Predicting Key Agronomic Soil Properties with UV-Vis Fluorescence Measurements Combined with Vis-NIR-SWIR Reflectance Spectroscopy: A Farm-Scale Study in a Mediterranean Viticultural Agroecosystem

For adequate crop and soil management, rapid and accurate techniques for monitoring soil properties are particularly important when a farmer starts up his activities and needs a diagnosis of his cultivated fields. This study aimed to evaluate the potential of fluorescence measured directly on 146 whole soil solid samples, for predicting key soil properties at the scale of a 6 ha Mediterranean wine estate with contrasting soils. UV-Vis fluorescence measurements were carried out in conjunction with reflectance measurements in the Vis-NIR-SWIR range. Combining PLSR predictions from Vis-NIR-SWIR reflectance spectra and from a set of fluorescence signals enabled us to improve the power of prediction of a number of key agronomic soil properties including SOC, Ntot, CaCO3, iron, fine particle-sizes (clay, fine silt, fine sand), CEC, pH and exchangeable Ca2+ with cross-validation RPD ≥ 2 and R² ≥ 0.75, while exchangeable K+, Na+, Mg2+, coarse silt and coarse sand contents were fairly predicted (1.42 ≤ RPD < 2 and 0.54 ≤ R² < 0.75). Predictions of SOC, Ntot, CaCO3, iron contents, and pH were still good (RPD ≥ 1.8, R² ≥ 0.68) when using a single fluorescence signal or index such as SFR_R or FERARI, highlighting the unexpected importance of red excitations and indices derived from plant studies. The predictive ability of single fluorescence indices or original signals was very significant for topsoil: this is very important for a farmer who wishes to update information on soil nutrient for the purpose of fertility diagnosis and particularly nitrogen fertilization. These results open encouraging perspectives for using miniaturized fluorescence devices enabling red excitation coupled with red or far-red fluorescence emissions directly in the field.

[1]  Giovanni Agati,et al.  Light-induced accumulation of ortho-dihydroxylated flavonoids as non-destructively monitored by chlorophyll fluorescence excitation techniques , 2011 .

[2]  Á. Zsolnay,et al.  Differentiating with fluorescence spectroscopy the sources of dissolved organic matter in soils subjected to drying , 1999, Chemosphere.

[3]  Prasad S. Thenkabail,et al.  Spectral Sensing from Ground to Space in Soil Science: State of the Art, Applications, Potential, and Perspectives , 2018, Remote Sensing Handbook - Three Volume Set.

[4]  Z. Cerovic,et al.  Optically assessed contents of leaf polyphenolics and chlorophyll as indicators of nitrogen deficiency in wheat (Triticum aestivum L.) , 2005 .

[5]  Gwendal Latouche,et al.  Non-Destructive Optical Monitoring of Grape Maturation by Proximal Sensing , 2010, Sensors.

[6]  Emmanuelle Vaudour,et al.  Retrospective 70 y-spatial analysis of repeated vine mortality patterns using ancient aerial time series, Pléiades images and multi-source spatial and field data , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[7]  Dandan Wang,et al.  Synthesized use of VisNIR DRS and PXRF for soil characterization: Total carbon and total nitrogen☆ , 2015 .

[8]  Moon S. Kim,et al.  Potential Application of Fluorescence Imaging for Assessing Fecal Contamination of Soil and Compost Maturity , 2016 .

[9]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[10]  Giovanni Agati,et al.  Nondestructive evaluation of anthocyanins in olive (Olea europaea) fruits by in situ chlorophyll fluorescence spectroscopy. , 2005, Journal of agricultural and food chemistry.

[11]  Tsutomu Ohno,et al.  Fluorescence inner-filtering correction for determining the humification index of dissolved organic matter. , 2002, Environmental science & technology.

[12]  R. V. Rossel,et al.  Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties , 2006 .

[13]  L. Janik,et al.  Soil properties prediction of western Mediterranean islands with similar climatic environments by means of mid‐infrared diffuse reflectance spectroscopy , 2010 .

[14]  J. Hill,et al.  Using Imaging Spectroscopy to study soil properties , 2009 .

[15]  A. Mouazen,et al.  Calibration of visible and near infrared spectroscopy for soil analysis at the field scale on three European farms , 2011 .

[16]  Ingrid Kögel-Knabner,et al.  The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter , 2002 .

[17]  James E. McMurtrey,et al.  Potential for Discriminating Crop Residues from Soil by Reflectance and Fluorescence , 1995 .

[18]  James E. McMurtrey,et al.  Fluorescence and reflectance of crop residue and soil , 1993 .

[19]  Hartmut K. Lichtenthaler,et al.  The Chlorophyll Fluorescence Ratio F735/F700 as an Accurate Measure of the Chlorophyll Content in Plants , 1999 .

[20]  Dr.h.c. Dieter Bäuerle Thermal, Photophysical, and Photochemical Processes , 2011 .

[21]  Pietro Amenta,et al.  Prediction of Soil Properties with PLSR and vis-NIR Spectroscopy: Application to Mediterranean Soils from Southern Italy , 2012 .

[22]  G. Schmuck,et al.  Application of chlorophyll fluorescence in ecophysiology , 1986, Radiation and environmental biophysics.

