Towards development of on-line soil moisture content sensor using a fibre-type NIR spectrophotometer

Mouazen, Abdul Mounem; Baerdemaeker, Josse De; Ramón, Herman

doi:10.1016/j.still.2004.03.022

Cited by 223 publications

(152 citation statements)

References 19 publications

(17 reference statements)

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“…This was to avoid beam reflectance from the bottom of the dish due to down-welling solar and sky radiation penetrating into the soil at approximately 1/2 wavelength [34], which could have an unwanted effect of modifying the soil spectra. Samples were levelled off using a stainless steel blade to guarantee a flat surface flush with the top of the petri dish, as a smooth soil surface ensures maximum light reflection and a high signal-to-noise ratio [35]. All of the spectral readings were measured in the center of the samples (three replications each) in a dark room to avoid interference from stray light.…”

Section: Culs Protocolmentioning

confidence: 99%

“…It is clear that VIS-NIR-SWIR spectra contain useful information that can be used to derive estimates of soil properties. For example, absorption features in the VIS-NIR wavelength (400-1000 nm) are characteristics of the presence of soil carbon and iron oxide [34,35,[48][49][50], and those in the SWIR (1000-2500 nm) are from water, clay minerals and organic matter [16,51]. The important spectra absorption features through the use of some data mining algorithms have been studied by Viscarra Rossel and Behrens [15] and Gholizadeh et al [17].…”

Section: Soil Spectral Reflectance Patternmentioning

confidence: 99%

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Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

et al. 2017

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Abstract:Soil spectroscopy has shown to be a fast, cost-effective, environmentally friendly, non-destructive, reproducible and repeatable analytical technique. Soil components, as well as types of instruments, protocols, sampling methods, sample preparation, spectral acquisition techniques and analytical algorithms have a combined influence on the final performance. Therefore, it is important to characterize these differences and to introduce an effective approach in order to minimize the technical factors that alter reflectance spectra and consequent prediction. To quantify this alteration, a joint project between Czech University of Life Sciences Prague (CULS) and Tel-Aviv University (TAU) was conducted to estimate Cox, pH-H 2 O, pH-KCl and selected forms of Fe and Mn. Two different soil spectral measurement protocols and two data mining techniques were used to examine seventy-eight soil samples from five agricultural areas in different parts of the Czech Republic. Spectral measurements at both laboratories were made using different ASD spectroradiometers. The CULS protocol was based on employing a contact probe (CP) spectral measurement scheme, while the TAU protocol was carried out using a CP measurement method, accompanied with the internal soil standard (ISS) procedure. Two spectral datasets, acquired from different protocols, were both analyzed using partial least square regression (PLSR) technique as well as the PARACUDA II ® , a new data mining engine for optimizing PLSR models. The results showed that spectra based on the CULS setup (non-ISS) demonstrated significantly higher albedo intensity and reflectance values relative to the TAU setup with ISS. However, the majority of statistics using the TAU protocol was not noticeably better than the CULS spectra. The paper also highlighted that under both measurement protocols, the PARACUDA II ® engine proved to be a powerful tool for providing better results than PLSR. Such initiative is not only a way to unlock current limitations of soil spectroscopy, but also offers considerable efficiency and cost-and time-saving possibilities, which lead to further improvements in prediction performance of spectral models.

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Section: Culs Protocolmentioning

confidence: 99%

Section: Soil Spectral Reflectance Patternmentioning

confidence: 99%

Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

et al. 2017

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“…The ratio of the SD to the RMSEP, called the ratio of prediction to deviation (RPD), is the factor by which the prediction accuracy has been increased compared with using the mean composition for all samples. This ratio is desired to be larger than 2 for a good calibration [40]. A RPD ratio less than 1.5 indicates incorrect predictions and the model cannot be used for further prediction.…”

Section: Partial Least Squares Analysismentioning

confidence: 99%

Utilisation of front-face fluorescence spectroscopy for the determination of some selected chemical parameters in soft cheeses

