Minimizing the use of chemical fertilizers and investigating an appropriate ecofriendly level of nitrogen fertilizer is the key to sustainable agriculture. Sugarcane is the main cash crop of China, especially in the Guangxi region. Information regarding the effect of different nitrogen levels on sugarcane rhizosphere microbiota is still limited. In this study, we evaluated the effect of four different levels of nitrogen fertilizers on rhizosphere bacterial composition using high throughput sequencing, along with soil physiochemical properties, sugarcane agronomic and yield performance. The four treatment combinations were CK (no fertilizers), L (Low, 100 kg ha–1), M (Medium, 150 kg ha–1), and H (High, 200 kg ha–1). The results showed that M nitrogen application significantly altered the rhizosphere bacterial community, soil properties, and sugarcane yield. The richness and evenness of the bacterial community were higher in M treatment than CK. In M treatment important bacterial phyla Acidobacteria and Proteobacteria increased by 47 and 71%, respectively; and at genus level, Acidothermus and Bradyrhizobium increased by 77.2 and 30.3%, respectively, compared to CK. Principal component analysis (PCA) and cluster analysis further confirmed the level of differences among the treatments. The PCA analysis explained 80% of the total variation among the treatments. Spearmen correlation heatmap showed that environmental factors such as pH, AP (available phosphorous), AK (available potassium), and SCAT (soil catalase) were the key factors impacting sugarcane rhizosphere microbiome composition. The H and L nitrogen application alter the bacterial community and sugarcane performance but the M nitrogen application appears to be ecofriendly, productive, and an appropriate nitrogen application rate that could be further used in the Guangxi region.
Background Ratooning in sugarcane is a crucial strategy for ensuring the long-term sustainability of the sugarcane industry. Knowledge gap relating to the interaction between rhizosphere microbiome and ratooning crop, particularly the impact of different sugarcane cultivars on the rhizosphere microbiome in consecutive ratooning, requires additional research. The response of two different sugarcane cultivars, viz ZZ-1 and ZZ-13, were evaluated in consecutive ratooning towards the rhizosphere microbial community and cane morphological characters. Results Significant changes in the rhizosphere microbiome were observed in the second ratooning over the years. Several important genera were observed in high abundance during the second ratooning, including Burkholderia, Sphingomonas, Bradyzhizobium, and Acidothermus. Cultivar ZZ-13 caused more alterations in the rhizosphere microbiome than ZZ-1, resulting in a more favorable rhizosphere environment for sugarcane growth. The genotypes also varied in terms of nutrients and enzyme activity over the years. There were significant differences between the genotypes and year for number of stalks and yield was significant for genotypes, years and genotype × year. Conclusion This finding will help to understand thorough interactions between rhizosphere microorganisms and ratoon sugarcane and lay the foundation for promoting and maximizing yield as far as possible. In the future, this work can serve as guidance in sugarcane husbandry, mainly in Guangxi, China.
Background Plant microbiomes and soil are bridged by rhizobacteria, maintaining and improving plant health and growth in different aspects. This study was conducted in the field station of the Guangxi University, Fusui, China. We investigated soil nutrients, root morphology and rhizosphere bacterial composition, and community structures in 18 sugarcane genotypes concerning sugar content under the same environmental condition. Results Most of the rhizosphere microbiomes of these genotypes exhibited similar bacterial compositions. However, the evaluated genotypes harbored a significant effect and difference in the abundance of operational taxonomic units and bacterial composition in the rhizosphere compartments. Alpha diversity analysis on the rhizosphere microbiome showed a significant difference in the bacterial diversity (Shannon index, p < 0.001) and OTU richness (Chao1, p < 0.001). The principal coordinate analysis (PCoA) and hierarchical cluster analysis revealed that the genotype replicated samples grouped, indicating their similarity. Besides, these genotypes also differed significantly in terms of root structure and soil properties. A significant genotypic effect (p < 0.05) was found in the root traits except for rooting depth. The soil chemical properties were significantly different among the evaluated genotypes. Furthermore, sucrose content was strongly correlated with the total root length (TRL) and rooting depth. Genotypes (FN-1702, GUC-3, ZZ-13, ZZ-10, ZZ-6) were the best performing and distinct in bacterial diversity, root structure, soil parameters and sucrose content. Conclusion The results showed a closely related and highly conserved bacterial community of the rhizosphere microbiome. The rhizosphere microbiome diversity and related bacterial communities were highly associated with the relevant plant taxa, probably at the order level. As a result, it is possible to conclude that the host genotype and the same environmental condition influenced the rhizosphere microbiome via root phenes. Future research regarding plant phenes and microbiome functional groups could be considered an essential factor. Graphic abstract
Aim The purpose of this study was to investigate the different combination of testcrosses for morphological and yield relating traits and to investigate general combining ability of the inbred lines. Materials and Methods This research was conducted at The University of Agriculture Peshawar, Pakistan during 2016. Line x-tester analysis was used to test general combining ability (GCA) effects of 24 S4 lines of sweet corn. Alpha lattice design with two replications and two checks was used during the experiment. Research data were recorded on various flowering, morphological and yield parameters. Results Highly significant variations were recorded among the testcrosses for the studied traits except anthesis silking interval (ASI), 100-kernel weight. Minimum days to tasseling (48-days) and silking (53.5-days) was exhibited by pop-syn-swt (9-4)×synthetic sweet. GCA effect was -2.14 for tasseling and -2.00 for silking. Maximum value (3.5-days) for ASI was recorded for Pop-synswt 1(8-3)×synthetic sweet, while GCA effect for ASI was -0.71. Lowest plant height (129.8 cm) was recorded for pop-syn-swt 1(3-3)×synthetic sweet, while GCA effect for plant height was observed to be -14.79. Maximum cob length (16.6 cm) was revealed by pop-syn-swt 1(12-2)×synthetic sweet. For cob length GCA effect of 1.01 was recorded. Maximum 100 kernel weight (31.3 g) was estimated for pop-syn-swt 1(2-1)×synthetic sweet. GCA effect of 1.85 was recorded for 100-kernel weight. Highest mean (7143.9 kg ha-1) for grain yield was recorded for pop-syn-swt 1(9-4)×synthetic sweet. GCA effect for grain yield was found to be 1370.93. Conclusion Generally a low GCA value, either positive or negative indicates that the mean of a parent does not largely vary from its offsprings. In contrast, high GCA value suggests that parent is either superior or inferior to the general mean and it has high heritability and less environmental effects. Based on the findings in this research, the above mentioned testcrosses can be included in future sweet corn breeding programs where early flowering and yield attributes is desired.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.