A non-destructive estimation of chlorophyll-a and -b over different crops using airborne imaging spectroscopy observations

Kushwaha, Amit; Das, Ayan; Dave, Rucha; Bhattacharya, Bimal K.

doi:10.1016/j.asr.2022.07.060

Cited by 5 publications

(3 citation statements)

References 26 publications

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“…These results (R 2 > 0.90) indicated that the model could be employed in most analysis applications, including quality control. The results of this study were better than the research of [23] with R²C 0.46 by utilizing aerial imaging spectroscopy with a chlorophyll with a peak wavelength of 672 nm on some crops, such as beans, sugarcane, jowar, Bengal gram, maize, wheat. As shown in Figure 2, the regression coefficient values are derived from the PLSR analysis modeled using the pre-processing Savitzky-Golay's 1st derivative technique.…”

Section: The Performance Model Of Chlorophyll a Accumulationmentioning

confidence: 53%

“…The performance model of chlorophyll b accumulation The results of PLSR calibration, validation, and prediction performance of Chlorophyll b Content of Red and Green Spinach Microgreens are shown in Table 3. The best R 2 C findings (with the closest value to 1) are 0.813, with RMSEC values of 0.979 yielded by Standard Normal Variance (SNV) as a preprocessing technique.The of this study are superior to studies by[23] on crops that utilize aerial imaging spectroscopy with an R 2 C value of 0.51 and a peak at 587 nm. R 2 is between 0.66 to 0.81, indicating that the generated model is acceptable for screening and other approximate calibrations[25]…”

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confidence: 79%

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Determination of green and red spinach microgreen chlorophyll content using visible spectroscopy and wavelength selection

Nugroho

Zahra

Masithoh

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Microgreens are quickly-grown greens that are suitable for urban areas. The accumulation of chlorophyll in plants is essential for both nutritional compounds and the microgreen’s attractive appearance. A plant factory is a controlled-environment cultivation method that employs LEDs to enhance photosynthesis, vegetative development, seed germination, and chlorophyll accumulation. This work used VIS-NIR for the quantitative determination of chlorophyll content in green and red spinach microgreens grown under four different LED light intensities with four different ratios, with 100% blue, red, and white LED, and 67%:20%:13% of red:blue: white LED, as artificial grow for 12 hours illumination. The performance of MSC, AN, SNV, smoothing, and the first and second Savitzky-Golay’s derivatives (SGD) were examined. PLSR explained accurately predicted R2C, R2P, RMSEC, and RMSEP up to 0.957, 0.892, 1.054, and 1.661 for chlorophyll a using SGD 1st; 0.813, 0.652, 0.979, and 1.338 for chlorophyll b using SNV; and 0.931, 0.876, 1.155, and 1.550 for total chlorophyll using SNV. The wavelength region of 400 to 700 nm was dominant based on the best regression coefficient (β) for predicting green and red spinach microgreens. Results demonstrated that VIS-NIR spectroscopy, combined with chemometric techniques, PLSR, can be used to evaluate the chlorophyll content of green and red spinach microgreens.

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Section: The Performance Model Of Chlorophyll a Accumulationmentioning

confidence: 53%

mentioning

confidence: 79%

Determination of green and red spinach microgreen chlorophyll content using visible spectroscopy and wavelength selection

Nugroho

Zahra

Masithoh

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…Additionally, the transfer of nitrogen between leaf layers during different growth stages and fertilization treatments further amplifies the spatiotemporal variability of LCC within the canopy. While current models can predict crop CCC to some extent ( Huang et al., 2022 ; Kushwaha et al., 2022 ), they often overlook the heterogeneity of LCC distribution in the vertical space, resulting in significant errors during practical application ( Winterhalter et al., 2012 ). Hence, the incorporation of vertical distribution characteristics of LCC into the maize chlorophyll content model is pivotal.…”

Section: Introductionmentioning

confidence: 99%

Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery

Chen,

Huang,

et al. 2023

Front. Plant Sci.

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Real-time monitoring of canopy chlorophyll content is significant in understanding crop growth status and guiding precision agricultural management. Remote sensing methods have demonstrated great potential in this regard. However, the spatiotemporal heterogeneity of chlorophyll content within crop canopies poses challenges to the accuracy and stability of remote sensing estimation models. Hence, this study aimed to develop a novel method for estimating canopy chlorophyll content (represented by SPAD values) in maize (Zea mays L.) canopies. Firstly, we investigated the spatiotemporal distribution patterns of maize canopy SPAD values under varying nitrogen application rates and different growth stages. The results revealed a non-uniform, “bell-shaped” curve distribution of maize canopy SPAD values in the vertical direction. Nitrogen application significantly influenced the distribution structure of SPAD values within the canopy. Secondly, we achieved satisfactory results by fitting the Lorentz peak distribution function to the SPAD values of different leaf positions in maize. The fitting performance, evaluated using R2 and RMSE, ranged from 0.69 to 0.98 and 0.45 to 3.59, respectively, for the year 2021, and from 0.69 to 0.77 and 2.38 to 6.51, respectively, for the year 2022.Finally, based on the correlation between canopy SPAD values and vegetation indices (VIs) at different growth stages, we identified the sensitive leaf positions for the selected CCCI (Canopy Chlorophyll Index) in each growth stage. The 6th (r = 0.662), 4th (r = 0.816), 12th (r = 0.722), and 12th (r = 0.874) leaf positions exhibited the highest correlations. Compared to the estimation model using canopy wide SPAD values, the model based on sensitive leaf positions showed improved accuracy, with increases of 34%, 3%, 20%, and 3% for each growth stage, respectively. In conclusion, the findings of this study contribute to the enhancement of chlorophyll content estimation models in crop canopies and provide valuable insights for the integration of crop growth models with remote sensing methods.

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Long Term Monitoring of Ecological Status of Major Deserts of the World

Kushwaha,

Bhatnagar,

Kumar

et al. 2024

J Indian Soc Remote Sens

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A non-destructive estimation of chlorophyll-a and -b over different crops using airborne imaging spectroscopy observations

Cited by 5 publications

References 26 publications

Determination of green and red spinach microgreen chlorophyll content using visible spectroscopy and wavelength selection

Determination of green and red spinach microgreen chlorophyll content using visible spectroscopy and wavelength selection

Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery

Long Term Monitoring of Ecological Status of Major Deserts of the World

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