Skip to main content

Advertisement

SpringerLink
Log in

In-field measurement and sampling technologies for monitoring quality in the sugarcane industry: a review

  • Published:
Precision Agriculture Aims and scope Submit manuscript

Abstract

Reliable in-field quality measurement and sampling techniques are needed in the sugarcane industry to accommodate spatial variability in crop quality during harvesting. Existing in-field monitoring systems only monitor the crop yield and do not have the ability to measure product quality. This is a serious limitation for the industry in dealing with a significant quality variation across a field. Conventional technologies for measuring sugarcane quality in a laboratory have severe limitations for field use because they require complex sample preparation procedures especially to have clarified juice samples for each measurement. This review focuses on the use of current and new emerging precision agricultural sensing technologies for measuring product quality and describes their potential application and limitation for field use in the sugarcane industry. Optical spectroscopy is among the most promising technologies for measuring sugarcane quality on a harvester. The key considerations for development of a measurement method and sampling mechanism in the field are also discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Abdel-Rahman, E. M., Ahmed, F. B., & van den Berg, M. (2010). Estimation of sugarcane leaf nitrogen concentration using in situ spectroscopy. Journal of Applied Earth Observation and Geoinformation International, 12S, 52–57.

    Article  Google Scholar 

  • Barber, A. (1997). Pneumatic handbook (8th ed., pp. 387–398). Oxford: Elsevier Science Ltd.

    Google Scholar 

  • Berding, N., Brotherton, G. A., & Skinner, J. C. (1991a). Near infrared reflectance spectroscopy for analysis of sugarcane from clonal evaluation trials: I. Fibrated cane. Crop Science, 31, 1017–1023.

    Article  Google Scholar 

  • Berding, N., Brotherton, G. A., & Skinner, J. C. (1991b). Near infrared reflectance spectroscopy for analysis of sugarcane from clonal evaluation Trials: II. Expressed juice. Crop Sciences, 31, 1024–1028.

    Article  Google Scholar 

  • Bramley, R. G. V. (2009). Lessons from nearly 20 years of Precision Agriculture research, development, and adoption as a guide to its appropriate application. Crop and Pasture Science, 60, 197–217.

    Article  Google Scholar 

  • Bramley, R. G. V., Panitz, J. H., Jensen, T., & Baillie, C. (2012). Within block spatial variation in CCS—another potentially important consideration in the application of precision agriculture to sugarcane production. In Proceedings of the Australian Society of Sugar Cane Technologists (vol. 34, pp. 1–8). Brisbane: Australian Society of Sugar Cane Technologists.

  • Bramley, R. G. V., & Quabba, R. P. (2001). Opportunities for improving the management of sugarcane production through the adoption of precision agriculture—An Australian perspective. Proceedings of the 24th Congress of the International Society of Sugar Cane Technologists (pp. 38–46). Brisbane: Australian Society of Sugar Cane Technologists.

    Google Scholar 

  • BSES, (2001). The laboratory manual for Australian sugar mills, vol. 2. Analytical methods and tables. Australia: BSES Limited.

  • Cadet, F. D. R., & Offmann, B. (1997). Direct spectroscopic sucrose determination of raw sugar cane juices. Journal of Agricultral and Food Chemistry, 45, 166–171.

    Article  CAS  Google Scholar 

  • Campbell, J. A., Hansen, R., & Wilson, J. R. (1999). Cost effective colorimetric microtitre plate enzymatic assays for sucrose, glucose and fructose in sugarcane tissue extracts. Journal of the Science of Food and Agriculture, 79, 232–236.

    Article  CAS  Google Scholar 

  • Carlini, P., Massantini, R., & Mencarelli, F. (2000). Measurement of soluble solids in cherry and apricot by PLS regression and wavelength selection. Journal of Agricultural and Food Chemistry, 48, 5236–5242.

    Article  PubMed  CAS  Google Scholar 

  • Caryn, B., Mailander, M., & Price, R. (2002). Sugar cane yield monitoring system. Baton Rouge, LA: Agricultural and Biological Engineering Louisiana State University.

    Google Scholar 

  • Chia, K. S., Rahim, H. A., & Rahim, R. A. (2012). Prediction of soluble solids content of pineapple via non-invasive low cost visible and shortwave near infrared spectroscopy and artificial neural network. Biosystems Engineering, 113, 158–165.

    Article  Google Scholar 

  • Cox, G. J., H. D. Harris, D. R. Cox, D. M. Bakker, R. A. Pax, & S. R. Zillman. (1999). Mass flow rate sensor for sugar cane harvesters. Australian Patent No. 744,047.

