Analysis of Various Quality Attributes of Sunflower and Soybean Plants by Near Infrared Reflectance Spectroscopy: Development and Validation Calibration Models — Oak Academic Publishing
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Analysis of Various Quality Attributes of Sunflower and Soybean Plants by Near Infrared Reflectance Spectroscopy: Development and Validation Calibration Models
Agricultural and Environmental Services Laboratories, The University of Georgia Cooperative Extension, Athens, GA, USA
,
Southeast Watershed Research Laboratory, USDA-ARS, Tifton, GA, USA
,
Crop Protection and Management Research Laboratory, USDA-ARS, Tifton, GA, USA
,
Crop Protection and Management Research Laboratory, USDA-ARS, Tifton, GA, USA
,
Department of Crop and Soil Sciences, Miller Plant Science Building, University of Georgia, Athens, GA, USA
,
Agricultural and Environmental Services Laboratories, The University of Georgia Cooperative Extension, Athens, GA, USA
,
Sustainable Agricultural Systems Laboratory, USDA-ARS, Beltsville, MD, USA
,
Agricultural and Environmental Services Laboratories, The University of Georgia Cooperative Extension, Athens, GA, USA
1 Agricultural and Environmental Services Laboratories, The University of Georgia Cooperative Extension, Athens, GA, USA
2 Southeast Watershed Research Laboratory, USDA-ARS, Tifton, GA, USA
3 Crop Protection and Management Research Laboratory, USDA-ARS, Tifton, GA, USA
4 Crop Protection and Management Research Laboratory, USDA-ARS, Tifton, GA, USA
5 Department of Crop and Soil Sciences, Miller Plant Science Building, University of Georgia, Athens, GA, USA
6 Agricultural and Environmental Services Laboratories, The University of Georgia Cooperative Extension, Athens, GA, USA
7 Sustainable Agricultural Systems Laboratory, USDA-ARS, Beltsville, MD, USA
8 Agricultural and Environmental Services Laboratories, The University of Georgia Cooperative Extension, Athens, GA, USA
Soybean and sunflower are summer annuals that can be grown as an alternative to corn and may be particularly useful in organic production systems for forage in addition to their traditional use as protein and/or oil yielding crops. Rapid and low cost methods of analyzing plant forage quality would be helpful for nutrition management of livestock. We developed and validated calibration models using Near-infrared Reflectance Spectroscopic (NIRS) analysis for 27 different forage quality parameters of organically grown sunflower and soybean leaves or reproductive parts. Crops were managed under conventional tillage or no-till with a cover crop of wheat before soybean and rye-crimson clover before sunflower. From a population of 120 samples from both crops, covering multiple sampling dates within the treatments, calibration models were developed utilizing spectral information covering both visible and NIR region of 61 - 85 randomly chosen samples using modified partial least-squares (MPLS) regression with internal cross validation. Within MPLS protocol, we compared nine different math treatments on the quality of the calibration models. The math treatment “2,4,4,1” yielded the best quality models for all but starch and simple sugars (r 2 = 0.699 - 0.999; where the 1st digit is the number of the derivative with 0 for raw spectra, 1 for first derivative, and 2 for second derivative, the 2nd digit is the gap over which the derivative is calculated, the 3rd digit is the number of data points in a running average or smoothing, and the 4th digit is the second smoothing). Prediction of an independent validation set of 28-35 samples with these models yielded excellent agreement between the NIRS predicted values and the reference values except for starch (r 2 = 0.8260 - 0.9990). The results showed that the same model was able to adequately quantify a particular forage quality of both crops managed under different tillage treatments and at different stages of growth. Thus, these models can be reliably applied in the routine analysis of soybean and sunflower forage quality for the purposes of livestock nutrient management decisions.
KeywordsNIRSCalibrationSoybeanSunflowerValidation
Acikgoz, E., Sincik, M., Karasu, A., Tongel, O., Wietgrefe, G., Bilgili, U., Oz, M., Albayarak, S., Turan, Z.M. and Goksoy, A.T. (2009) Forage Soybean Production for Seed in Mediterranean Environments. Field Crops Research, 110, 213-218.
