Using UAV Collected RGB and Multispectral Images to Evaluate Winter Wheat Performance Across a Site Characterized by Century-Old Biochar Patches in Belgium
[en] Remote sensing data play a crucial role in monitoring crop dynamics in the context of precision agriculture by characterizing the spatial and temporal variability of crop traits. At present there is special interest in assessing the long-term impacts of biochar in agro-ecosystems. Despite the growing body of literature on monitoring the potential biochar effects on harvested crop yield and aboveground productivity, studies focusing on the detailed crop performance as a consequence of long-term biochar enrichment are still lacking. The primary objective of this research was to evaluate crop performance based on high-resolution unmanned aerial vehicle (UAV) imagery considering both crop growth and health through RGB and multispectral analysis, respectively. More specifically, this approach allowed monitoring of century-old biochar impacts on winter wheat crop performance. Seven Red-Green-Blue (RGB) and six multispectral flights were executed over 11 century-old biochar patches of a cultivated field. UAV-based RGB imagery exhibited a significant positive impact of century-old biochar on the evolution of winter wheat canopy cover (p-value = 0.00007). Multispectral optimized soil adjusted vegetation index indicated a better crop development over the century-old biochar plots at the beginning of the season (p-values < 0.01), while there was no impact towards the end of the season. Plant height, derived from the RGB imagery, was slightly higher for century-old biochar plots. Crop health maps were computed based on principal component analysis and k-means clustering. To our knowledge, this is the first attempt to quantify century-old biochar effects on crop performance during the entire growing period using remotely sensed data. Ground-based measurements illustrated a significant positive impact of century-old biochar on crop growth stages (p-value of 0.01265), whereas the harvested crop yield was not affected. Multispectral simplified canopy chlorophyll content index and normalized difference red edge index were found to be good linear estimators of harvested crop yield (p-value(Kendall) of 0.001 and 0.0008, respectively). The present research highlights that other factors (e.g., inherent pedological variations) are of higher importance than the presence of century-old biochar in determining crop health and yield variability.
Research center :
TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium LISAH, Univ Montpellier, INRAE, IRD, Institut Agro, 34060 Montpellier, France Urban and Environmental Engineering, University of Liège, 4000 Liège, Belgium Department of Environmental Sciences and Management, University of Liège, 6700 Arlon, Belgium
Heidarian Dehkordi, Ramin ; Université de Liège - ULiège > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > Eau, Environnement, Développement
Cornelis, Jean-Thomas ; Université de Liège - ULiège > Département GxABT > Echanges Eau-Sol-Plantes
Nguyen, Frédéric ; Université de Liège - ULiège > Département ArGEnCo > Géophysique appliquée
Denis, Antoine ; Université de Liège - ULiège > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > DER Sc. et gest. de l'environnement (Arlon Campus Environ.)
Meersmans, Jeroen ; Université de Liège - ULiège > Département GxABT > Analyse des risques environnementaux
Language :
English
Title :
Using UAV Collected RGB and Multispectral Images to Evaluate Winter Wheat Performance Across a Site Characterized by Century-Old Biochar Patches in Belgium
Malghani, S., Gleixner, G., Trumbore, S.E., Chars produced by slow pyrolysis and hydrothermal carbonization vary in carbon sequestration potential and greenhouse gases emissions (2013) Soil Biol. Biochem., 62, pp. 137-146
Trupiano, D., Cocozza, C., Baronti, S., Amendola, C., Vaccari, F.P., Lustrato, G., Di Lonardo, S., Scippa, G.S., The effects of biochar and its combination with compost on lettuce (Lactuca sativa L.) growth, soil properties, and soil microbial activity and abundance (2017) Int. J. Agron., 2017