  • Cox, G. J. (2002). A yield mapping system for sugar cane chopper harvesters. PhD Dissertation. Toowoomba, Australia: Faculty of Engineering and Surveying, University of Southern Queensland.

  • Cox, G., Harris, H., Pax, R., & Dick, R. (1996). Monitoring cane yield by measuring mass flow rate through the harvester. Proceedings of the Australian Society of Sugar Cane Technologists (pp. 152–157). Brisbane: Australian Society of Sugar Cane Technologists.

    Google Scholar 

  • Dardenne, P. & Femenias, N. (1999). Diode array NIR instruments to analyse fresh forages. Near Infrared Spectroscopy. In A. M. C. Davies & R. Giangiacomo (Eds.), Proceedings of the 9th International Conference (pp. 121–124). Chichester, West Sussex, UK: NIR Publications.

  • Digman, M. F., & Shinners, K. J. (2008). Real time moisture measurement on a forage harvester using near infrared reflectance spectroscopy. Transactions of the ASABE, 51, 1801–1810.

    Article  Google Scholar 

  • Fernández-Ahumada, E., Garrido-Varo, A., & Guerrero-Ginel, J. E. (2008). Feasibility of diode-array instruments to carry near-infrared spectroscopy from laboratory to feed process control. Journal of Agriculture and Food Chemistry, 56, 3185–3192.

    Article  Google Scholar 

  • Filho, J. L. L., Pandey, P. C., & Weetal, H. H. (1996). An amperometric flow injection analysis enzyme sensor for sucrose using a tetracyanoquinodimethane modified graphite paste electrode. Biosensors and Bioelectronics, 11, 719–723.

    Article  Google Scholar 

  • Gavin, B. M. (2008). Development of a single drum chopper concept for a sugarcane harvester. Master (Research) thesis. Queensland, Australia: James Cook University.

  • Golic, M., Walsh, K. B., & Lawson, P. (2003). Short-wavelength near-infrared spectra of sucrose, glucose, and fructose with respect to sugar concentration and temperature. Applied Spectroscopy, 57, 139–145.

    Article  PubMed  CAS  Google Scholar 

  • Gouda, M. D., Kumar, M. A., Thakur, M. S., & Karanth, N. G. (2002). Enhancement of operational stability of an enzyme biosensor for glucose and sucrose using protein based stabilizing gents. Biosensors and Bioelectronics, 7, 503–507.

    Article  Google Scholar 

  • Hsieh, C., & Lee, Y. (2005). Applied visible/near-infrared spectroscopy on detecting the sugar content and hardness of pearl guava. Applied Engineering in Agriculture, 21(6), 1039–1046.

    Article  Google Scholar 

  • Huang, M., & Lu, R. (2010). Optimal wavelength selection for hyperspectral scattering prediction of apple firmness and soluble solids content. Transaction of the ASABE, 53(4), 1175–1182.

    Article  Google Scholar 

  • Jensen, T., Baillie, C., Bramley, G. V., DiBella, L., Whiteing, C. & Davis, R. (2010). Assessment of sugarcane yield monitoring technology for precision agriculture. In Proceedings of the Australian Society of Sugar Cane Technologists, (vol. 32, pp. 410–423). Brisbane: Australian Society of Sugar Cane Technologists.

  • Jensen, T. A., Baillie, C., Bramley, R. G. V., Panitz, J. H. & Schroeder, B. L. (2012). An assessment of sugarcane yield monitoring concepts and techniques from commercial yield monitoring systems. In Proceedings of the Australian Society of Sugar Cane Technologists, (vol. 34, pp. 8–15). Brisbane: Australian Society of Sugar Cane Technologists.

  • Johnson, R. M., & Richard, E. P, Jr. (2005). Sugarcane yield, sugarcane quality, and soil variability in Louisiana. Agronomy Journal, 97, 760–771.

    Article  Google Scholar 

  • Kennedy, J. F., Pimentel, M. C. B., Melo Eduardo, H. M., & Lima-Filho, J. L. (2007). Sucrose biosensor as an alternative tool for sugarcane field samples. Journal of the Science of Food and Agriculture, 87, 2266–2271.

    Article  CAS  Google Scholar 

  • Kim, Y., & Reid, J. F. (2006). Modeling and Calibration of a Multi-Spectral Imaging Sensor for In-Field Crop Nitrogen Assessment. Applied Engineering in Agriculture, 22(6), 935–941.

    Article  Google Scholar 

  • Klute, U. (2007). Microwave measuring technology for the sugar industry. International Sugar Journal, 109(1308), 1–6.