Devine, T.E. and McMurtrey III, J.E. (2004) Registration of “Tara” Soybean. Crop Science, 44, 1020-1021. https://doi.org/10.2135/cropsci2004.1020
Asekova, S., Shannon, J.G. and Lee, J.D. (2014) The Current Status of Forage Soybean. Plant Breeding and Biotechnology, 2, 334-341. https://doi.org/10.9787/PBB.2014.2.4.334
Orozco, L.R., Castro-Alegria, A. and Fievez, V. (2013) Ensiled Sorghum and Soybean as Ruminant Feed in the Tropics, with Emphasis on Cuba. Grass and Forage Science, 68, 20-32. https://doi.org/10.1111/j.1365-2494.2012.00890.x
Chang, S.R., Lu, C.-H., Lur, H.-S. and Hsu, F.-H. (2012) Forage Yield, Chemical Contents, and Silage Quality of Manure Soybean. Agronomy Journal, 104, 130-136. https://doi.org/10.2134/agronj2011.0015
Sheaffer, C.C., Orf, J.H., Devine, T.E. and Jewett, J.G. (2001) Yield and Quality of Forage Soybean. Agronomy Journal, 93, 99-106. https://doi.org/10.2134/agronj2001.93199x
Nielsen, D.C. (2011) Forage Soybean Yield and Quality Response to Water Use. Field Crops Research, 124, 400-407.
NDSU Extension Service (2007) Sunflower Production. Bulletin A-1331 (EB-25 Revised). North Dakota Agricultural Experiment Station and North Dakota State University Extension Service, Fargo, ND.
McClure, M.A., Allen, F.L., Johnson, R.D. and Heatherly, L.G. (2010) Sunflower: An Alternative Crop for Tennessee Producers. Production Guidelines and Tennessee Hybrid Trials. Bulletin SP721, The University of Tennessee Institute of Agriculture, Knoxville, TN.
NSA (National Sunflower Association) (2017) 2016 U.S. Sunflower Crop Quality Report. National Sunflower Association, Mandan, ND.
Mafakher, E., Meskarbashee, M., Hassibi, P. and Mashayekhi, M.R. (2010) Evaluation of Sunflower Silage in Development Stages. Asian Journal of Crop Science, 2, 20-24. https://doi.org/10.3923/ajcs.2010.20.24
Kansas Forage Task Force (2017) Sunflower Silage. Forage Facts Series Fora31. Kansas State University Agricultural Experiment Station and Cooperative Extension Service. https://www.asi.K-state.edu/doc/forage/fora31.pdf
Shenk, J.S., Westerhaus, M.O. and Hoover, M.R. (1979) Analysis of Forage by Near Infrared Reflectance. Journal of Dairy Science, 62, 807-812. https://doi.org/10.3168/jds.S0022-0302(79)83330-5
AOAC (1996) Moisture in Animal Feed, Method 930.15. 16th Edition, Official Methods of Analysis of AOAC International, Gaithersburg, MD.
Etheridge, R.D., Pesti, G.M. and Foster, E.H. (1998) A Comparison of Nitrogen Values Obtained Utilizing the Kjeldahl Nitrogen and Dumas Combustion Methodologies (Leco CNS 2000) on Samples Typical of an Animal Nutrition Analytical Laboratory. Animal Feed Science and Technology, 73, 21-28. https://doi.org/10.1016/S0377-8401(98)00136-9
Kirsten, W.J. (1979) Automated Methods for the Simultaneous Determination of Carbon, Hydrogen, Nitrogen and Sulfur, and Sulfur Alone in Organic and Inorganic Materials. Analytical Chemistry, 51, 1173-1179. https://doi.org/10.1021/ac50044a019
Dumas, J.B.A. (1831) Procedes de l’analyse Organic. Annales de Chimie et de Physique (Annals of Chemistry and of Physics), 247, 198-213.
ASTM Standards D3174-97 (1998) Standard Test Method for Ash in the Analysis Sample of Coal and Coke, Section 5, Vol. 05.05, Annual Book of ASTM Standards, ASTM International, West Conshohocken, PA, 303-305.
