Hu Zhen Zhu, Pan Cun de, Xiao Bing, Pan Xin
Collage of Forestry and Horticulture, Xinjiang Agricultural University/Key Laboratory of Forestry Ecology and Industry Technology in Arid Region, Education Department of Xinjiang, Urumqi 830052, China.
Ying Yong Sheng Tai Xue Bao. 2016 May;27(5):1393-1400. doi: 10.13287/j.1001-9332.201605.014.
According to the field trials with quantitative fertilization, the spectral characteristic parameters which were highly significantly correlated with foliar potassium (K) content were screened out using Pearson correlation analysis, and the foliar K content estimation models of Juglans regia 'Wen185' in different phenological periods of fruit development were built up with these parameters as independent variables using regression analysis. The results showed that there were one or more spectral characteristic parameters which were highly significantly correlated with the foliar K contents of 'Wen185' walnut in the different phonological periods of fruit development (P＜0.01). Through cubic function analysis with normalized difference green index in the fruit setting period, ratio red and yellow edge area index in the fruit rapid-growth period, ratio green index in the fruit fat-change period and blue edge area in the fruit near-mature period as independent variable, the regression estimation models of the foliar K content in the different phenological periods of fruit development were established respectively, and their fitting degrees (R) were all above 0.95. In addition, the estimated values of the models for the foliar K content of 'Wen185' walnut were consis-tent with the measured values of the independent samples, and the root mean square errors and the relative errors of the independent sample tests were less than 0.8161 g·kg and 2.7% in the diffe-rent phenological periods of fruit development. The models showed their high estimation accuracy. The spectrum technology possessed great application potential in monitoring K status of J. regia.
通过定量施肥田间试验，利用Pearson相关性分析筛选出与叶片钾（K）含量高度显著相关的光谱特征参数，并以这些参数为自变量，采用回归分析建立了核桃‘温185’果实发育不同物候期的叶片钾含量估算模型。结果表明，在果实发育的不同物候期，存在一个或多个与‘温185’核桃叶片钾含量高度显著相关的光谱特征参数（P＜0.01）。分别以坐果期归一化差值绿度指数、果实快速生长期红边和黄边面积比值指数、果实脂肪变化期绿度比值指数以及果实近成熟期蓝边面积为自变量进行三次函数分析，建立了果实发育不同物候期叶片钾含量的回归估算模型，其拟合度（R）均在0.95以上。此外，‘温185’核桃叶片钾含量模型的估算值与独立样本的测量值一致，在果实发育的不同物候期，独立样本检验的均方根误差和相对误差分别小于0.8161 g·kg和2.7%。模型显示出较高的估算精度。光谱技术在监测核桃钾素状况方面具有很大的应用潜力。