[23]  Kenneth A. Sudduth,et al.  Soil Phosphorus and Potassium Estimation by Reflectance Spectroscopy , 2016 .

[24]  Ron Wehrens,et al.  The pls Package: Principal Component and Partial Least Squares Regression in R , 2007 .

[25]  Gwendal Latouche,et al.  Optical detection of downy mildew in grapevine leaves: daily kinetics of autofluorescence upon infection , 2013, Journal of experimental botany.

[26]  Gustavo González-Gaitano,et al.  The usefulness of UV–visible and fluorescence spectroscopies to study the chemical nature of humic substances from soils and composts , 2006 .

[27]  C. Granger,et al.  Improved methods of combining forecasts , 1984 .

[28]  Rattan Lal,et al.  Assessing humification and organic C compounds by laser-induced fluorescence and FTIR spectroscopies under conventional and no-till management in Brazilian Oxisols , 2013 .

[29]  Ismael Moya,et al.  The use of chlorophyll fluorescence excitation spectra for the non‐destructive in situ assessment of UV‐absorbing compounds in leaves , 2002 .

[30]  Budiman Minasny,et al.  An assessment of model averaging to improve predictive power of portable vis-NIR and XRF for the determination of agronomic soil properties , 2016 .

[31]  Eric P. Verrecchia,et al.  Microbial origin for pedogenic micrite associated with a carbonate paleosol (Champagne, France) , 1999 .

[32]  O. P. MEdinA,et al.  IRON OXIDE REMOVAL FROM SOILS AND CLAYS BY A DITHIONITE-CITRATE SYSTEM BUFFERED WITH SODIUM BICARBONATE by , 2006 .

[33]  Johan Hofkens,et al.  Handbook of fluorescence spectroscopy and imaging : from single molecules to ensembles , 2011 .

[34]  Bin Li,et al.  Simultaneous assessment of key properties of arid soil by combined PXRF and Vis–NIR data , 2016 .

[35]  Geoffrey Davies,et al.  Spectroscopic characterization of humic acid fractions isolated from soil using different extraction procedures , 2006 .

[36]  Manuel Robbins,et al.  Fluorescence: Gems and Minerals Under Ultraviolet Light , 1994 .

[37]  Zoran G. Cerovic,et al.  Investigating UV screening in leaves by two different types of portable UV fluorimeters reveals in vivo screening by anthocyanins and carotenoids , 2007, Photosynthesis Research.

[38]  T. Miano,et al.  CHARACTERIZATION, DIFFERENTIATION, AND CLASSIFICATION OF HUMIC SUBSTANCES BY FLUORESCENCE SPECTROSCOPY , 1991 .

[39]  Alex B. McBratney,et al.  Multivariate calibration of hyperspectral γ‐ray energy spectra for proximal soil sensing , 2007 .

[40]  David J. Chittleborough,et al.  Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties , 2011 .

[41]  Ulrich Schreiber,et al.  Measurement of leaf epidermal transmittance of UV radiation by chlorophyll fluorescence , 1997 .

[42]  Gennaro Brunetti,et al.  Chemical and spectroscopic characterization of humic acids isolated from different Slovak soil types , 1997 .

[43]  Philippe Lagacherie,et al.  Potential of SENTINEL-2 images for predicting common topsoil properties over Temperate and Mediterranean agroecosystems , 2017 .

[44]  N. Blough,et al.  On the origin of the optical properties of humic substances. , 2004, Environmental science & technology.

[45]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[46]  T. Miano,et al.  Synchronous excitation fluorescence spectroscopy applied to soil humic substances chemistry , 1992 .

[47]  C. Hurburgh,et al.  Near-Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties , 2001 .

[48]  M. Paoletti,et al.  Soil algae composition under different agro-ecosystems in North-Eastern Italy , 2006 .

[49]  Georg Noga,et al.  Fluorescence-based sensing of drought-induced stress in the vegetative phase of four contrasting wheat genotypes , 2013 .

[50]  Gennaro Brunetti,et al.  Characterization of Clay- and Silt-Sized Fractions and Corresponding Humic Acids Along a Terra Rossa Soil Profile , 2016 .

[51]  A. McBratney,et al.  Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils – Critical review and research perspectives , 2011 .

[52]  M. Canle,et al.  Environmental Applications of Excitation-Emission Spectrofluorimetry: An In-Depth Review I , 2013 .

[53]  C. Guerrero,et al.  Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils. , 2008, Soil biology & biochemistry.

[54]  Giovanni Agati,et al.  New portable optical sensors for the assessment of winegrape phenolic maturity based on berry fluorescence , 2008 .

[55]  Alex B. McBratney,et al.  Simultaneous estimation of several soil properties by ultra-violet, visible, and near-infrared reflectance spectroscopy , 2003 .

[56]  B. Van Vliet-Lanoe Physico-chemical conditions determining the auto-fluorescence of clay minerals. , 1980 .

[57]  C. Bayer,et al.  Organic Matter Study of Whole Soil Samples Using Laser-Induced Fluorescence Spectroscopy , 2006 .

[58]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[59]  F. Rosario‐Ortiz,et al.  Evaluating fluorescence spectroscopy as a tool to characterize cyanobacteria intracellular organic matter upon simulated release and oxidation in natural water. , 2015, Water research.