ANKOM Technology (2006) Neutral Detergent Fiber in Feeds-Filter Bag Technique, Method 6, ANKOM Technology. http://www.ankom.com/media/documents/NDF_081606_A200.pdf
ANKOM Technology (2006) Acid Detergent Fiber in Feeds Filter Bag Technique, Method 5, ANKOM Technology. http://www.ankom.com/media/documents/ADF_81606_A200.pdf
Undersander, D., Martens, D.R. and Thiex, N. (1993) National Forage Testing Association, Method 5.1: Determination of Amylase Neutral Detergent Fiber by Refluxing, Forage Analysis Procedures, National Forage Testing Association. http://www.foragetesting.org/index.php?page=lab_procedures
Undersander, D., Martens, D.R. and Thiex, N. (1993) National Forage Testing Association, Method 4.1: Determination of Acid Detergent Fiber by Refluxing, Forage Analysis Procedures, National Forage Testing Association. http://www.foragetesting.org/index.php?page=lab_procedures
ANKOM Technology (2005) Method for Determining Acid Detergent Lignin in Beakers, Method 08/05, ANKOM Technology Method 08/05. http://www.ankom.com/media/documents/ADL_beakers.pdf
Karkalas, J.J. (1985) An Improved Enzymatic Method for the Determination of Native and Modified Starch. Journal of the Science of Food and Agriculture, 36, 1019-1027. https://doi.org/10.1002/jsfa.2740361018
Holm, J., Bjorck, I., Drews, A. and Asp, N.G. (1986) A Rapid Method for the Analysis of Starch. Starch/Starke, 38, 224-226. https://doi.org/10.1002/star.19860380704
Smith, D. (1969) Removing and Analyzing Total Nonstructural Carbohydrates from Plant Tissue. Research Report No. 41, Wisconsin Agricultural Experiment Station.
Dubois, M., Gilles, K.A., Hamilton, J.K., Roberts, P.A. and Smith, F. (1956) Colorimetric Method for Determination of Sugars and Related Substances. Analytical Chemistry, 28, 350-356. https://doi.org/10.1021/ac60111a017
Harris Jr., B. (2003) Nonstructural and Structural Carbohydrates in Dairy Cattle Rations, Extension Circular 1122. University of Florida, IFAS.
USEPA (1995) Microwave Assisted Acid Digestion of Siliceous and Organically Based Matrices, Method 3052. 3rd Edition, Test Methods for Evaluating Solid Waste, US Environmental Protection Agency, Washington DC.
Creed, J.T., Brockhoff, C.A. and Martin, T.D. (1994) Determination of Trace Elements in Waters and Wastes by Inductively Coupled Plasma-Mass Spectrometry, US-EPA Method 200.8, Revision 5.4 EMMC Version. Environmental Monitoring Systems Laboratory, Office of Research and Development, Revision 5.4 EMMC Version, U.S. Environmental Protection Agency, Cincinnati, OH.
Rushing, J.B., Saha, U.K., Lemus, R., Sonon, L. and Baldwin, B.S. (2016) Analysis of Some Important Forage Quality Attributes of Southeastern Wildrye (Elymus glabriflorus) Using Near-Infrared Reflectance Spectroscopy. American Journal of Ana- lytical Chemistry, 7, 642-662.
Shenk, J.S. and Westerhaus, M.O. (1995) Analysis of Agriculture and Food Products by Near Infrared Reflectance Spectroscopy. Monograph, NIR Systems, Silver Spring, MD.
Shenk, J.S. and Westerhaus, M.O. (1991) Population Definition, Sample Selection and Calibration Procedures for Near Infrared Reflectance Spectroscopy. Crop Science, 31, 469-474. https://doi.org/10.2135/cropsci1991.0011183X003100020049x
Windham, W.R., Mertens, D.R. and Barton, F.E. (1989) Protocol for NIRS Calibration: Sample Selection and Equation Development and Validation. In: Marten, G.C., Ed., Near Infrared Reflectance Spectroscopy (NIRS): Analysis of Forage Quality, USDA Agricultural Handbook, Washington DC, 643.
