Current Status and Future Trends of Mechanized Fruit Thinning Devices and Sensor Technology
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33117
Current Status and Future Trends of Mechanized Fruit Thinning Devices and Sensor Technology

Authors: Marco Lopes, Pedro D. Gaspar, Maria P. Simões

Abstract:

This paper reviews the different concepts that have been investigated concerning the mechanization of fruit thinning as well as multiple working principles and solutions that have been developed for feature extraction of horticultural products, both in the field and industrial environments. The research should be committed towards selective methods, which inevitably need to incorporate some kinds of sensor technology. Computer vision often comes out as an obvious solution for unstructured detection problems, although leaves despite the chosen point of view frequently occlude fruits. Further research on non-traditional sensors that are capable of object differentiation is needed. Ultrasonic and Near Infrared (NIR) technologies have been investigated for applications related to horticultural produce and show a potential to satisfy this need while simultaneously providing spatial information as time of flight sensors. Light Detection and Ranging (LIDAR) technology also shows a huge potential but it implies much greater costs and the related equipment is usually much larger, making it less suitable for portable devices, which may serve a purpose on smaller unstructured orchards. Portable devices may serve a purpose on these types of orchards. In what concerns sensor methods, on-tree fruit detection, major challenge is to overcome the problem of fruits’ occlusion by leaves and branches. Hence, nontraditional sensors capable of providing some type of differentiation should be investigated.

Keywords: Fruit thinning, horticultural field, portable devices, sensor technologies.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3607801

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 987

References:


[1] Akdag, R.; Danzon, M.: "European charter on countering obesity" WHO European Ministerial conference on counteracting obesity., no (2006).
[2] Berlage, A.; Langmo, R.: "Machine-vs hand-thinning of peaches." Transactions of the American Society of Agricultural Engineers (ASAE), Vol. 25 n.º 3 (1982), pp. 538-543.
[3] Martin, B.; Torregrosa, A.; Brunton, J. G.: "Post-bloom thinning of peaches for canning with hand-held mechanical devices" Scientia Horticulturae, Vol. 125 no 4 (2010), pp. 658–665.
[4] Diezma, B.; Rosa, U.: "Monitoring of fruit removal for mechanical thinning of peaches" Frutic, Vol. 5 no (2005), pp. 12–16.
[5] Rosa, U.; Cheetancheri, K.; Gliever, C.; Lee, S.; Thompson, J.; Slaughter, D.: "An electro-mechanical limb shaker for fruit thinning" Computers and Electronics in Agriculture, Vol. 61 no 2 (2008), pp. 213–221.
[6] Baugher, T. A.; Elliott, K. C.; Leach, D. W.; Horton, B.; Miller, S. S.: "Improved methods of mechanically thinning peaches at full bloom" Journal of the American Society for Horticultural Science, Vol. 116 no 5 (1991), pp. 766–769.
[7] Glenn, D. M.; Peterson, D. L.; Giovannini, D.; Faust, M.: "Mechanical thinning of peaches is effective postbloom" HortScience, Vol. 29 no 8 (1994), pp. 850–853.
[8] Peach blossom thinning device, Phil Brown (accessed 2018, September 24). Retrieved from http://www.philbrownwelding.com/index.php/peach-blossom-thinner.
[9] Schupp, J.; Baugher, T. A.; Miller, S.; Harsh, R.; Lesser, K.: "Mechanical thinning of peach and apple trees reduces labor input and increases fruit size" HortTechnology, Vol. 18 no 4 (2008), pp. 660–670.
[10] Baugher, T. A.; Schupp, J.; Lesser, K.; Hess-Reichard, K.: "Horizontal string blossom thinner reduces labor input and increases fruit size in peach trees trained to open-center systems" HortTechnology, Vol. 19 no 4 (2009), pp. 755–761.
[11] Baugher, T. A.; Schupp, J.; Ellis, K.; Remcheck, J.; Winzeler, E.; Duncan, R.; Johnson, S.; Lewis, K.; Reighard, G.; Henderson, G.; others: "String blossom thinner designed for variable tree forms increases crop load management efficiency in trials in four United States peach-growing regions" HortTechnology, Vol. 20 no 2 (2010), pp. 409–414.
[12] Darwin 300, blossom thinner with flexible stems. (accessed 2018, September 24). Retrieved from http://fruit-tec.com/en/202200-2.
[13] USDA drum-shaker, fruit thinner. (accessed 2018, September 24). Retrieved from https://ucanr.edu/sites/fruitreport/Thinning/Mechanical_Thinning/.
[14] Dise, R.; Heinemann, P.: "Automated String Thinner Positioning" 2011 Mid-Atlantic Fruit and Vegetable Convention, Hershey Lodge and Convention Center, Hershey, Pennsylvania, USA (2011).
[15] Aasted, M.; Dise, R.; Auxt Baugher, T.; Schupp, J. R.; Heinemann, P. H.; Singh, S.: "Autonomous Mechanical Thinning Using Scanning LIDAR", 2011 ASABE Annual International Meeting, Louisville, Kentucky, (2011).
[16] Johnson, R. S.; Phene, B.; Slaughter, D.; DeJong, T.; Day, K.; Duncan, R.; Norton, M.; Hasey, J.: "Mechanical Blossom Thinning Using a Darwin String Thinner" CTFA Annual Research Report, no (2010).
[17] Glozer, K.; Hasey, J.: "Mechanical thinning in cling peach" HortScience, Vol. 41 no 4 (2006), pp. 995–995.
[18] Miller, S. S.; Schupp, J. R.; Baugher, T. A.; Wolford, S. D.: "Performance of mechanical thinners for bloom or green fruit thinning in peaches" HortScience, Vol. 46 no 1 (2011), pp. 43–51.
[19] Blanke, M.; Damerow, L.: A novel device for precise and selective thinning in fruit crops to improve fruit quality. International Symposium on Application of Precision Agriculture for Fruits and Vegetables, ISHS Acta Horticulturae 824 (2009), pp. 275–280.
[20] Martin-Gorriz, B.; Torregrosa, A.; Brunton, J.G.: "Post-bloom mechanical thinning for can peaches using a hand-held electrical device" Scientia Horticulturae, Vol. 144 no (2012), pp. 179–186.
[21] Martin-Gorriz, B.; Mira, A. T.; Brunton, J. G.; Pallares, R. A.: A Hand-held Mechanical Blossom and Post-bloom Thinning Device for Peach Trees. (Power and Machinery. International Conference of Agricultural Engineering-CIGR-AgEng 2012: agriculture and engineering for a healthier life, Valencia, Spain, 8-12 July 2012), pp. P–0154.
[22] Simões, M. P.; Vuleta, I.; Belusic, N.: "Monda mecânica de flores com equipamento electro flor em pessegueiros da cultivar Rich Lady" Revista de Ciências Agrárias, Vol. 36 no 3 (2013), pp. 297–302.
[23] Commercially available portable solution for blossom thinning (accessed 2018, September 24). Retrieved from https://www.infaco.com/fr/les-produits/powercoup-pw2/fiche-produit#pw2_eclaircisseuse.
