Nondestructive Determination of Total Chlorophyll Content in Maize Using Three-Wavelength Diffuse Reflectance

Gu, Dazhen; Wang, W.-Z.; Hu, Jiandong; Zhang, X.-M.; Wang, J.-B.; Wang, B.-S.

doi:10.1007/s10812-016-0325-y

Cited by 24 publications

(17 citation statements)

References 31 publications

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“…Chlorophyll a, b and total for each sample of treatments were determined following Gu et al . (2016):where A663 and A645 are the absorbance evaluated from 663 and 645 nm, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Induction of resistance againstBrevicoryne brassicaebyPseudomonas putidaand salicylic acid in canola

Khoshfarman-Borji

Yali

Bozorg-Amirkalaee

2020

Bull. Entomol. Res.

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The cabbage aphid, Brevicoryne brassicae L. (Hem: Aphididae), is one of the most serious pests of canola worldwide. In this research, the effects of Pseudomonas putida, salicylic acid (SA), and integrated application of both inducers were studied on the resistance of canola to B. brassicae. In free-choice situation, the number of B. brassicae attracted on canola plants under treatments containing P. putida and SA was significantly lower compared to control plants. In the life table study, pre-adult survival, longevity, reproductive period, and fecundity of this aphid were lowest on plants treated with P. putida + SA. The net reproductive rate (R0), intrinsic rate of population increase (r), and finite rate of increase (λ) of B. brassicae decreased significantly in the following order: control (47.19 offspring, 0.293 and 1.340 day−1), P. putida (16.7 offspring, 0.238 and 1.269 day−1), SA (6.37 offspring, 0.163 and 1.178 day−1), and P. putida + SA (3.24 offspring, 0.112 and 1.119 day−1). Moreover, the beneficial effect of the integrated application of P. putida and SA on plant growth parameters was significantly evident in our study. The highest values of glucosinolates, total phenol, and flavonoids were recorded in P. putida + SA treatment. We concluded that canola plants treated with P. putida + SA are more resistant to the cabbage aphid. These findings demonstrated that SA integrated with P. putida on canola plants act effectively for reducing the population of B. brassicae and can be used in integrated management programs of this pest.

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“…Chlorophyll a, b and total for each sample of treatments were determined following Gu et al . (2016):where A663 and A645 are the absorbance evaluated from 663 and 645 nm, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Then, the absorbance was measured at the wavelengths of 663 and 645 nm using a spectrophotometer. Chlorophyll a, b and total for each sample of treatments were determined following Gu et al (2016):…”

Section: Measurement Of Plant Growth Parametersmentioning

confidence: 99%

Induction of resistance againstBrevicoryne brassicaebyPseudomonas putidaand salicylic acid in canola

Khoshfarman-Borji

Yali

Bozorg-Amirkalaee

2020

Bull. Entomol. Res.

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“…The obtained values were substituted in the following formulas, described in [ 30 ], for the estimation of photosynthetic pigments. Chlorophyll a (mg/g) = (12.7 * A663) − (2.59 * A645) Chlorophyll b (mg/g) = (22.9 * A645) − (4.7 * A663) Chlorophyll total (mg/g) = (8.2 * A663) + (20.2 * A645) where A663 and A645 are the absorbance measured from 663 nm and 645 nm, respectively.…”

Section: Methodsmentioning

confidence: 99%

Optical Method for Estimating the Chlorophyll Contents in Plant Leaves

Pérez-Patricio

Camas-Anzueto

Sanchez-Alegría

et al. 2018

Sensors

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This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance), a novel optical arrangement is proposed. The chlorophyll content is then estimated by using linear regression where the inputs are the reflectance and transmittance of the leaf. Performance of the proposed method for chlorophyll content estimation was compared with a spectrophotometer and a Soil Plant Analysis Development (SPAD) meter. Chlorophyll content estimation was realized for Lactuca sativa L., Azadirachta indica, Canavalia ensiforme, and Lycopersicon esculentum. Experimental results showed that—in terms of accuracy and processing speed—the proposed algorithm outperformed many of the previous vision-based approach methods that have used SPAD as a reference device. On the other hand, the accuracy reached is 91% for crops such as Azadirachta indica, where the chlorophyll value was obtained using the spectrophotometer. Additionally, it was possible to achieve an estimation of the chlorophyll content in the leaf every 200 ms with a low-cost camera and a simple optical arrangement. This non-destructive method increased accuracy in the chlorophyll content estimation by using an optical arrangement that yielded both the reflectance and transmittance information, while the required hardware is cheap.

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“…The nitrogen estimation algorithms presented in [20,41,42] also use color image analysis. The system in [43] uses three-wavelength diffuse reflectance for nitrogen estimation in plants. Similarly, systems proposed in [44] used the CIE-LAB color system to estimate nitrogen content in leaves.…”

Section: Review Of Existing Methodsmentioning

confidence: 99%

A Computer-Vision-Based Approach for Nitrogen Content Estimation in Plant Leaves

et al. 2021

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Nitrogen is an essential nutrient element required for optimum crop growth and yield. If a specific amount of nitrogen is not applied to crops, their yield is affected. Estimation of nitrogen level in crops is momentous to decide the nitrogen fertilization in crops. The amount of nitrogen in crops is measured through different techniques, including visual inspection of leaf color and texture and by laboratory analysis of plant leaves. Laboratory analysis-based techniques are more accurate than visual inspection, but they are costly, time-consuming, and require skilled laboratorian and precise equipment. Therefore, computer-based systems are required to estimate the amount of nitrogen in field crops. In this paper, a computer vision-based solution is introduced to solve this problem as well as to help farmers by providing an easier, cheaper, and faster approach for measuring nitrogen deficiency in crops. The system takes an image of the crop leaf as input and estimates the amount of nitrogen in it. The image is captured by placing the leaf on a specially designed slate that contains the reference green and yellow colors for that crop. The proposed algorithm automatically extracts the leaf from the image and computes its color similarity with the reference colors. In particular, we define a green color value (GCV) index from this analysis, which serves as a nitrogen indicator. We also present an evaluation of different color distance models to find a model able to accurately capture the color differences. The performance of the proposed system is evaluated on a Spinacia oleracea dataset. The results of the proposed system and laboratory analysis are highly correlated, which shows the effectiveness of the proposed system.

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Nondestructive Determination of Total Chlorophyll Content in Maize Using Three-Wavelength Diffuse Reflectance

Cited by 24 publications

References 31 publications

Induction of resistance againstBrevicoryne brassicaebyPseudomonas putidaand salicylic acid in canola

Induction of resistance againstBrevicoryne brassicaebyPseudomonas putidaand salicylic acid in canola

Optical Method for Estimating the Chlorophyll Contents in Plant Leaves

A Computer-Vision-Based Approach for Nitrogen Content Estimation in Plant Leaves

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