Stability Performance of Inductively Coupled Plasma Mass Spectrometry-Phenotyped Kernel Minerals Concentration and Grain Yield in Maize in Different Agro-Climatic Zones

Abstract

Deficiency of iron and zinc causes micronutrient malnutrition or hidden hunger, which severely affects ~25% of global population. Genetic biofortification of maize has emerged as cost effective and sustainable approach in addressing malnourishment of iron and zinc deficiency. Therefore, understanding the genetic variation and stability of kernel micronutrients and grain yield of the maize inbreds is a prerequisite in breeding micronutrient-rich high yielding hybrids to alleviate micronutrient malnutrition. We report here, the genetic variability and stability of the kernel micronutrients concentration and grain yield in a set of 50 maize inbred panel selected from the national and the international centres that were raised at six different maize growing regions of India. Phenotyping of kernels using inductively coupled plasma mass spectrometry (ICP-MS) revealed considerable variability for kernel minerals concentration (iron: 18.88 to 47.65 mg kg(-1); zinc: 5.41 to 30.85 mg kg(-1); manganese: 3.30 to 17.73 mg kg(-1); copper: 0.53 to 5.48 mg kg(-1)) and grain yield (826.6 to 5413 kg ha(-1)). Significant positive correlation was observed between kernel iron and zinc within (r = 0.37 to r = 0.52, p < 0.05) and across locations (r = 0.44, p < 0.01). Variance components of the additive main effects and multiplicative interactions (AMMI) model showed significant genotype and genotype × environment interaction for kernel minerals concentration and grain yield. Most of the variation was contributed by genotype main effect for kernel iron (39.6%), manganese (41.34%) and copper (41.12%), and environment main effects for both kernel zinc (40.5%) and grain yield (37.0%). Genotype main effect plus genotype-by-environment interaction (GGE) biplot identified several mega environments for kernel minerals and grain yield. Comparison of stability parameters revealed AMMI stability value (ASV) as the better representative of the AMMI stability parameters. Dynamic stability parameter GGE distance (GGED) showed strong and positive correlation with both mean kernel concentrations and grain yield. Inbreds (CM-501, SKV-775, HUZM-185) identified from the present investigation will be useful in developing micronutrient-rich as well as stable maize hybrids without compromising grain yield.

Fig 1. AMMI 2 (1A) and GGE (1B) biplots for kernel iron concentration in six environments.

Mega-environment 1 comprises of Almora, Bajaura, Delhi and Hyderabad; Barapani falls under mega-environment 2.

Fig 2. AMMI 2 (2A) and GGE (2B) biplots for kernel zinc concentration in six environments.

Mega-environment 1 comprises of Almora, Bajaura and Delhi; mega-environment 2 holds Barapani and Hyderabad.

Fig 3. AMMI 2 (3A) and GGE (3B) biplots for kernel manganese concentration in six environments.

For kernel manganese concentration all the environments grouped in a single mega-environment.

Fig 4. AMMI 2 (4A) and GGE (4B) biplots for kernel copper concentration in six environments.

Mega-environment 1 comprises of Almora, Bajaura, Barapani and Hyderabad; Delhi and Dharwad falls under mega-environment 2.

Fig 5. AMMI 2 (5A) and GGE (5B) biplots for grain yield in six environments.

Mega-environment 1 comprises hill locations (Almora, Bajaura, Barapani); mega-environment 2 comprises plain locations (Hyderabad, Delhi and Dharwad).