[24] Cinch coupled to a driller, and its inventor accessed 2018, September 24). Retrieved from https://fruitgrowersnews.com/article/new-device-makes-peach-thinning-a-cinch/.
[25] Nielsen, M.; Slaughter, D. C.; Gliever, C.: "Vision-based 3D peach tree reconstruction for automated blossom thinning" Industrial Informatics, IEEE Transactions on, Vol. 8 no 1 (2012), pp. 188–196.
[26] "Patent US2013312322 (A1), Device for Thinning and Harvesting Fruit and Flowers, 28 Nov. 2013."no (n.d.).
[27] "Patent CN102217493 (A), Ultrasonic targeted electric flower and fruit thinning machine, Oct 19, 2011. "no (n.d.).
[28] "Patent KR101336350 (B1), Fruit defoliating and thinning device for use in fruit trees, Dec 4, 2013"no (n.d.).
[29] "Patent CN203327599 (U), Flower and fruit thinning machine, Dec 11, 2013."no (n.d.).
[30] Tukey, L.: "A linear electric device for continuous measurement and recording of fruit enlargement and contraction" Journal of the American Society for Horticultural Science, Vol. 84 no (1964), pp. 653–660.
[31] Klepper, B.; Browning, V. D.; Taylor, H. M.: "Stem diameter in relation to plant water status" Plant Physiology, Vol. 48 no 6 (1971), pp. 683–685.
[32] Higgs, K.; Jones, H.: "A microcomputer-based system for continuous measurement and recording fruit diameter in relation to environmental factors" Journal of Experimental Botany, Vol. 35 no 11 (1984), pp. 1646–1655.
[33] Beedlow, P. A.; Daly, D. S.; Thiede, M. E.: "A new device for measuring fluctuations in plant stem diameter: Implications for monitoring plant responses: Note." Environmental Monitoring and Assessment, Vol. 6 no 3 (1986), pp. 277–82.
[34] Link, S.; Thiede, M.; Van Bavel, M.: "An improved strain-gauge device for continuous field measurement of stem and fruit diameter" Journal of Experimental Botany, Vol. 49 no 326 (1998), pp. 1583–1587.
[35] Morandi, B.; Manfrini, L.; Zibordi, M.; Noferini, M.; Fiori, G.; Grappadelli, L. C.: "A low-cost device for accurate and continuous measurements of fruit diameter" HortScience, Vol. 42 no 6 (2007), pp. 1380–1382.
[36] Iraguen, V.; Guesalaga, A.; Agosin, E.: "A portable non-destructive volume meter for wine grape clusters" Measurement Science and Technology, Vol. 17 no 12 (2006), pp. N92.
[37] Moreda, G.; Ortiz-Cañavate, J.; Garc’\ia-Ramos, F. J.; Ruiz-Altisent, M.: "Non-destructive technologies for fruit and vegetable size determination-a review" Journal of Food Engineering, Vol. 92 no 2 (2009), pp. 119–136.
[38] Laing, A.; Smit, Q.; Mortimer, B.; Tapson, J.: "Ultrasonic fruit sizing device" Journal of the South African Acoustics Institute, Vol. 6 no (1995), pp. 60–65.
[39] Jiménez, A. R.; Jain, A. K.; Ceres, R.; Pons, J.: "Automatic fruit recognition: a survey and new results using range/attenuation images" Pattern recognition, Vol. 32 no 10 (1999), pp. 1719–1736.
[40] Scarfe, A. J.; Flemmer, R. C.; Bakker, H.; Flemmer, C.L.: Development of an autonomous kiwifruit picking robot. (4th International Conference on Autonomous Robots and Agents, 2009. ICARA 2009), pp. 380–384.
[41] Ceres, R.; Pons, J.; Jimenez, A.; Martin, J.; Calderon, L.: "Design and implementation of an aided fruit-harvesting robot (Agribot)" Industrial Robot: An International Journal, Vol. 25 no 5 (1998), pp. 337–346.
[42] Baeten, J.; Donné, K.; Boedrij, S.; Beckers, W.; Claesen, E.: Autonomous fruit picking machine: A robotic apple harvester. (Field and Service Robotics), pp. 531–539.
[43] Li, P.; Lee, S.; Hsu, H.-Y.: "Review on fruit harvesting method for potential use of automatic fruit harvesting systems" Procedia Engineering, Vol. 23 no (2011), pp. 351–366.
[44] Edan, Y.: "Design of an autonomous agricultural robot" Applied Intelligence, Vol. 5 no 1 (1995), pp. 41–50.
[45] De-An, Z.; Jidong, L.; Wei, J.; Ying, Z.; Yu, C.: "Design and control of an apple harvesting robot" Biosystems Engineering, Vol. 110 no 2 (2011), pp. 112–122.
[46] Jimenez, A.; Ceres, R.; Pons, J.; others: "A survey of computer vision methods for locating fruit on trees" Transactions of the American Society of Agricultural Engineers (ASAE), Vol. 43 no 6 (2000), pp. 1911–1920.
[47] Pereira, C. A. P.: "Utilización de imágenes digitales para medición del diámetro de frutos de Mandarina (Citrus reticulata) en crecimiento." Revista Ciencia y Tecnolog’\ia, Vol. 6 no 1 (2013), pp. 1–9.
[48] Zhao, J.; Tow, J.; Katupitiya, J.: On-tree fruit recognition using texture properties and color data. (2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005 (IROS 2005)), pp. 263–268.
[49] Zeng, Q.; Liu, C.; Miao, Y.; Fei, S.; Wang, S.: A machine vision system for continuous field measurement of grape fruit diameter. (IITA’08. Second International Symposium on Intelligent Information Technology Application, 2008.), pp. 1064–1068.