Karoui

Mouazen

Dufour³

et al. 2006

Lait

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-This study evaluated the usefulness of front-face fluorescence spectroscopy for predicting some selected chemical parameters in soft cheeses in external (E) and central (C) zones. Fat, dry matter (DM), pH, total nitrogen (TN) and water-soluble nitrogen (WSN) contents were determined by reference methods. Tryptophan (excitation: 290 nm; emission: 305-450 nm), riboflavin (excitation: 380 nm; emission: 400-640 nm) and vitamin A fluorescence spectra (emission: 410 nm; excitation: 270-350 nm) were recorded on the investigated cheeses. Three separate prediction models were developed from the tryptophan, riboflavin and vitamin A spectra using partial least squares (PLS) regression and the leave-one-out cross-validation technique. The results showed that fat, DM, fat in dry matter and WSN were the best predicted with the vitamin A fluorescence spectra models providing the highest values of the determination coefficient (R 2 ) of 0.88, 0.86, 0.86 and 0.84, respectively. The prediction of the pH was also successful using riboflavin fluorescence spectra (R 2 = 0.85). The WSN/TN ratio can also be predicted from the three intrinsic probes, but with much lower precision. Résumé -Utilisation de la spectroscopie de fluorescence frontale pour la détermination de quelques paramètres chimiques à la surface et au centre des fromages à pâte molle. L'objectif de cette étude était d'évaluer le potentiel de la spectroscopie de fluorescence frontale à prédire quelques paramètres chimiques, à la surface et au centre, des fromages à pâte molle. Les teneurs en matière grasse, extrait sec, pH, azote total et en azote soluble ont été déterminées par des méthodes de référence. Des spectres de fluorescence des tryptophanes (excitation : 290 nm ; émission: 305-450 nm), de la riboflavine (excitation : 380 nm ; émission : 400-640 nm) et de la vitamine A (émission : 410 nm ; excitation : 270-350 nm) ont été également enregistrés sur ces fromages. Trois modèles séparés de prédictions ont été développés à partir des spectres des tryptophanes, de la riboflavine et de la vitamine A en utilisant la technique des moindres carrés partiels avec validation croisée. Les résultats obtenus ont montré que les teneurs en matière grasse, extrait sec, gras sur sec et en azote soluble étaient mieux prédites avec les modèles des spectres de fluorescence de la vitamine A qui donnaient les valeurs les plus élevées du coefficient de détermination (R 2 ) : 0,88, 0,86, 0,86 et 0,84, respectivement. La prédiction du pH est réalisée avec succès en utilisant les spectres de fluorescence de la riboflavine (R 2 = 0,85). Le rapport azote soluble/azote total peut, également, être prédit à partir des trois sondes intrinsèques, mais avec une précision beaucoup plus faible. fromage à pâte molle / tryptophane / riboflavine / vitamine A / moindres carrés partiels

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“…The prediction accuracy achieved so far with the on-line vis-NIRS sensors available today (Shibusawa et al, 2001;Christy, 2008) might be sufficient for many applications in precision agriculture, since spatial and temporal variation of soil properties is large relative to the precision of measurement (Shepherd and Walsh, 2002). However, similar to laboratory and in situ measurements, Kuang et al (2012) concluded that the best accuracy is achieved for soil properties with direct spectral response, which is probably the reason why researchers using on-line vis-NIRS sensors have focused mainly on soil properties with direct spectral responses (Shonk et al, 1991;Mouazen et al, 2005;Bricklemyer and Brown, 2010;Munoz andKravchenko, 2011, Knadel et al, 2011). Mouazen et al (2007) showed potential success for the on-line vis-NIRS measurement of extractable and available P and pH, without proving the accuracy to be of quantitative meaning.…”

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confidence: 99%

On-line measurement of soil properties without direct spectral response in near infrared spectral range

Marín-González

Kuang

Quraishi

et al. 2013

Soil and Tillage Research

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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited.

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Towards development of on-line soil moisture content sensor using a fibre-type NIR spectrophotometer

Cited by 223 publications

References 19 publications

Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

Utilisation of front-face fluorescence spectroscopy for the determination of some selected chemical parameters in soft cheeses

On-line measurement of soil properties without direct spectral response in near infrared spectral range

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