In China, due to labor shortages and increasing labor costs, manual topping is gradually being replaced by chemical capping with mepiquat chloride (DPC). External chemicals can adjust plant growth by affecting endogenous hormones. Based on the hormone changes combined with the development of the main stem of cotton plants, a comparative experiment was conducted in 2019 and 2020 to determine the regulatory mechanism of the growth of the cotton main stem after chemical capping. In the experiment, two treatment times (T1: 12 July, T2: 18 July) and two treatment agents (CA [chemical capping agent] and DPC) were set, the hormone (auxin IAA, abscisic acid ABA, Gibberellin GA₃ and Zeatin ZR) concentrations at the top of main stem (0–5 and 5–10 cm) were continuously measured and the main stem development situation was observed and recorded. The results showed that after chemical capping, the IAA concentration decreased firstly and increased later, lower than that of CK. ABA concentration increased significantly and GA₃ concentration decreased significantly compared with CK. ZR concentrations fluctuated obviously at T1 and gently at T2. In terms of main stem growth, the plant height, number of fruit branches and average length of upper internode (fifth and above) were decreased compared with CK, while the CA treatment was inhibited more strongly than the DPC treatment. To conclude, chemical capping operation affected the hormone concentration at the plant apex significantly and effectively regulated plant development. In comparison with DPC treatment, CA regulated hormones effectively, which is favorable for conducive reasonable plant shaping.

Background: Mung bean (Vigna radiata L.) has a short growth period, long suitable sowing period, drought and barren tolerance, wide adaptability, nitrogen fixation and other characteristics. China is one of the original centers of mung bean, with a cultivation history of more than 2000 years. The current study aimed to assess the present mung bean germplasm in Liaoning Province scientifically, to provide a theoretical basis for collection, preservation, innovative and usage of mung bean germplasm resources. Methods: This study was conducted during 2011-2015 and 170 mung bean germplasm collections were selected from the germplasm resource bank of Liaoning Academy of Agricultural Sciences. Fourty six agronomic traits, including 34 quality traits and 12 quantitative traits, were observed and recorded. Data were comprehensively evaluated by multivariate analysis, i.e., diversity analysis, principal component analysis, correlation analysis, grey relational analysis and cluster analysis. Result: It was observed that mung bean resources have abundant diversity for exploitation in breeding programs. The traits pod-bearing capacity and vegetative growth capacity of plants were found closely related to yield. Germplasm lines with superior performance for yield characteristics, growth period, plant height and grain size were selected which included one high-yield and one early-matured and high-yield resource.

Aims: This study evaluated millet germplasms in Liaoning Province to support the collection, preservation and innovation of millet germplasm resources. Methods: The study was conducted from 2018 to 2020, involved the selection of 105 millet germplasm resources from the Germplasm Bank of the Liaoning Academy of Agricultural Sciences (LAAS), the observation and recording of 31 traits, and the application of multivariate analysis methods to assess phenotypic diversity. Results: From the diversity analysis and correlation analysis, it was found that the tested traits had abundant diversity and complex correlations among them. Principal component analysis (PCA) comprehensively analyzed all quantitative traits and extracted seven principal components. Grey relational analysis (GRA) highlighted the varied contributions of different traits to yield. Through systematic cluster analysis (SCA), the resources were categorized into six groups at Euclidean distance of 17.09. K-mean cluster analysis determined the distribution interval and central value of each trait, then identified resources with desirable traits. Conclusion: The results revealed resources that possess characteristics such as upthrow seedling leaves, more tillers and branches, larger and well-formed ears, and lodging resistance prefer to higher grain yield. It was also discovered that the subear internode length (SIL) could be an indicator for maturity selection. Four specific resources, namely, Dungu No. 1, Xiao-li-xiang, Basen Shengu, and Yuhuanggu No. 1, were identified for further breeding and practical applications.

Millet (Setaria italica [L.]) originated in China and is one of the oldest cultivated crops in the world. The current study aims to assess the present millet germplasms in Liaoning Province scientifically, in order to provide a theoretical basis for the collection, preservation, innovation, and use of millet germplasm resources. This study was conducted from 2018 to 2020. A total of 105 millet germplasm collections were selected from the germplasm resource bank of the Liaoning Academy of Agricultural Sciences. Thirty-one agronomic traits, including 19 qualitative traits and 12 quantitative traits, were observed and recorded. Data were comprehensively evaluated via multivariate analyses, including diversity analysis, correlation analysis, principal component analysis, grey relational analysis, and cluster analysis. Results show that millet resources have abundant diversity, traits represent ear size and ear-bearing capacity were found to be closely related to yield. In high-yield breeding, the resources with upthrow seedling leaves, more tillers, more branches, large ears, and long growth periods should be selected as cross parents. Meanwhile, one early-maturing and lower plant resource, one early-maturing and small-grain resource, one later-maturing and higher plant and big-ear resource, and one later-maturing and big-grain resource were screened for excellent millet breeding.

Aims This study evaluated millet germplasms in Liaoning Province to support the collection, preservation and innovation of millet germplasm resources. Methods The study was conducted from 2018 to 2020, involved the selection of 105 millet germplasm resources from the Germplasm Bank of the Liaoning Academy of Agricultural Sciences (LAAS), the observation and recording of 31 traits, and the application of multivariate analysis methods to assess phenotypic diversity. Results From the diversity analysis and correlation analysis, it was found that the tested traits had abundant diversity and complex correlations among them. principal component analysis (PCA) comprehensively analyzed all quantitative traits and extracted 7 principal components. Grey relational analysis (GRA) highlighted the varied contributions of different traits to yield. Through systematic cluster analysis, the resources were categorized into six groups at Euclidean distance of 17.09. K-mean cluster analysis determined the distribution interval and central value of each trait, then identified resources with desirable traits. Conclusion The results revealed resources that possess characteristics such as upthrow seedling leaves, more tillers and branches, larger and well-formed ears, and lodging resistance prefer to higher grain yield. It was also discovered that the subear internode length (SIL) could be an indicator for maturity selection. Four specific resources, namely, Dungu No. 1, Xiao-li-xiang, Basen Shengu, and Yuhuanggu No. 1, were identified for further breeding and practical applications.