Using a single-board computer as a low-cost instrument for SPAD value estimation through colour images and chlorophyll-related spectral indices

Křížová, Kateřina; Kadeřábek, Jan; Novák, V.; Linda, Rostislav; Kurešová, Gabriela; Šařec, P.

doi:10.1016/j.ecoinf.2021.101496

Cited by 10 publications

(2 citation statements)

References 31 publications

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“…Spectral indices obtained from digital images have been used with recognized success in the evaluation of biophysical parameters of different crops. In forage crops, the use of digital images has enabled the instantaneous, nondestructive quantification of leaf area and leaf weight (HUACCHA-CASTILLO et al, 2023), nitrogen fertilization estimation (MANCIN et al, 2022), aboveground biomass estimation (MAIMAITIJIANG et al, 2019), productivity estimation (SERRET et al, 2020), and chlorophyll monitoring (KŘÍŽOVÁ et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Relationship between spectral indices and quality parameters of tifton 85 forage

Souza,

Costa,

Carvalho

et al. 2024

Rev. Caatinga

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Computer vision systems can be an alternative to traditional methods of analyzing the quality of forage crops, allowing the instantaneous, non-destructive monitoring of the crop, with cost reduction. This study aimed to evaluate the quality parameters of Tifton 85 (Cynodon spp.) using digital images, relating spectral indices to the quality parameters of this forage. In the experimental area, four levels of nitrogen fertilization were applied and the analyses were made at different times after the standardization cut (14, 28, 42, and 56 days). The quality parameters evaluated were mineral matter, crude protein, and neutral detergent fiber. From images obtained in the visible (RGB) and near-infrared (RGNIR) spectral regions, spectral indices were generated. Principal component analysis was applied to summarize the information obtained by spectral indices into a single principal component (PCI). PCI associated with spectral indices was related to forage quality parameters for each cutting time using simple quadratic regression models. The relationships between mineral matter and spectral indices were variable over time. Crude protein and neutral detergent fiber showed the highest relationships with the spectral indices obtained by RGNIR images already at the initial times. Thus, although the RGB images have shown satisfactory results to obtain information about the quality of Tifton 85, the NIR band tends to increase the reliability of the relationships at early times.

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Section: Introductionmentioning

confidence: 99%

Relationship between spectral indices and quality parameters of tifton 85 forage

Souza,

Costa,

Carvalho

et al. 2024

Rev. Caatinga

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show abstract

“…Therefore, chlorophyll content is related to photosynthetic capacity [1]. Chlorophyll content has also been used to evaluate crop status, such as plant physiological activity, to ensure high yield [2,3] and other aspects of crop management. Portable chlorophyll content meters, such as the SPAD-02 Leaf Chlorophyll Meter (Konica Minolta Inc.), have been used to measure in-situ leaf chlorophyll content.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a One-Dimensional Convolution Neural Network for Chlorophyll Content Estimation Using a Compact Spectrometer

et al. 2022

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Leaf chlorophyll content is used as a major indicator of plant stress and growth, and hyperspectral remote sensing is frequently used to monitor the chlorophyll content. Hyperspectral reflectance has been used to evaluate vegetation properties such as pigment content, plant structure and physiological features using portable spectroradiometers. However, the prices of these devices have not yet decreased to consumer-affordable levels, which prevents widespread use. In this study, a system based on a cost-effective fingertip-sized spectrometer (Colorcompass-LF, a total price for the proposed solution was approximately 1600 USD) was evaluated for its ability to estimate the chlorophyll contents of radish and wasabi leaves and was compared with the Analytical Spectral Devices FieldSpec4. The chlorophyll contents per leaf area (cm2) of radish were generally higher than those of wasabi and ranged from 42.20 to 94.39 μg/cm2 and 11.39 to 40.40 μg/cm2 for radish and wasabi, respectively. The chlorophyll content was estimated using regression models based on a one-dimensional convolutional neural network (1D-CNN) that was generated after the original reflectance from the spectrometer measurements was de-noised. The results from an independent validation dataset confirmed the good performance of the Colorcompass-LF after spectral correction using a second-degree polynomial, and very similar estimation accuracies were obtained for the measurements from the FieldSpec4. The coefficients of determination of the regression models based on 1D-CNN were almost same (with R2 = 0.94) and the ratios of performance to deviation based on reflectance after spectral correction using a second-degree polynomial for the Colorcompass-LF and the FieldSpec4 were 4.31 and 4.33, respectively.

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Wetland Species Mapping Using Advanced Technological Measurement

Mohanty,

Srivastava,

Pandey

et al. 2024

Aquatic Conservation

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Wetlands are pivotal in supporting the natural ecosystem and maintaining biodiversity while being susceptible to anthropogenic activities and climate change. However, monitoring wetlands over a large geographical and temporal extent is challenging. Vegetation health can be considered a good indicator of wetland conditions, and measuring chlorophyll content will provide insight into vegetation health. Linking wetland species mapping from chlorophyll spectral indices to local and regional conservation strategies could improve biodiversity conservation. Here, we apply this to Keetham Lake, India, using machine learning methods (relevance vector model) and hyperspectral measurements. From 10 chlorophyll‐sensitive spectral indices, we identified four as best performing, particularly for: TVI + CCCI + NDRE for calibration and NDRE + TVI for validation data. The least performing combinations were MCARI for calibration and TVI + CCCI + NDRE + MCARI for validation. Overall, we identified that NDRE + TVI was the best‐performing pair of spectral indices for chlorophyll assessment and implementation in wetland species. This approach allows for precise mapping of wetland species, providing data on their extent and the area they cover. By creating a digital database, this method enables long‐term monitoring of changes in wetland species' numbers and distribution, helping to assess trends of increase or decline in freshwater ecosystems. Such strategies are vital for supporting both local and global conservation efforts, offering insights for forward‐looking, data‐driven preservation initiatives.

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Using a single-board computer as a low-cost instrument for SPAD value estimation through colour images and chlorophyll-related spectral indices

Cited by 10 publications

References 31 publications

Relationship between spectral indices and quality parameters of tifton 85 forage

Relationship between spectral indices and quality parameters of tifton 85 forage

Evaluation of a One-Dimensional Convolution Neural Network for Chlorophyll Content Estimation Using a Compact Spectrometer

Wetland Species Mapping Using Advanced Technological Measurement

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