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 to17.73 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.

Limits to the Biofortification of Leafy Brassicas with Zinc

“…Recent efforts to biofortify edible crops with Zn have focused primarily on staple crops, such as cereals, pulses, cassava and potatoes, and maximum Zn concentrations of 0.02-0.10 mg g −1 DW, depending upon the crop, have been achieved without loss of yield [1,6,9,[12][13][14][15][16][17][18][19][20][21]. The critical shoot Zn concentrations in cabbage and broccoli reported here generally exceed these values (Table 1).…”

“…Inorganic fertilisers are often preferred because of their consistent composition; foliar applications are most effective where the phytoavailability of Zn decreases rapidly when applied to the soil [1,5]. Recent biofortification efforts have focused largely on developing germplasm and agronomic strategies to increase Zn concentrations in staple crops including cereals, pulses, cassava and potatoes, and Zn concentrations approaching 0.02-0.10 mg g −1 dry weight (DW), depending upon the crop, have been achieved [1,6,9,[12][13][14][15][16][17][18][19][20][21]. However, greater Zn concentrations can be achieved in leafy vegetables than in fruits, seeds or tubers because Zn transport in the phloem limits Zn accumulation in the latter tissues [13].…”

Identifying Promising Pearl Millet Hybrids Using AMMI and Clustering Models

“…Therefore, hybrids TNBH 05 10 and TNBH 05 45 recorded with lower ASV scores, were considered to be stable entries (Table 3). The ASV parameter has been successfully used in several studies to find stable performers (Mallikarjuna et al, 2015).…”

Diversity of Maize Kernels from a Breeding Program for Protein Quality III: Ionome Profiling

“…Natural variation of Fe (8.0 to 62 mg kg −1 ) and Zn (12.0 to 58.0 mg kg −1 ) has been extensively reported as a prerequisite for genetic biofortification [36,37]. However, a genetic approach may not always be adequate due to several interacting factors, including lack of readily available germplasm, unfavorable genetic, physiological, and chemical interactions within the ionome [38], and negative relationships with grain yield [17,20]. These perceived shortcomings of genetic biofortification recently led to promoting molecular breeding [38,39] as a means of improving [nutrient] and bioavailability of micronutrients in maize and other grain crops.…”