Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses.

Bread wheat is a vital staple crop worldwide; including in Ethiopia, but its production is prone to various environmental constraints and yield reduction associated with adaptation. To identify adaptable genotypes, a total of 12 bread wheat genotypes (G1 to G12) were evaluated for their genotype-environment interaction (GEI) and stability across three different environments for two years using Additive Main Effect and Multiplicative Interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplots analysis. GEI is a common phenomenon in crop improvement and is of significant importance in genotype assessment and recommendation. According to combined analysis of variance, grain yield was considerably impacted by environments, genotypes, and GEI. AMMI and GGE biplots analysis also provided insights into the performance and stability of the genotypes across diverse environmental conditions. Among the 12 genotypes, G6 was selected by AMMI biplot analysis as adaptive and high-yielding genotype; G5 and G7 demonstrated high stability and minimal interaction with the environment, as evidenced by their IPCA1 values. G7 was identified as the most stable and high-yielding genotype. The GGE biplot's polygon view revealed that the highest grain yield was obtained from G6 in environment three (E3). E3 was selected as the ideal environment by the GGE biplot. The top three stable genotypes identified by AMMI stability value (ASV) were G5, G7, and G10, while the most stable genotype determined by Genotype Selection Index (GSI) was G7. Even though G6 was a high yielder, it was found to be unstable according to ASV and ranked third in stability according to GSI. Based on the study's findings, the GGE biplot genotype view for grain yield identified Tay genotype (G6) to be the most ideal genotype due to its high grain yield and stability in diverse environments. G7 showed similar characteristics and was also stable. These findings provide valuable insights to breeders and researchers for selecting high-yielding and stable, as well as high-yielding specifically adapted genotypes.

Mitigation of ammonia volatilization from organic and inorganic nitrogen sources applied to soil using water hyacinth biochars.

The recent global population explosion has increased people's food demand. To meet this demand, huge amounts of nitrogen (N) fertilizer have been applied in the worldwide. However, ammonia (NH3) volatilization is one of the primary factors of N loss from soil after N application causing decrease crop N utilization efficiency and productivity. Incubation experiments were conducted on an acidic clayey soil with two different N sources (urea and anaerobic digestion effluent; ADE), two differently-produced biochars, and three biochar application rates (0%, 0.25%, and 1.0% w/w). Ammonia volatilization was lower from urea (14.0-23.5 mg N kg-1) and ADE (11.3-21.0 mg N kg-1) with biochar application than those without biochar (40.1 and 26.2 mg N kg-1 from urea and ADE alone, respectively). Biochar application significantly mitigated volatilization and reduction percentages for urea and ADE were 40%-64% and 18%-55%, respectively. 1.0% biochar application mitigated volatilization significantly compared to 0.25% application regardless of N source and biochar types. Possible mechanism for volatilization mitigation for urea and ADE were increased N immobilization by soil microorganisms and accelerated net nitrification rate due to increased soil nitrifying bacteria, respectively. Overall, our results clarified different mechanisms for N volatilization mitigation from different (inorganic vs. organic) N sources with biochar application.