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作 者:任红军 许桂玲[1] 冯跃华[1,2] 梁涛 王晓珂 宋正丽 郭彦君 卢林亚 龙天雨 PhonenasaySomsana LatifMuhammad Usama
机构地区:[1]贵州大学农学院,贵州 贵阳 [2]贵州大学山地植物资源保护与种质创新教育部重点实验室,贵州 贵阳
出 处:《有机化学研究》2023年第3期109-115,共7页Journal of Organic Chemistry Research
摘 要:为探明水稻叶色的最佳测试位置,最佳的颜色特征参数,并构建颜色特征参数与SPAD值的关系模型。利用叶绿素计(SPAD-502型)获取叶片的SPAD值及智能手机获取的颜色空间RGB值,分析叶片各测试位置的SPAD值之间的关系及颜色特征参数与SPAD值之间的关系。结果表明,水稻叶片中间1/2及上下3 cm处的SPAD值的平均值与整片叶的SPAD值平均值相关系数最高;水稻叶片两侧SPAD值的平均值、标准差、变异系数的大小分别为,光滑侧 > 粗糙侧、光滑侧 SPAD = −0.4541XG-B + 64.4618 (n = 48, df = 45, R2 = 0.7475, F = 133.2052, p < 0.01)。综上,基于智能手机的颜色识别器测量水稻叶色,能为代替价格昂贵、性价比低、操作繁琐等仪器的水稻氮营养监测提供新方法。To identify the optimal testing location and color feature parameters for rice leaf color, and to construct a relationship model between color feature parameters and SPAD values, a chlorophyll meter (SPAD-502 type) was used to obtain the SPAD value of leaves and the RGB value of color space obtained by a smartphone to analyze the relationship between SPAD values at various test positions of leaves and the relationship between color feature parameters and SPAD values. The results showed that the correlation coefficient between the average SPAD values at the middle 1/2 and upper and lower 3cm of rice leaves and the average SPAD values of the entire leaf was the highest. The average value, standard deviation, and coefficient of variation of SPAD values on both sides of rice leaves are as follows: smooth side > rough side, smooth side SPAD = −0.4541XG-B + 64.4618 (n = 48, df = 45, R2 = 0.7475, F = 133.2052, p < 0.01). In summary, color recognition devices based on smartphones can provide a new method for monitoring rice nitrogen nutrition, replacing expensive, cost-effective, and cumbersome instruments.
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