    Google Scholar 

  • Kumar, A. J., Gowri, N. M., Raju, R. V., Nirmala, G., Bellubbi, B. S., & Krishna, T. R. (2006). Study of fiber optic sugar sensor. Pramana Journal of Physics, 67(2), 383–387.

    Article  CAS  Google Scholar 

  • Kweon, G., & Maxton, C. (2013). Soil organic matter sensing with an on-the-go optical sensor. Biosystems Engineering, 115, 66–81.

    Article  Google Scholar 

  • Lawes, R. A., & Lawn, R. J. (2005). Applications of industry information in sugarcane production systems. Field Crops Research, 92, 353–363.

    Article  Google Scholar 

  • Lawes, R. A., Wegener, M. K., Basford, K. E., & Lawn, R. J. (2002). Commercial cane sugar trends in the Tully sugar district. Australian Journal of Experimental Agriculture, 40, 969–973.

    Article  Google Scholar 

  • Lehnert, R. (2010). Vacuum harvester passes bruising tests. Good Fruit Grower. Retrieved March 24, 2014, from (http://www.goodfruit.com/vacuum-harvester-passes-bruising-tests/).

  • Lindström, H., Malinen, J. & Marbach, R. 2004. Performance evaluation of standard and extended InGaAs detector array spectrometers. In A. M. C. Davies, & A. Garrido-Varo (Eds.), Near Infrared Spectroscopy: Stretching the NIR Spectrum to the Limit (pp. 99–104). Chichester, West Sussex, UK: NIR Publications.

  • Long, J. P., & Buckmaster, D. R. (2003). Development of an automated system for sampling crop material from a forage harvester. Applied Engineering in Agriculture, 19(2), 133–140.

    Google Scholar 

  • Madsen, L. R., White, B. E., & Rein, P. W. (2003). Evaluation of a near infrared spectrometer for the direct analysis of sugar cane. Journal of American Society of Sugarcane Technologists, 23, 80–92.

    Google Scholar 

  • Mailander, M., Benjamin, C., Price, R., & Hall, S. (2010). Sugar cane yield monitoring system. Applied Engineering in Agriculture, 26(6), 965–969.

    Article  Google Scholar 

  • Marcotte, D., Savoie, P., Martel, H. & Theriault, R. (1999). Precision agriculture for hay and forage crops: A review of sensors and potential applications, St. Joseph, MI: American Society of Agricultural Engineers, ASAE Paper No. 99–1049.

  • McCarthy, S. G. (2003). The integration of sensory control for a sugar cane harvester, PhD Thesis: Faculty of engineering and surveying, Australia: University of Southern Queensland.

  • McCarthy, S. G., & Billingsley, J. (2002). A sensor for the sugar cane harvester topper. Sensor Review, 22, 242–246.

    Article  Google Scholar 

  • McRae, T. A., Bull, J. K., Robotham, B. G. & Sweetnam, R. C. (1996). Measuring sugar content in variety trials. In Sugar 2000 symposium, Sugarcane: Research towards efficient and sustainable production (pp. 55–56). Brisbane, Australia: CSIRO Division of tropical crops and pastures.

  • Meade, G. P., & Chen, J. C. P. (1985). Sugar Cane Handbook (11th ed.). New York: Wiley.

    Google Scholar 

  • Mehrotra, R., & Siesler, H. W. (2003). Application of mid infrared/near infrared spectroscopy in sugar industry. Applied Spectroscopy Reviews, 38, 307–354.

    Article  CAS  Google Scholar 

  • Meyer, J. H. & Wood, R. A. 1988. Rapid analysis of cane juice by near infra-red reflectance. In Proceeding of the South African Sugar Technologists Association (vol. 62, pp. 203–207).

  • Montes, J. M., Utz, H. F., Schipprack, W., Kusterer, B., Muminovic, J., Paul, C., et al. (2006). Near-infrared spectroscopy on combine harvesters to measure maize grain dry matter content and quality parameters. Plant Breeding, 125, 591–595.

    Article  Google Scholar 

  • Mouazen, A. M., Baerdemaeker, J. D., & Ramon, H. (2005). Towards development of online soil moisture content sensor using a fibre-type NIR spectrophotometer. Soil and Tillage Research, 80, 171–183.

    Article  Google Scholar 

  • Nawi, N. M., Chen, G., & Jensen, T. (2013a). Visible and shortwave near infrared spectroscopy for predicting sugar content of sugarcane based on a cross-sectional scanning method. Journal of Near Infrared Spectroscopy, 21, 289–297.

