Agronomic Performance and Genotype by Environment Interaction of Hybrid Maize Across Different Land Typologies in South Sulawesi

Technical Summary: Agronomic Performance and Genotype by Environment Interaction of Hybrid Maize Across Different Land Typologies in South Sulawesi

Problem Statement
Hybrid maize (*Zea mays L.) production in Indonesia faces significant constraints due to the variability of agroecological conditions across regions. The genotype × environment (G×E) interaction causes substantial differences in the agronomic performance of genotypes when cultivated across diverse land typologies. This phenomenon often results in nationally superior varieties failing to reach their yield potential when planted in environments different from their selection sites, due to mismatches between genetic expression and environmental pressures such as abiotic stress (drought, soil acidity) and biotic stress. Consequently, there is a critical need to identify stable and adaptive genotypes suitable for specific zones, particularly in South Sulawesi, which possesses contrasting land typologies ranging from fertile mid-altitude zones to dry, acidic drylands.

Methodology
The study was conducted between July and September 2025 in two contrasting locations in South Sulawesi:

1. Sinoa (Bantaeng District): A fertile, mid-altitude agroclimatic zone with relatively humid conditions and good soil fertility.
2. Moncongloe (Maros District): A dry climate zone characterized by acidic dryland soil texture, low soil moisture, and rapid drainage.

The experimental design was a Randomised Complete Block Design (RCBD) with 10 treatments (seven candidate hybrid varieties: JH MAS 01–07, and three check varieties: ADV777, NK306, and NK212) replicated three times, resulting in 30 plots per location. Each plot measured 2.8 m × 5 m with a plant spacing of 70 cm × 20 cm.

Agronomic parameters evaluated included plant height, leaf length, leaf width, leaf angle, stem diameter, ear height, and the number of ear rows. Data were analyzed using Analysis of Variance (ANOVA) at a 5% significance level. Where significant differences were detected, means were compared using the Least Significant Difference (LSD) test. Path analysis was also conducted to determine direct and indirect effects of agronomic characters on yield.

Key Results
The analysis of variance (ANOVA) revealed that environmental factors (replications/locations) were the dominant determinant of agronomic character expression, significantly outweighing genotypic factors for several key traits:

• Significant Environmental Effects: The environmental factor had a highly significant effect on plant height ($p=0.001$), stem diameter ($p=0.000$), and ear height ($p=0.007$).
• Non-Significant Genotypic Effects: The genotype factor did not significantly affect any of the tested parameters ($p > 0.05$ for all traits), indicating that the genetic differences among the tested hybrids did not produce statistically distinct variations in these specific agronomic traits under the given conditions.
• Stable Traits: Leaf angle, leaf length, leaf width, and the number of ear rows showed low variability and were not significantly affected by either genotype or environment, suggesting these are canalized, stable traits.

Performance of Specific Genotypes:

• NK212: Recorded the highest mean plant height (214.73 cm) and the largest stem diameter (19.55 mm).
• NK306: Exhibited the second-largest stem diameter (17.97 mm).
• JH MAS 03: Showed the lowest plant height (186.53 cm).

Significance and Claims
The paper concludes that for the hybrid maize genotypes tested in South Sulawesi, environmental conditions are the primary driver of phenotypic expression for vegetative and reproductive structural traits, rather than genetic potential. The lack of significant genotypic effects suggests that the tested candidate hybrids possess a relatively narrow genetic base or that their responses did not diverge significantly under the specific range of environmental conditions tested.

The study provides a scientific basis for variety recommendations and zone-based cultivation strategies in South Sulawesi. It underscores the necessity of multi-location and multi-environment testing to identify genotypes with broad adaptability or specific stability. The authors assert that while the current data offers valuable baseline information on agronomic characters, comprehensive G×E stability analyses (such as AMMI or GGE Biplot) across multiple growing seasons are required to fully elucidate specific genotype adaptations for precision agriculture strategies in diverse agroecosystems.