Yamato, M., Okimori, Y., Wibowo, I.F., Anshori, S., Ogawa, M., Effects of the application of charred bark of Acacia mangium on the yield of maize, cowpea and peanut, and soil chemical properties in South Sumatra, Indonesia (2006) Soil Sci. Plant Nutr., 52, pp. 489-495
Montanarella, L., Lugato, E., The Application of Biochar in the EU: Challenges and Opportunities (2013) Agronomy, 3, pp. 462-473
Stewart, C.E., Zheng, J., Botte, J., Cotrufo, M.F., Co-generated fast pyrolysis biochar mitigates green-house gas emissions and increases carbon sequestration in temperate soils (2013) Gcb Bioenergy, 5, pp. 153-164
Kerré, B., Willaert, B., Cornelis, Y., Smolders, E., Long-term presence of charcoal increases maize yield in Belgium due to increased soil water availability (2017) Eur. J. Agron., 91, pp. 10-15
Lehmann, J., Da Silva, J.P., Steiner, C., Nehls, T., Zech, W., Glaser, B., Nutrient availability and leaching in an archaeological Anthrosol and a Ferralsol of the Central Amazon basin: Fertilizer, manure and charcoal amendments (2003) Plant Soil, 249, pp. 343-357
Biederman, L.A., Stanley Harpole, W., Biochar and its effects on plant productivity and nutrient cycling: A meta-analysis (2013) Gcb Bioenergy, 5, pp. 202-214
Glaser, B., Lehmann, J., Zech, W., Ameliorating physical and chemical properties of highly weathered soils in the tropics with charcoal-A review (2002) Biol. Fertil. Soils, 35, pp. 219-230
Jeffery, S., Meinders, M.B.J., Stoof, C.R., Bezemer, T.M., van de Voorde, T.F.J., Mommer, L., van Groenigen, J.W., Biochar application does not improve the soil hydrological function of a sandy soil (2015) Geoderma., 251-252, pp. 47-54
De la Rosa, J.M., Paneque, M., Miller, A.Z., Knicker, H., Relating physical and chemical properties of four different biochars and their application rate to biomass production of Lolium perenne on a Calcic Cambisol during a pot experiment of 79 days (2014) Sci. Total Environ., 499, pp. 175-184
Gray, M., Johnson, M.G., Dragila, M.I., Kleber, M., Water uptake in biochars: The roles of porosity and hydrophobicity (2014) Biomass Bioenergy, 61, pp. 196-205
Hardie, M., Clothier, B., Bound, S., Oliver, G., Close, D., Does biochar influence soil physical properties and soil water availability? (2014) Plant Soil, 376, pp. 347-361
Liu, X., Zhang, A., Ji, C., Joseph, S., Bian, R., Li, L., Pan, G., Paz-Ferreiro, J., Biochar's effect on crop productivity and the dependence on experimental conditions-a meta-analysis of literature data (2013) Plant Soil, 373, pp. 583-594
Glaser, B., Wiedner, K., Seelig, S., Schmidt, H.P., Gerber, H., Biochar organic fertilizers from natural resources as substitute for mineral fertilizers (2015) Agron. Sustain. Dev., 35, pp. 667-678
Lehmann, J., Rillig, M.C., Thies, J., Masiello, C.A., Hockaday, W.C., Crowley, D., Biochar effects on soil biota-A review (2011) Soil Biol. Biochem., 43, pp. 1812-1836
Major, J., Rondon, M., Molina, D., Riha, S.J., Lehmann, J., Maize yield and nutrition during 4 years after biochar application to a Colombian savanna oxisol (2010) Plant Soil, 333, pp. 117-128
Liang, B., Lehmann, J., Solomon, D., Kinyangi, J., Grossman, J., O'Neill, B., Skjemstad, J.O., Petersen, J., Black Carbon Increases Cation Exchange Capacity in Soils (2006) Soil Sci. Soc. Am. J., 70, pp. 1719-1730
Crane-Droesch, A., Abiven, S., Jeffery, S., Torn, M.S., Heterogeneous global crop yield response to biochar: A meta-regression analysis (2013) Environ. Res. Lett., p. 8
Jeffery, S., Abalos, D., Prodana, M., Bastos, A.C., Van Groenigen, J.W., Hungate, B.A., Verheijen, F., Biochar boosts tropical but not temperate crop yields (2017) Environ. Res. Lett., p. 12
Güereña, D., Lehmann, J., Hanley, K., Enders, A., Hyland, C., Riha, S., Nitrogen dynamics following field application of biochar in a temperate North American maize-based production system (2013) Plant Soil, 365, pp. 239-254
Van Zwieten, L., Kimber, S., Morris, S., Chan, K.Y., Downie, A., Rust, J., Joseph, S., Cowie, A., Effects of biochar from slow pyrolysis of papermill waste on agronomic performance and soil fertility (2010) Plant Soil, 327, pp. 235-246
