| Study on relationships among maize ear traits in Guanzhong region based on structural equation model |
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| DOI：10.7606/j.issn.1000-7601.2025.01.16 |
| Key Words: maize field environment ear traits structural equation model |
| Author Name | Affiliation | | WANG Naijiang | College of Land Resources and Surveying & Mapping Engineering, Shandong Agriculture and Engineering University, Ji’nan, Shandong 250100,China； College of Soil and Water Conservation Science and Engineering (Institute of Soil and Water Conservation), Northwest A&F University, Yangling, Shaanxi 712100，China | | LIU Lu | College of Land Resources and Surveying & Mapping Engineering, Shandong Agriculture and Engineering University, Ji’nan, Shandong 250100,China | | FENG Hao | College of Soil and Water Conservation Science and Engineering (Institute of Soil and Water Conservation), Northwest A&F University, Yangling, Shaanxi 712100，China； State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China | | WEI Yongsheng | College of Life Sciences, Northwest A&F University, Yangling, Shaanxi 712100, China |
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| Abstract: |
| In this study, a in\|situ field experiment was conducted from 2014 to 2016 at Yangling District, Shaanxi Province. According to local field management practices, thirty\|three treatments including two main treatments (rain\|fed and irrigation) and five secondary treatments (no\|tillage as well as different irrigation quotas, inorganic fertilization application rates, organic materials, and mulching practices) were designed. The maize ear length (EL), ear diameter (ED), kernel row number (KRN), kernel number per row (KNR), 100-kernel weight (HKW), and kernel weight per ear (KWE) in fields were investigated. Structural equation model was used to quantify the relationship EL-ED-KRN-KNR-HKW-KWE for revealing the causal effect among ear traits. The results showed that six ear traits were vulnerable to changing field environment with coefficient of variation (CV) from 10.87% to 22.49%. The variation magnitude of six ear traits was moderate, KWE was most senstive to field environment, and HKW was second. There was a poor fitting between initial structural equation model and field measured data. However, for modified structural equation model, six fitting indices fell within the reasonable ranges. HKW had the greatest effect on KWE with total effect of 0.677, followed by KRN, EL, KNR, and ED with that of 0.554, 0.463, 0.283, and 0.102, respectively. The effect on HKW was KNR>EL>KRN>ED with total effect of -0.734, -0.398, 0.318 and 0.151, respectively. The total effect on KNR was 0.939 for EL and -0.167 for KRN. The total effect of EL on ED (0.606) was greater than that of KRN on ED (0.272). These findings provide theoretical reference for increasing maize grain yield by improving ear traits in Guanzhong region. |
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