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【目的】叶片形状系数(α)为测量作物的叶面积和叶面积指数提供了简单快捷的方法。然而,以往研究表明对作物叶片形状系数的选取存在很大的随意性,缺乏统一标准,且通常将其视为常数,不考虑它的时间和空间变异性。为解决这一问题,文章对陕西关中地区夏玉米不同生长阶段和不同叶位叶片形状系数的时间和空间变异性进行了深入研究。【方法】选取2015年6—10月生长季6个夏玉米品种,将玉米生育期划分为三叶、拔节、抽雄、开花、吐丝、成熟等6个不同生长阶段,每6天采样一次,测量叶片面积(LA)、叶片长度(L)和宽度(W),计算各个阶段的α值,同时对比α值在单个玉米植株不同叶位之间的差异。然后分别建立线性、二次、对数等3类共5个叶面积估算模型,以RMSE、RRMSE和ARE 3个统计量作为评价指标,对各叶片面积估算模型的精度进行评价。【结果】对全生育期6个夏玉米品种的760个叶片的面积和长宽乘积进行线性回归分析,夏玉米叶片形状系数均值约为0.78;在被验证的5种叶面积估算模型中,叶面积模型LA=α×L×W,其中α=0.78时精度最高,其相对均方根误差(RRMSE)约为9.50%,绝对相对误差(ARE)约为6.96%。α值范围为0.72—0.87,并随玉米生育期的变化而变化,自三叶期到开花期逐渐增大到全生育期最大值0.87,开花后缓慢下降至0.78,其中开花期叶片的α值与开花前各阶段的α值存在显著差异,而与开花后各阶段的α值不存在显著差异。不同熟性的夏玉米品种之间叶片α值也只在开花、吐丝期表现显著差异。不同叶型叶片α值表现出不同的变化规律,三叶期到拔节前,短宽型叶片的α值大于细长型叶片,此后一直到成熟期,细长型叶片的α值则大于短宽型叶片。在单个植株不同叶位叶片之间,α值变异性明显,开花期、吐丝期、成熟期均呈现出两头大中间小的规律,其中植株中部棒三叶位置α均值最为稳定,为0.78,对应的标准差在0.05以内,而植株上部和下部α均值约为0.84,对应的标准差在0.03—0.10。其中拔节、抽雄期不同叶位叶片的α值不存在显著差异,而在开花、吐丝、成熟期则表现出显著差异。【结论】叶面积模型LA=0.78×L×W更适于估算田间夏玉米叶片面积,较一般采用叶片性状系数0.75时提高模拟精度(ARE)3.86%。应在不同的生长阶段和不同叶位分别采用不同的叶片形状系数,这样才能进一步提高玉米叶面积估算的精度。
【Objective】 Leaf shape index (α) provides a simple and quick method for measuring leaf area and leaf area index of crops. However, previous studies have shown that there is a great deal of randomness in choosing the shape coefficient of crop leaves, lacking a uniform standard, and it is usually regarded as a constant irrespective of its temporal and spatial variability. In order to solve this problem, the article deeply studied the temporal and spatial variability of leaf shape coefficient of summer maize at different growth stages and different leaf positions in Guanzhong region of Shaanxi Province. 【Method】 Six summer maize varieties from June to October in 2015 were selected. The growth stages of maize were divided into 6 different growth stages: clover, jointing, tasselling, flowering, silking and maturity. Samples were taken every 6 days, Leaf area (LA), leaf length (L) and width (W) were measured to calculate the alpha values for each stage, while comparing the differences in alpha values between different leaf positions in a single corn plant. Then, five leaf area estimation models including linear, quadratic and logarithm were established respectively. The RMSE, RRMSE and ARE three statistics were used as evaluation indexes to evaluate the precision of each leaf area estimation model. 【Result】 The linear regression analysis of 760 leaves of 6 summer maize cultivars during the whole growth period was conducted. The average leaf shape coefficient of summer maize was 0.78. Among the five leaf area estimation models validated, The area model LA = α × L × W, with the highest accuracy when α = 0.78, the relative root mean square error (RRMSE) was about 9.50% and the absolute relative error (ARE) was about 6.96%. The value of α ranged from 0.72 to 0.87 and varied with the growth of maize. It gradually increased from the three-leaf stage to the flowering stage to the maximum during the whole growth period of 0.87, and then decreased slowly to 0.78 after flowering. The α value of the flowering stage There was a significant difference between the value of a and the value of α before flowering, but there was no significant difference with the value of α after flowering. Different maturity varieties of summer maize leaves α value only in the flowering, silking significant differences. The α values of different leaves showed different changes. Before the jointing stage, the α value of the short and wide leaves was larger than that of the elongated leaves. From then till the mature stage, the α value of the elongated leaves was greater than the short Wide blade. The variability of α value was obvious among different leaf positions of single plant, and the law of middle and small size at both flowering, silking and maturing stages was the most. Among them, The corresponding standard deviation is within 0.05, while the upper and lower plant a mean values are about 0.84, corresponding to a standard deviation of 0.03-0.10. Among them, there was no significant difference in the value of α among different leaf positions at jointing and tasseling stages, but significant difference in flowering, silking and maturity stages. 【Conclusion】 Leaf area model LA = 0.78 × L × W is more suitable for estimating the leaf area of summer maize, which is 3.86% higher than the average of 0.75 when the leaf trait coefficient is 0.75. Different leaf shape coefficients should be used at different growth stages and at different leaf positions in order to further improve the accuracy of leaf area estimation.