基于不同传感器的纽荷尔脐橙叶片叶绿素含量检测技术评价

doi:10.3864/j.issn.0578-1752.2018.06.005

Abstract

Abstract: 【Objective】 The objective of the study was to investigate the detection accuracy of chlorophyll content in the leaves of Newhall Navel Orange (Citrus sinensis Osbeck) based on different sensors with different scales and prediction models, so as to provide evidence for establishing an easy and high efficient nutrition diagnosis technology in citrus orchard.【Method】The spring shoot leaves of Newhall Navel Orange trees on trifoliate orange (Poncirus trifoliata (L.) Raf.) root stocks were selected for the study. Using the FieldSpec4, Multiplex®Research, digital image technology and SPAD-502 chlorophyll meter to obtain the leaf spectral, fluorescent values, digital indicators and chlorophyll content (SPAD values). In addition, the association of leaf spectral, fluorescent values and digital indicators with chlorophyll content were analyzed. The chlorophyll content quantitative inversion model was established by means of univariate and multiple regression (partial least square regression, PLS). Then the model accuracy and feasibility of the monitoring of leaf chlorophyll content based on different sensors were evaluated. 【Result】The results showed that the correlation between the content of relative chlorophyll content and parameter information from FieldSpec4, Multiplex®Research, digital image technology were extremely significant, and their relative coefficients were all more than 0.7. The goodness-of-fit of the predictive models were good. Among them, the PLS models based on FieldSpec4 established by First-order derivative (FD) method at the band of 532 nm, 586 nm and 705 nm showed the best goodness-of-fit with MRE (mean relative error) =1.80%，RPD (residual prediction deviation) =3.801. The quadratic regression model based on digital image technology which chose G-B values as characteristic indicators was established with MRE=1.98%, RPD=3.946. The PLS models was established by using the characteristic fluorescent parameters based on Multiplex®Research with MRE=2.37%, RPD=4.807.【Conclusion】The results showed that it had a certain feasibility by using information obtained from FieldSpec4, Multiplex® Research, digital image technology to predict chlorophyll content of citrus single leaves. The prediction accuracy of FieldSpec4 was best, the Multiplex ® Research was most convenient, and the digital image technology was more suitable for detection of large quantities of samples.

Key words: Newhall Navel Orange, chlorophyll content, spectrum, fluorescence, digital image

LI WenTao, YANG JiangBo, ZHANG Ji, WANG KeJian, DENG Lie, Lü Qiang, HE ShaoLan, XIE RangJin, ZHENG YongQiang, MA YanYan, YI ShiLai. The Evaluation of Chlorophyll Content Detection in the Leaves of Newhall Navel Orange Based on Different Sensors[J].Scientia Agricultura Sinica, 2018, 51(6): 1057-1066.

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The Evaluation of Chlorophyll Content Detection in the Leaves of Newhall Navel Orange Based on Different Sensors

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