Relationships between Some Spectral Traits and Grain Yield in Bread Wheat under Rainfed Conditions

S. Taner, Şah İsmail Cerit, Enes Yakışır, M. Türköz
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Abstract

Developing varieties adapted to dry conditions is one of the biggest targets for breeders. It is important to use inexpensive spectral sensing methods saving time in variety development. The aim of this study was to select bread wheat genotypes having high grain yield by using spectral sensing methods. Twenty-five bread wheat (Triticum aestivum L.) genotypes were evaluated under rainfed condition at three locations in Central Anatolia Region. The experiment was arranged in randomized complete block design with three replications. Grain yield (GY), Canopy Temperature (CT), Soil Plant Analysis Development (SPAD) and Normalized Difference Vegetation Index (NDVI) values were recorded. GY, CT, SPAD and NDVI were found to be statistically significant in terms of both genotype and environment. The relationship between grain yield and NDVI (R2=0.321**) values was linear. The positive correlation of GY (0.5671**) and SPAD (0.1729*) with NDVI suggest that NDVI can be used as efficient and precise selection criteria for identifying high effiency wheat varieties under rainfed conditions.
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旱作条件下面包小麦某些光谱性状与产量的关系
培育适应干旱条件的品种是育种者的最大目标之一。在品种开发过程中,采用廉价的光谱传感方法,节省时间是非常重要的。本研究旨在利用光谱传感技术筛选高产面包小麦基因型。在中安纳托利亚地区3个地点的雨养条件下,对25种面包小麦(Triticum aestivum L.)基因型进行了评价。试验采用随机完全区组设计,每组3个重复。记录了籽粒产量(GY)、冠层温度(CT)、土壤植物分析发展(SPAD)和归一化植被指数(NDVI)值。GY、CT、SPAD和NDVI在基因型和环境上均有统计学意义。籽粒产量与NDVI呈线性关系(R2=0.321**)。ggy(0.5671**)和SPAD(0.1729* *)与NDVI呈正相关,表明NDVI可作为旱作条件下高效小麦品种的筛选标准。
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