Windham, W.R., Fales, S.L. and Hoveland, C.S. (1988) Analysis for Tannin Concentration in Sericea lespedeza by Near IR Reflectance Spectroscopy. Crop Science, 28, 705-708. https://doi.org/10.2135/cropsci1988.0011183X002800040031x
Shenk, J.S. and Westerhaus, M.O. (1996) Calibration the ISI Way. In: Davis, A.M.C. and Williams, P., Eds., Near Infrared Spectroscopy: The Future Waves, NIR Publications, Chichester, 198-202.
Lestander, T.A. and Christofer, R. (2005) Multivariate NIR Spectroscopy Models for Moisture, Ash and Calorific Content in Biofuels Using Bi-Orthogonal Partial Least Squares Regression. Analyst, 130, 1182-1189.
Saeys, W., Mouazen, A.M. and Ramon, H. (2005) Potential for Onsite and Online Analysis of Pig Manure Using Visible and Near Infrared Reflectance Spectroscopy. Biosystem Engineering, 91, 393-402.
Barnes, R.J., Dhanoa, M.S. and Lister, S.J. (1989) Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance Spectra. Applied Spectroscopy, 43, 772-777. https://doi.org/10.1366/0003702894202201
Shenk, J.S. and Westerhaus, M.O. (1991) Population Structuring of Near Infrared Spectra and Modified Partial Least Squares Regression. Crop Science, 31, 1548-1555. https://doi.org/10.2135/cropsci1991.0011183X003100060034x
Kim, K.S., Park, S.H. and Choung, M.G. (2007) Nondestructive Determination of Oil Content and Fatty Acid Composition in Perilla Seeds by Near-Infrared Spectroscopy. Journal of Agriculture and Food Chemistry, 55, 1679-1685. https://doi.org/10.1021/jf0631070
Chang, C.W., Laird, D.A., Mausbach, M.A. and Hurburgh Jr., C.R. (2001) Near-Infrared Reflectance Spectroscopy-Principal Components Regression Analyses of Soil Properties. Soil Science Society of America Journal, 65, 480-490. https://doi.org/10.2136/sssaj2001.652480x
Reeves III, J.B. (2001) Near-Infrared Diffuse Reflectance Spectroscopy for the Analysis of Poultry Manures. Journal of Agriculture and Food Chemistry, 49, 2193-2197. https://doi.org/10.1021/jf0013961
Mowrer, J., Kissel, D., Cabrera, M. and Hassan, S. (2014) Near-Infrared Calibrations for Organic, Inorganic, and Mineralized Nitrogen from Poultry Litter. Soil Science Society of America Journal, 78, 1775-1785. https://doi.org/10.2136/sssaj2013.12.0532
Bellon-Maurel, V., Fernandez-Ahumada, E., Roger, B.P.J.M. and McBratney, A. (2010) Critical Review of Chemometric Indicators Commonly Used for Assessing the Quality of the Prediction of Soil Attributes by NIR Spectroscopy. Trends in Analytical Chemistry, 29, 1073-1081.
Williams, P.C. and Sobering, D.C. (1996) How Do We Do It: A Brief Summary of the Methods We Use in Developing Near Infrared Calibration. In: Davis, A.M.C. and Williams, P., Eds., Near Infrared Spectroscopy: The Future Waves, NIR Publications, Chichester, 185-188.
Ward, A., Nielsen, A.L. and Moller, H. (2011) Rapid Assessment of Mineral Concentration in Meadow Grasses by Near Infrared Reflectance Spectroscopy. Sensors, 11, 4830-4839. https://doi.org/10.3390/s110504830
Williams, P. (2014) Tutorial: The RPD Statistic: A Tutorial Note.NIR News, 25, 22-26.