    Article  CAS  Google Scholar 

  • Nawi, N. M., Chen, G., Jensen, T., & Mehdizadeh, S. A. (2013b). Prediction and classification of sugar content of sugarcane based on skin scanning using visible and shortwave near infrared. Biosystems Engineering, 115, 154–161.

    Article  Google Scholar 

  • Nawi, N. M., Jensen, T., & Chen, G. (2012). The application of spectroscopic methods to predict sugarcane quality based on stalk cross-sectional scanning. Journal of American Society of Sugar Cane Technologists, 32, 16–27.

    Google Scholar 

  • Nelson, S. O. (1987). Potential agricultural applications for RF and microwave energy. Transactions of the ASAE, 30(3), 818–831.

    Article  Google Scholar 

  • Nicolai, B. M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K. I., et al. (2007). Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review. Postharvest Biology and Technology, 46, 99–118.

    Article  Google Scholar 

  • O’Shea, M. G., Staunton, S. P., Donald, D. & Simpson, J. (2011). Developing laboratory near infra-red (NIR) instruments for the analysis of sugar factory products. In Proceedings of the Australian Society of Sugar Cane Technologists,(vol. 33, pp. 1–8). Brisbane: Australian Society of Sugar Cane Technologists.

  • Panigrahi, S., & Hofman V. (2003). On the go sugar sensor for determining sugar content during harvesting, U.S. Patent No. 6,624,888.

  • Paul, C. & Pfitzner, C. 2004. Analytical use of NIR diode array spectrometers on forage harvesters. In A. M. C. Davies, A. Garrido-Varo (Eds.), Near Infrared Spectroscopy: Stretching the NIR Spectrum to the Limit (pp. 333–338). Chichester, West Sussex, UK: NIR Publications.

  • Pollock, J. S., O’Hara, I. M. & Griffin, K. G. (2007). Aligning the drivers in the value chain—a new cane payment system for Mackay Sugar. In Proceedings of the Australian Society of Sugar Cane Technologists (vol. 29,pp. 1–8). Australian Society of Sugar Cane Technologists: Brisbane.

  • Pope, G., McDowall, R., Massey, W. & Staunton, S. 2004. The use of NIR spectroscopy in a cane quality incentive scheme. In: Proceedings of the Australian Society of Sugar Cane Technologists. Brisbane: Australian Society of Sugar Cane Technologists, 26, (CD-ROM) 8.

  • Price, R. R., Johnson, R. M., Viator, R. P., Larsen, J., & Peters, A. (2011). Fiber optic yield monitor for a sugarcane harvester. Transactions of the ASABE, 54(1), 31–39.

    Article  Google Scholar 

  • Purcell, D. E., Leonard, G. J., O’Shea, M. G., & Kokot, S. (2005). A chemometrics investigation of sugarcane plant properties based on the molecular composition of epicuticular wax. Chemometrics and Intelligent Laboratory Systems, 76, 135–147.

    Article  CAS  Google Scholar 

  • Rattey, A. R., Jackson, P. A., Hogarth, D. M., & McRae, T. A. (2009). Selection among genotypes in final stage sugarcane trials: Effects of time of year. Crop and Pasture Science, 60, 1165–1174.

    Article  Google Scholar 

  • Reyns, P., Ramon, B., Missotten, H., & De Baerdemaeker, J. (2002). A review of combine sensors for precision farming. Precision Agriculture, 3, 169–182.

    Article  Google Scholar 

  • Richard, C., Jackson, W. & Waguespack, Jr. H. (2001). Harvester trials and extraneous matter in the Louisiana sugar industry. In Proceedings of the International Society of Sugar Cane Technologists, Australian Society of Sugar Cane Technologists, Brisbane, 24(2), pp. 263–268.

  • Robotham, B. G. (2000). Production of an automated cane billet sampler for research trials. Sugar Research and development corporation—Project BSS156, Australia.

  • Sassenrath, G. F., Adams, E. R., & Williford, J. R. (2005). Rapid sampling system for determination of cotton fiber quality spatial variability. Applied Engineering in Agriculture, 21(1), 9–14.

    Article  Google Scholar 

  • Schupp, J., Baugher, T., Winzeler, E., & Schupp, M. (2011). Preliminary results with a vacuum assisted harvest system for apples. Fruit Notes, 76(4), 1–5.

    Google Scholar 

  • Shah, S., & Joshi, M. (2010). Modeling microwave drying kinetics of sugarcane bagasse. International Journal of Electronics Engineering, 2(1), 159–163.

