International Maize and Wheat Improvement Center, El Batán, Texcoco CP 56130, Mexico.
J Agric Food Chem. 2011 Jan 26;59(2):467-74. doi: 10.1021/jf103395z. Epub 2010 Dec 22.
The oxygen isotope composition (δ(18)O), accumulation of minerals (ash content), and nitrogen (N) content in plant tissues have been recently proposed as useful integrative physiological criteria associated with yield potential and drought resistance in maize. This study tested the ability of near-infrared reflectance spectroscopy (NIRS) to predict δ(18)O and ash and N contents in leaves and mature kernels of maize. The δ(18)O and ash and N contents were determined in leaf and kernel samples from a set of 15 inbreds and 18 hybrids grown in Mexico under full irrigation and two levels of drought stress. Calibration models between NIRS spectra and the measured variables were developed using modified partial least-squares regressions. Global models (which included inbred lines and hybrids) accurately predicted ash and N contents, whereas prediction of δ(18)O showed lower results. Moreover, in hybrids, NIRS clearly reflected genotypic differences in leaf and kernel ash and N contents within each water treatment. It was concluded that NIRS can be used as a rapid, cost-effective, and accurate method for predicting ash and N contents and as a method for screening δ(18)O in maize with promising applications in crop management and maize breeding programs for improved water and nitrogen use efficiency and grain quality.
氧同位素组成 (δ(18)O)、矿物质积累 (灰分含量) 和植物组织中的氮 (N) 含量最近被提议作为与玉米产量潜力和抗旱性相关的有用综合生理指标。本研究测试了近红外反射光谱 (NIRS) 预测玉米叶片和成熟籽粒中 δ(18)O、灰分和 N 含量的能力。在墨西哥,在充分灌溉和两种干旱胁迫水平下,对来自一组 15 个自交系和 18 个杂交种的叶片和籽粒样本进行了 δ(18)O 和灰分和 N 含量的测定。使用修正的偏最小二乘回归建立了 NIRS 光谱与测量变量之间的校准模型。全球模型(包括自交系和杂交种)准确预测了灰分和 N 含量,而 δ(18)O 的预测结果则较低。此外,在杂交种中,NIRS 清楚地反映了每个水分处理下叶片和籽粒灰分和 N 含量的基因型差异。研究结论认为,NIRS 可用于快速、经济高效、准确地预测灰分和 N 含量,以及作为筛选玉米 δ(18)O 的方法,在作物管理和玉米育种计划中具有广阔的应用前景,可提高水和氮的利用效率和谷物品质。