Fassio, A., Gimenez, A., Fernandez, E., Martins, D.V. and Cozzolino, D. (2007) Prediction of Chemical Composition in Sunflower Whole Plant and Silage (Helianthus annus L.) by Near Infrared Reflectance Spectroscopy. Journal of Near Infrared Spectroscopy, 15, 201-207. https://doi.org/10.1255/jnirs.731
Asekova, S., Han, S.I., Choi, H.-J., Park, S.-J., Shin, D.-H., Kwon, C.-H., Shannon, J.G. and Lee, J.-D. (2016) Determination of Forage Quality by Near-Infrared Reflectance Spectroscopy in Soybean. Turkish Journal of Agriculture and Forestry, 40, 45-52. https://doi.org/10.3906/tar-1407-33
Erdogan, S. and Demirel, M. (2016) Conservation Characteristics and Nutritive Value of Sunflower Silages as Affected by the Maturity Stages and Fibrolytic Enzymes. Turkish Journal of Agriculture-Food Science and Technology, 4, 464-469. https://doi.org/10.24925/turjaf.v4i6.464-469.652
Pérez-Marín, D., Garrido-Varo, A., De Pedro, E. and Guerrero-Ginel, J.E. (2007) Chemometric Utilities to Achieve Robustness in Liquid NIRS Nalibrations: Application to Pig Fat Analysis. Chemometrics and Intelligent Laboratory Systems, 87, 241-246.
Osborne, B.G., Fearn, T. and Hindle, P.H. (1993) Practical NIR Spectroscopy with Applications in Food and Beverage Analysis. Longman Scientific and Technical, Harlow.
Workman Jr., J. and Weyer, L. (2012) Practical Guide and Spectral Atlas for Interpretive Near-Infrared Spectroscopy. CRC Press, Boca Raton, 326. https://doi.org/10.1201/b11894
Kim, K.S., Park, S.H. and Choung, M.G. (2006) Nondestructive Determination of Lignans and Lignan Glycosides in Sesame Seeds by Near Infrared Reflectance Spectroscopy. Journal of Agriculture and Food Chemistry, 54, 4544-4550. https://doi.org/10.1021/jf0605603
Sato, T., Maw, A.A. and Katsuta, M. (2003) NIR Reflectance Spectroscopic Analysis of the FA Composition in Sesame (Sesamum indicum L.) Seeds. Journal of the American Oil Chemists’ Society, 80, 1157-1162. https://doi.org/10.1007/s11746-003-0835-5
Lestander, T.A., Johnsson, B. and Grothage, M. (2009) NIR Techniques Create Added Values for the Pellet and Biofuel Industry. Bioresource Technology, 100, 1589-1594.
Vogel, K.P., Dien, B.S., Jung, H.G., Casler, M.D., Masterson, S.D. and Mitchell, R.B. (2010) Quantifying Actual and Theoretical Ethanol Yields for Switchgrass Strains Using NIRS Analyses. Bioenergy Research, 4, 96-110. https://doi.org/10.1007/s12155-010-9104-4
Everard, C.D., McDonnell, K.P. and Fagan, C.C. (2012) Prediction of Biomass Gross Calorific Values Using Visible and Near Infrared Spectroscopy. Biomass and Bioenergy, 45, 203-209.
Williams, P. (2003) Near-infrared Technology—Getting the Best out of Light. PDK Grain. Nanaimo, Canada.
Huang, C.J., Han, L.J., Yang, Z.L. and Liu, M. (2009) Exploring the Use of Near Infrared Reflectance Spectroscopy to Predict Minerals in Straw. Fuel, 88, 163-168.
Zornoza, R., Guerrero, C., Mataix-Solera, J., Scow, K.M., Arcenegui, V. and Mataix-Beneyto, J. (2008) Near Infrared Spectroscopy for Determination of Various Physical, Chemical and Biochemical Properties in Mediterranean Soils. Soil Biology and Biochemistry, 40, 1923-1930.