    Google Scholar 

  • Simpson, R. & Naidoo, Y. (2010). Progress in improving laboratory efficiencies using near infrared spectroscopy (NIRS). In Proceedings of the International Society of Sugar Cane Technologists, (vol. 27, pp. 1–8). Brisbane: Australian Society of Sugar Cane Technologists.

  • Staunton, S., Donald, D. & Pope, G. (2011). Estimating sugarcane composition using ternary growth relationships. In Proceedings of the Australian Society of Sugar Cane Technologists,(vol. 33, pp. 1–8). Brisbane: Australian Society of Sugar Cane Technologists.

  • Staunton, S. P., Lethbridge, P. J., Grimley, S. C., Streamer, R. W., Rogers, J. & Mackintosh, D. L. (1999). On-line cane analysis by near infra-red spectroscopy. In Proceedings of the Australian Society of Sugar Cane Technologists, (vol. 21, pp. 20–27). Brisbane: Australian Society of Sugar Cane Technologists.

  • Staunton, S. P. & Wardrop, K. (2006). Development of an online bagasse analysis system using NIR spectroscopy. In Proceedings of the Australian Society of Sugar Cane Technologists,(vol. 28, pp. 446–453). Brisbane: Australian Society of Sugar Cane Technologists.

  • Sugiyama, J. (1999). Visualization of sugar content in the flesh of a melon by near-infrared imaging. Journal of Agriculture and Food Chemistry, 47, 2715–2718.

    Article  CAS  Google Scholar 

  • Sukhchain, S. D., & Saini, G. S. (1997). Inter-relationships among cane yield and commercial cane sugar and their component traits in autumn plant crop of sugarcane. Euphytica, 95, 109–114.

    Article  Google Scholar 

  • Taira, E., Ueno, M., & Kawamitsu, Y. (2010). Automated quality evaluation system for net and gross sugarcane samples using near infrared spectroscopy. Journal of Near Infrared Spectroscopy, 18, 209–215.

    Article  CAS  Google Scholar 

  • Tumbo, S. D., Wagner, D. G., & Heinemann, P. H. (2002). On-the-go sensing of chlorophyll status in corn. Transactions of the ASAE, 45, 1207–1215.

    Google Scholar 

  • Valderrama, P., Braga, J. W. B., & Poppi, R. J. (2007). Validation of multivariate calibration models in the determination of sugar cane quality parameters by near infrared spectroscopy. Journal of Brazilian Chemical Society, 18, 259–266.

    Article  CAS  Google Scholar 

  • Von Rosenberg, C., Abbate, A., Drake, J., & Mayes, D. (2000). A rugged near-infrared spectrometer for real-time measurements of grains during harvest. Spectroscopy, 15, 34–38.

    Google Scholar 

  • Walsh, K. B., Guthrie, J. A., & Burney, J. W. (2000). Application of commercially available, low-cost, miniaturised NIR spectrometers to the assessment of the sugar content of intact fruit. Australian Journal of Plant Physiology, 27, 1175–1186.

    CAS  Google Scholar 

  • Welle, R., Greten, W., Rietmann, B., Alley, S., Sinnaeve, G., & Dardenne, P. (2003). Near-infrared spectroscopy on chopper to measure maize forage quality parameters online. Crop Science, 43(4), 407–413.

    Article  Google Scholar 

  • Wendte, K. W., Skotnikov, A. & Thomas, K. K. (2001). Sugar cane yield monitor, U.S. Patent No. 6,272,819.

  • Wright, S., Brumb, S., Niebur, T. & Welle, R. (2002). Near‐infrared spectrometry for real‐time analysis of substances, U.S. Patent No. 6,483,583.

  • Zhang, N., Wang, M., & Wang, N. (2002). Precision agriculture—a worldwide overview. Computers and Electronics in Agriculture, 36, 113–132.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400, Selangor, Malaysia

    Nazmi Mat Nawi

  2. Faculty of Health, Engineering and Sciences, University of Southern Queensland, Toowoomba, QLD, 4350, Australia

    Nazmi Mat Nawi, Guangnan Chen & Troy Jensen

  3. National Centre for Engineering in Agriculture (NCEA), University of Southern Queensland, Toowoomba, QLD, 4350, Australia

    Guangnan Chen & Troy Jensen

Authors
  1. Nazmi Mat Nawi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guangnan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Troy Jensen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nazmi Mat Nawi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nawi, N.M., Chen, G. & Jensen, T. In-field measurement and sampling technologies for monitoring quality in the sugarcane industry: a review. Precision Agric 15, 684–703 (2014). https://doi.org/10.1007/s11119-014-9362-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-014-9362-9

Keywords

Search

Navigation