (a) the V6-V8 stage (41 DAS), (b) the VT stage (61 DAS), (c) the R1 stage (75 DAS), (d) the R3 stage (90 DAS), and (e) the R4 stage (103 DAS); The images were taken by the hyperspectral camera at a 42 m height and composited using the red (620 nm), green (530 nm), and blue (465 nm) bands from the hyperspectral imagery. Red boxes highlight the tassel parts on the maize canopy (Adopted from Fan et al., 2022)
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