Gonzalez-Martin, I., Hernandez-Hierro, J.M. and Gonzalez-Cabrera, J.M. (2007) Use of NIRS Technology with a Remote Reflectance Fibre-Optic Probe for Predicting Mineral Composition (Ca, K, P, Fe, Mn, Na, Zn), Protein and Moisture in Alfalfa. Analytical and Bioanalytical Chemistry, 387, 2199-2205. https://doi.org/10.1007/s00216-006-1039-4
Van Maarschalkerweerd, M. and Husted, S. (2015) Recent Developments in Fast Spectroscopy for Plant Mineral Analysis. Frontiers in Plant Sciences, 6, 169. https://doi.org/10.3389/fpls.2015.00169
Buxton, D.R. and Mertens, D.R. (1991) Errors in Forage-Quality Data Predicted by Near Infrared Reflectance Spectroscopy. Crop Science, 31, 212-218. https://doi.org/10.2135/cropsci1991.0011183X003100010047x
Hoffman, P.C., Brehm, N.M., Bauman, L.M., Peters, J.B. and Undersander, D.J. (1998) Prediction of Laboratory and In-Situ Protein in Legume and Grass Silages Using Near-Infrared Reflectance Spectroscopy. Journal of Dairy Science, 82, 764-770. https://doi.org/10.3168/jds.S0022-0302(99)75294-X
Dimov, Z., Suprianto, E., Hermann, F. and Mollers, C. (2011) Genetic Variation for Seed Hull and Fibre Content in a Collection of European Winter Oilseed Rape Material (Brassica napus L.) and Development of NIRS Calibrations. Plant Breeding, 131, 361-368. https://doi.org/10.1111/j.1439-0523.2012.01951.x
Roberts, C.A., Stuth, J. and Finn, P.C. (2003) NIRS Applications in Forages and Feedstuffs. In: Roberts, C.A., Workman, J. and Reeves, J., Eds., Near Infra-Spectroscopy in Agriculture, Agronomy Monograph 321, Soil Science Society of America/American Society of Agronomy/Crop Science Society of America, Madison.
Clark, D.H., Mayland, H.F. and Lamb, R.C. (1987) Mineral Analysis of Forages with Near IR Reflectance Spectroscopy. Agronomy Journal, 79, 485-490. https://doi.org/10.2134/agronj1987.00021962007900030016x
Petisco, C., Garcia-Criado, B., DeAldana, B.R.V., Zabalgogeazcoa, I., Mediavilla, S. and Garcia-Ciudad, A. (2005) Use of Near-Infrared Reflectance Spectroscopy in Predicting Nitrogen, Phosphorus and Calcium Contents in Heterogeneous Woody Plant Species. Analytical and Bioanalytical Chemistry, 382, 458-465. https://doi.org/10.1007/s00216-004-3046-7
Hawkesford, M., Horst, W., Kichey, T., Lambers, H., Schjoerrin, J.K. and Moller, I.S. (2012) Functions of Macronutrients. In: Marschner, P., Ed., Mineral Nutrition of Higher Plants, 3rd Edition, Elsevier, London, 135-189.
Menesatti, P., Antonucci, F., Pallottino, F., Roccuzzo, G., Allegra, M. and Stagno, F. (2010) Estimation of Plant Nutritional Status by Vis-NIR Spectrophotometric Analysis on Orange Leaves[Citrus sinensis (L) Osbeck cv. tarocco]. Biosystem Engineering, 105, 448-454.
Liao, H., Wu, J., Chen, W., Guo, W. and Shi, C. (2012) Rapid Diagnosis of Nutrient Elements in Fingered Citron Leaf Using Near Infrared Reflectance Spectroscopy. Journal of Plant Nutrition, 35, 1725-1734. https://doi.org/10.1080/01904167.2012.698352
Dealdana, B.R.V., Criado, B.G., Ciudad, A.G. and Corona, M.E.P. (1995) Estimation of Mineral-Content in Natural Grasslands by Near-Infrared Reflectance Spectroscopy. Communications in Soil Science and Plant Analysis, 26, 1383-1396. https://doi.org/10.1080/00103629509369379
Tremblay, G.F., Nie, Z., Belanger, G., Pelletier, S. and Allard, G. (2009) Predicting Timothy Mineral Concentrations, Dietary Cation-Anion Difference, and Grass Tetany Index by Near-Infrared Reflectance Spectroscopy. Journal of Dairy Science, 92, 4499-4506.
Villatoro-Pulido, M., Rojas, R.M., Munoz-Serrano, A., Cardenosa, V., Lopez, M.A.A. and Font, R. (2012) Characterization and Prediction by Near-Infrared Reflectance of Mineral Composition of Rocket (Eruca vesicaria subsp. sativa and Eruca vesicaria subsp. vesicaria). Journal of Science of Food and Agriculture, 92, 1331-1340. https://doi.org/10.1002/jsfa.4694