Hernandez-Soriano, M.C., Kerré, B., Goos, P., Hardy, B., Dufey, J., Smolders, E., Long-term effect of biochar on the stabilization of recent carbon: Soils with historical inputs of charcoal (2016) Gcb Bioenergy, 8, pp. 371-381
Mastrolonardo, G., Calderaro, C., Cocozza, C., Hardy, B., Dufey, J., Cornelis, J.T., Long-term effect of charcoal accumulation in hearth soils on tree growth and nutrient cycling (2019) Front. Environ. Sci., 7, pp. 1-15
Mikan, C.J., Abrams, M.D., Mechanisms Inhibiting the Forest Development of Historic Charcoal Hearths in Southeastern Pennsylvania (1996) Can. J. For. Res., 26, pp. 1893-1898
Heidarian Dehkordi, R., Denis, A., Fouche, J., Burgeon, V., Cornelis, J.T., Tychon, B., Placencia, E., Meersmans, J., Remotely-sensed assessment of the impact of century-old biochar on chicory crop growth using high-resolution UAV-based imagery (2020) Int. J. Appl. Earth Obs. Geoinf., 91
Aragon, B., Houborg, R., Tu, K., Fisher, J.B., McCabe, M., Cubesats enable high spatiotemporal retrievals of crop-water use for precision agriculture (2018) Remote Sens., 10, p. 1867
Segarra, J., Buchaillot, M.L., Araus, J.L., Kefauver, S.C., Remote sensing for precision agriculture: Sentinel-2 improved features and applications (2020) Agronomy., 10, p. 641
Matese, A., Toscano, P., Di Gennaro, S.F., Genesio, L., Vaccari, F.P., Primicerio, J., Belli, C., Gioli, B., Intercomparison of UAV, aircraft and satellite remote sensing platforms for precision viticulture (2015) Remote Sens., 7, pp. 2971-2990
Berni, J.A.J., Zarco-Tejada, P.J., Sepulcre-Cantó, G., Fereres, E., Villalobos, F., Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery (2009) Remote Sens. Environ., 113, pp. 2380-2388
Gago, J., Douthe, C., Coopman, R.E., Gallego, P.P., Ribas-Carbo, M., Flexas, J., Escalona, J., Medrano, H., UAVs challenge to assess water stress for sustainable agriculture (2015) Agric. Water Manag., 153, pp. 9-19
Xia, T., Kustas, W.P., Anderson, M.C., Alfieri, J.G., Gao, F., McKee, L., Prueger, J.H., Sanchez, L., Mapping evapotranspiration with high-resolution aircraft imagery over vineyards using one-and two-source modeling schemes (2016) Hydrol. Earth Syst. Sci., 20, pp. 1523-1545
Roosjen, P.P.J., Suomalainen, J.M., Bartholomeus, H.M., Kooistra, L., Clevers, J.G.P.W., Mapping reflectance anisotropy of a potato canopy using aerial images acquired with an unmanned aerial vehicle (2017) Remote Sens., 9, p. 417
Zhang, C., Kovacs, J.M., The application of small unmanned aerial systems for precision agriculture: A review (2012) Precis. Agric., 13, pp. 693-712
Yuan, L., Huang, Y., Loraamm, R.W., Nie, C., Wang, J., Zhang, J., Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects (2014) Field Crop. Res., 156, pp. 199-207
Schils, R., Olesen, J.E., Kersebaum, K.C., Rijk, B., Oberforster, M., Kalyada, V., Khitrykau, M., Manolova, V., Cereal yield gaps across Europe (2018) Eur. J. Agron., 101, pp. 109-120
Su, J., Liu, C., Coombes, M., Hu, X., Wang, C., Xu, X., Li, Q., Chen, W.H., Wheat yellow rust monitoring by learning from multispectral UAV aerial imagery (2018) Comput. Electron. Agric., 155, pp. 157-166
Franke, J., Menz, G., Oerke, E.-C., Rascher, U., Comparison of multi-and hyperspectral imaging data of leaf rust infected wheat plants (2005) In Remote Sensing for Agriculture, 5976. , Ecosystems, and Hydrology VII
SPIE: Bellingham, WA, USA
Franceschini, M.H.D., Bartholomeus, H., van Apeldoorn, D.F., Suomalainen, J., Kooistra, L., Feasibility of unmanned aerial vehicle optical imagery for early detection and severity assessment of late blight in Potato (2019) Remote Sens., 11, p. 224
Baxter, S., World Reference Base for Soil Resources (2007) World Soil Resources Report 103. Rome: Food and Agriculture Organization of the United Nations, p. 132. , Cambridge University Press: Cambridge UK
Witzenberger, A., Lancashire, P., Phenological growth stages and BBCH-identification keys of cereals (2001) In Growth Stages Mono- and Dicotyledonous Plants BBCH Monograph, pp. 14-18. , Federal Biological Research Centre for Agriculture and Forestry: Berlin/Braunschweig, Germany
