Mallikarjuna Mallana Gowdra, Thirunavukkarasu Nepolean, Hossain Firoz, Bhat Jayant S, Jha Shailendra K, Rathore Abhishek, Agrawal Pawan Kumar, Pattanayak Arunava, Reddy Sokka S, Gularia Satish Kumar, Singh Anju Mahendru, Manjaiah Kanchikeri Math, Gupta Hari Shanker
Maize Research Lab, Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
ICAR-Indian Agricultural Research Institute, Regional Research Centre, Dharwad, India.
PLoS One. 2015 Sep 25;10(9):e0139067. doi: 10.1371/journal.pone.0139067. eCollection 2015.
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.
铁和锌的缺乏会导致微量营养素营养不良或隐性饥饿，这严重影响了全球约25%的人口。玉米的基因生物强化已成为解决缺铁和缺锌营养不良问题的经济有效且可持续的方法。因此，了解玉米自交系籽粒微量营养素的遗传变异和稳定性以及籽粒产量，是培育富含微量营养素的高产杂交种以缓解微量营养素营养不良的先决条件。我们在此报告了从国家和国际中心选出的一组50个玉米自交系在印度六个不同玉米种植区种植时，籽粒微量营养素浓度和籽粒产量的遗传变异性和稳定性。使用电感耦合等离子体质谱法（ICP-MS）对籽粒进行表型分析，结果显示籽粒矿物质浓度（铁：18.88至47.65毫克/千克；锌：5.41至30.85毫克/千克；锰：3.30至17.73毫克/千克；铜：0.53至5.48毫克/千克）和籽粒产量（826.6至5413千克/公顷）存在相当大的变异性。籽粒铁和锌在地点内（r = 0.37至r = 0.52，p < 0.05）和跨地点（r = 0.44，p < 0.01）之间均观察到显著正相关。加性主效应和乘法互作（AMMI）模型的方差分量显示，籽粒矿物质浓度和籽粒产量存在显著的基因型以及基因型×环境互作。大部分变异是由籽粒铁（39.6%）、锰（41.34%）和铜（41.12%）的基因型主效应，以及籽粒锌（40.5%）和籽粒产量（37.0%）的环境主效应造成的。基因型主效应加基因型×环境互作（GGE）双标图确定了籽粒矿物质和籽粒产量的几个大环境。稳定性参数比较显示，AMMI稳定性值（ASV）是AMMI稳定性参数的更好代表。动态稳定性参数GGE距离（GGED）与平均籽粒浓度和籽粒产量均呈现出强正相关。从本研究中鉴定出的自交系（CM - 501、SKV - 775、HUZM - 185）将有助于培育富含微量营养素且稳定的玉米杂交种，同时不影响籽粒产量。
