Quantification of potassium concentration with Vis–SWNIR spectroscopy in fresh lettuce

Xiong, Yujuan; Ohashi, Shintaroh; Nakano, K.; Jiang, Weizhong; Takizawa, Kenji; Iijima, Kazuhiro; Maniwara, Phonkrit

doi:10.1142/s1793545820500297

Cited by 6 publications

(2 citation statements)

References 43 publications

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“…The results show that the proposed methodologies can be used to predict CHL levels but not the other leaf metrics. In 2020, Xiong et al used Vis-SWNIR spectroscopy and chemometric techniques to investigate the potassium concentration in fresh lettuce [21]. The authors demonstrated how PLS and SVR can be used to assess potassium concentrations in these plants.…”

Section: Introductionmentioning

confidence: 99%

A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture

Botero-Valencia,

Reyes-Vera,

Ospina-Rojas

et al. 2024

Instruments

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In this study, a novel system was designed to enhance the efficiency of data acquisition in a portable and compact instrument dedicated to the spectral analysis of various surfaces, including plant leaves, and materials requiring characterization within the 410 to 915 nm range. The proposed system incorporates two nine-band detectors positioned on the top and bottom of the target surface, each equipped with a digitally controllable LED. The detectors are capable of measuring both reflection and transmission properties, depending on the LED configuration. Specifically, when the upper LED is activated, the lower detector operates without its LED, enabling the precise measurement of light transmitted through the sample. The process is reversed in subsequent iterations, facilitating an accurate assessment of reflection and transmission for each side of the target surface. For reliability, the error estimation utilizes a color checker, followed by a multi-layer perceptron (MLP) implementation integrated into the microcontroller unit (MCU) using TinyML technology for real-time refined data acquisition. The system is constructed with 3D-printed components and cost-effective electronics. It also supports USB or Bluetooth communication for data transmission. This innovative detector marks a significant advancement in spectral analysis, particularly for plant research, offering the potential for disease detection and nutritional deficiency assessment.

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Section: Introductionmentioning

confidence: 99%

A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture

Botero-Valencia,

Reyes-Vera,

Ospina-Rojas

et al. 2024

Instruments

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show abstract

“…Recently, several classification methods were employed to classify agricultural products such as linear regression by partial least squares-discriminant analysis (PLS-DA) which was used to classify mandarin fruit from different canopy positions (Magsawa et al, 2012). Visible-short-wave nearinfrared (Vis-SWNIR) spectroscopy with partial least-squares (PLS) regression can detect and predict the potassium concentrations in fresh lettuce (Xiong et al, 2020). The NIR spectroscopy technique can be a good predictor of both chemical and physical parameters.…”

Section: Introductionmentioning

confidence: 99%

Seedlessness detection in ‘White Malaga’ table grapes using near-infrared spectroscopy

Kanchanomai¹,

Nakano²,

Kittiwachana³

et al. 2022

IFRJ

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‘White Malaga’ table grapes are seeded and widely grown in Thailand. They are converted by induction into seedless grapes to increase their value. It is difficult to identify seedlessness in table grapes without destroying the grape berry. The present work thus described a quick and non-destructive method for detecting and predicting seedlessness in ‘White Malaga’ table grapes by using near-infrared (NIR) spectroscopy together with chemometric analysis. The NIR spectra of 280 grape samples were recorded after harvest. Firmness, total soluble solids (TSS), pH, titratable acidity (TA), tartaric acid, number of seeds, and relevant physical properties were analysed. The width and weight of plant growth regulator (PGR) treatments were significantly lower than those in the untreated grapes, while the length, firmness, TA, and tartaric acid were not significantly different. Partial least square (PLS) regression was used to investigate the prediction. Classification models, namely principal component analysis (PCA) and quadratic discriminant analysis (QDA), were used to identify seedlessness. It was found that, QDA, as a representative of linear classification, resulted in the best classification of seeded and seedless performance, where the percentages of predictive ability (%PA), the percentages of model stability (%MS), and the percentages of correctly classified (%CC) were 97.27, 98.57, and 96.23%, respectively, for the training set with no pre-processing. Therefore, the NIR spectroscopy technique can be a non-destructive technique for seedlessness detection in ‘White Malaga’ table grapes.

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High-throughput phenotyping of plant leaf morphological, physiological, and biochemical traits on multiple scales using optical sensing

et al. 2023

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Quantification of potassium concentration with Vis–SWNIR spectroscopy in fresh lettuce

Cited by 6 publications

References 43 publications

A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture

A Portable Tool for Spectral Analysis of Plant Leaves That Incorporates a Multichannel Detector to Enable Faster Data Capture

Seedlessness detection in ‘White Malaga’ table grapes using near-infrared spectroscopy

High-throughput phenotyping of plant leaf morphological, physiological, and biochemical traits on multiple scales using optical sensing

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