Gitelson Anatoly A, Gritz Yuri, Merzlyak Mark N
Center for Advanced Land Management Information Technologies, School of Natural Resource Sciences, University of Nebraska-Lincoln, 113 Nebraska Hall, Lincoln, NE 68588-0517, USA.
J Plant Physiol. 2003 Mar;160(3):271-82. doi: 10.1078/0176-1617-00887.
Leaf chlorophyll content provides valuable information about physiological status of plants. Reflectance measurement makes it possible to quickly and non-destructively assess, in situ, the chlorophyll content in leaves. Our objective was to investigate the spectral behavior of the relationship between reflectance and chlorophyll content and to develop a technique for non-destructive chlorophyll estimation in leaves with a wide range of pigment content and composition using reflectance in a few broad spectral bands. Spectral reflectance of maple, chestnut, wild vine and beech leaves in a wide range of pigment content and composition was investigated. It was shown that reciprocal reflectance (R lambda)-1 in the spectral range lambda from 520 to 550 nm and 695 to 705 nm related closely to the total chlorophyll content in leaves of all species. Subtraction of near infra-red reciprocal reflectance, (RNIR)-1, from (R lambda)-1 made index [(R lambda)(-1)-(RNIR)-1] linearly proportional to the total chlorophyll content in spectral ranges lambda from 525 to 555 nm and from 695 to 725 nm with coefficient of determination r2 > 0.94. To adjust for differences in leaf structure, the product of the latter index and NIR reflectance [(R lambda)(-1)-(RNIR)-1]*(RNIR) was used; this further increased the accuracy of the chlorophyll estimation in the range lambda from 520 to 585 nm and from 695 to 740 nm. Two independent data sets were used to validate the developed algorithms. The root mean square error of the chlorophyll prediction did not exceed 50 mumol/m2 in leaves with total chlorophyll ranged from 1 to 830 mumol/m2.
叶片叶绿素含量为植物生理状态提供了有价值的信息。反射率测量使得能够快速且无损地原位评估叶片中的叶绿素含量。我们的目标是研究反射率与叶绿素含量之间关系的光谱行为,并开发一种利用几个宽光谱带的反射率对具有广泛色素含量和组成的叶片进行无损叶绿素估算的技术。研究了枫树、栗树、野生葡萄和山毛榉树叶在广泛色素含量和组成范围内的光谱反射率。结果表明,在520至550纳米以及695至705纳米的光谱范围λ内,倒数反射率(Rλ)-1与所有物种叶片中的总叶绿素含量密切相关。从(Rλ)-1中减去近红外倒数反射率(RNIR)-1,使得指数[(Rλ)-1 - (RNIR)-1]在525至555纳米以及695至725纳米的光谱范围λ内与总叶绿素含量呈线性比例,决定系数r2 > 0.94。为了校正叶片结构差异,使用了后一指数与近红外反射率的乘积[(Rλ)-1 - (RNIR)-1]×(RNIR);这进一步提高了在520至585纳米以及695至740纳米范围λ内叶绿素估算的准确性。使用两个独立数据集来验证所开发的算法。在总叶绿素含量为1至830 μmol/m²的叶片中,叶绿素预测的均方根误差不超过50 μmol/m²。