Clevers, J.G.P.W., Van Leeuwen, H.J., Sensing, R., Verhoef, W., Estimanting apar by means of vegetation indeces: A sensitivity analysis (1989) In XXIX ISPRS Congress Technical Commission VII: Interpretation of Photographic and Remote Sensing Data, pp. 691-698. , ISPRS: Christian Heipke, Germany
Bouman, B.A.M., Van Kasteren, H.W.J., Uenk, D., Standard relations to estimate ground cover and LAI of agricultural crops from reflectance measurements (1992) Eur. J. Agron., 1, pp. 249-262
Clevers, J.G.P.W., Kooistra, L., van den Brande, M.M.M., Using Sentinel-2 data for retrieving LAI and leaf and canopy chlorophyll content of a potato crop (2017) Remote Sens., 9, p. 405
Siegmann, B., Jarmer, T., Lilienthal, H., Richter, N., Selige, T., Höfled, B., Comparison of narrow band vegetation indices and empirical models from hyperspectral remote sensing data for the assessment of wheat nitrogen concentration (2013) In Proceedings of the 8th EARSeL Workshop on Imaging Spectroscopy, pp. 1-2. , Nantes, France, 8-10 April
Kooistra, L., Clevers, J.G.P.W., Estimating potato leaf chlorophyll content using ratio vegetation indices (2016) Remote Sens. Lett., 7, pp. 611-620
Gao, X., Huete, A.R., Ni, W., Miura, T., Optical-biophysical relationships of vegetation spectra without background contamination (2000) Remote Sens. Environ., 74, pp. 609-620
Gitelson, A.A., Gritz, Y., Merzlyak, M.N., Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves (2003) J. Plant Physiol., 160, pp. 271-282
Fitzgerald, G.J., Rodriguez, D., Christensen, L.K., Belford, R., Sadras, V.O., Clarke, T.R., Spectral and thermal sensing for nitrogen and water status in rainfed and irrigated wheat environments (2006) Precis. Agric., 7, pp. 233-248
Venkateswaran, K., Kasthuri, N., Balakrishnan, K., Prakash, K., Performance Analysis of K-Means Clustering For Remotely Sensed Images (2013) Int. J. Comput. Appl., 84, pp. 23-27
Pearson, K., On lines and planes of closest fit to systems of points in space (1901) Lond. Edinb. Dublin Philos. Mag. J. Sci., 2, pp. 559-572
Zhang, M., Liu, X., O'Neill, M., Spectral discrimination of Phytophthora infestants infection on tomatoes based on principal component and cluster analyses (2002) Int. J. Remote Sens., 23, pp. 1095-1107
Das, S., Singh, T.P., Correlation analysis between biomass and spectral vegetation indices of forest ecosystem (2012) Int. J. Eng. Res. Technol., 1, pp. 1-13
Rouse, J.W., Jr., Hass, R.H., Schell, J.A., Deering, D.W., Harlan, J.C., (1974) Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation, , Texas a&m University Remote Sensing Center: College Station, TX, USA
Clevers, J.G.P.W., The application of a weighted infrared-red vegetation index for estimating leaf area index by correcting for soil moisture (1989) Remote Sens. Environ., 29, pp. 25-37
Rondeaux, G., Steven, M., Baret, F., Optimization of soil-adjusted vegetation indices (1996) Remote Sens. Environ., 55, pp. 95-107
Vincini, M., Frazzi, E., D'Alessio, P., A broad-band leaf chlorophyll vegetation index at the canopy scale (2008) Precis. Agric., 9, pp. 303-319
Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X., Ferreira, L.G., Overview of the radiometric and biophysical performance of the MODIS vegetation indices (2002) Remote Sens. Environ., 83, pp. 195-213
Kim, T.K., T test as a parametric statistic (2015) Korean J. Anesthesiol., 68, p. 540
Kendall, A.M.G., A New Measure of Rank Correlation (1938) Biometrika, 30, pp. 81-93
Ten Harkel, J., Bartholomeus, H., Kooistra, L., Biomass and Crop Height Estimation of Different Crops Using UAV-Based Lidar (2020) Remote Sens., 12, p. 17
Carter, S., Shackley, S., Sohi, S., Suy, T., Haefele, S., The Impact of Biochar Application on Soil Properties and Plant Growth of Pot Grown Lettuce (Lactuca sativa) and Cabbage (Brassica chinensis) (2013) Agronomy, 3, pp. 404-418
Schulz, H., Dunst, G., Glaser, B., Positive effects of composted biochar on plant growth and soil fertility (2013) Agron. Sustain. Dev., 33, pp. 817-827
Parece, T.E., Campbell, J.B., (2015) Advances in Watershed Science and Assessment, 33. , Springer: Berlin, Germany