[50] Yang, L.; Dickinson, J.; Wu, Q.; Lang, S.: A fruit recognition method for automatic harvesting. (14th International Conference on Mechatronics and Machine Vision in Practice, 2007. M2VIP 2007), pp. 152–157.
[51] Patel, H.; Jain, R.; Joshi, M.: "Automatic segmentation and yield measurement of fruit using shape analysis" International Journal of Computer Applications, Vol. 45 no 7 (2012), pp. 19–24.
[52] Bulanon, D.; Kataoka, T.; Ota, Y.; Hiroma, T.: "AE—automation and emerging technologies: a segmentation algorithm for the automatic recognition of Fuji apples at harvest" Biosystems Engineering, Vol. 83 no 4 (2002), pp. 405–412.
[53] Kohno, Y.; Kondo, N.; Iida, M.; Kurita, M.; Shiigi, T.; Ogawa, Y.; Kaichi, T.; Okamoto, S.: "Development of a mobile grading machine for citrus fruit" Engineering in agriculture, Environment and Food, Vol. 4 no 1 (2011), pp. 7–11.
[54] Nielsen, M.; Slaughter, D.C.; Gliever, C.; Upadhyaya, S.: Orchard and tree mapping and description using stereo vision and lidar. SPC-03: IV International Workshop on Computer Image Analysis in Agriculture (2012).
[55] Nielsen, M.; Slaughter, D.; Gliever, C.: Stereo vision blossom mapping for automated thinning in peach. (2010 IEEE International Symposium on Industrial Electronics (ISIE)), pp. 499–504.
[56] Hahn, F.; Sanchez, S.: "Carrot volume evaluation using imaging algorithms" Journal of Agricultural Engineering Research, Vol. 75 no 3 (2000), pp. 243–249.
[57] Hoffmann, T.; Wormanns, G.; Fürll, C.; Poller, J.: "A system for determining starch in potatoes online" Res. Papers Lithuanian Inst. Agric. Eng. Lithuanian Univ. Agric., 37 (2005), pp. 34-43.
[58] Jordan, R. B.; Clark, C. J.: "Sorting of kiwifruit for quality using drop velocity in water" Transactions of the ASAE, Vol. 47 no 6 (2004), pp. 1991–1998.
[59] Alfatni, M. S. M.; Shariff, A. R. M.; Abdullah, M. Z.; Marhaban, M. H. B.; Saaed, O. M. B.: "The application of internal grading system technologies for agricultural products-Review" Journal of Food Engineering, Vol. 116 no 3 (2013), pp. 703–725.
[60] Ruiz-Altisent, M.; Ruiz-Garcia, L.; Moreda, G.; Lu, R.; Hernandez-Sanchez, N.; Correa, E.; Diezma, B.; Nicolai, B.; Garcia-Ramos, J.: "Sensors for product characterization and quality of specialty crops—A review" Computers and Electronics in Agriculture, Vol. 74 no 2 (2010), pp. 176–194.
[61] Opara, U. L.; Pathare, P. B.: "Bruise damage measurement and analysis of fresh horticultural produce—A review" Postharvest Biology and Technology, Vol. 91 no (2014), pp. 9–24.
[62] Butz, P.; Hofmann, C.; Tauscher, B.: "Recent developments in noninvasive techniques for fresh fruit and vegetable internal quality analysis" Journal of Food Science, Vol. 70 no 9 (2005), pp. R131–R141.
[63] Ruiz-Altisent, M.; Lleó, L.; Riquelme, F.: "Instrumental quality assessment of peaches: fusion of optical and mechanical parameters" Journal of Food Engineering, Vol. 74 no 4 (2006), pp. 490–499.
[64] Gall, H.: "A ring sensor system using a modified polar coordinate system to describe the shape of irregular objects" Measurement Science and Technology, Vol. 8 no 11 (1997), pp. 1228.
[65] Moreda, G.; Ortiz-Canavate, J.; Garcia-Ramos, F.; Homer, I.; Ruiz-Altisent, M.: "Optimal operating conditions for an optical ring sensor system to size fruits and vegetables" Applied Engineering in Agriculture, Vol. 21 n.º 4 (2005), pp. 661−670.
[66] Moreda, G.; Ortiz-Cañavate, J.; García-Ramos, F.; Ruiz-Altisent, M.: "Effect of orientation on the fruit on-line size determination performed by an optical ring sensor" Journal of Food Engineering, Vol. 81 no 2 (2007), pp. 388–398.
[67] Nishizu, T.; Ikeda, Y.; Torikata, Y.; Manmoto, S.; Umehara, T.; Mizukami, T.: "Automatic, continuous food volume measurement with a Helmholtz resonator" International Commission of Agricultural Engineering (CIGR, Commission Internationale du Genie Rural) E-Journal Volume 3 (2001):
[68] Kato, K.: "Electrical density sorting and estimation of soluble solids content of watermelon" Journal of Agricultural Engineering Research, Vol. 67 no 2 (1997), pp. 161–170.
[69] Hwamoto, M; Chuma, Y., 1982: Recent studies on development in automated citrus packinghouse facility in Japan. Proceedings of the International Society of Citriculture International Citrus Congress November 9-12, Tokyo, Japan.
[70] Hahn, F.: "PH—Postharvest Technology: Automatic Jalapeño Chilli Grading by Width" Biosystems Engineering, Vol. 83 no 4 (2002), pp. 433–440.
[71] Blasco, J.; Aleixos, N.; Moltó, E.: "Machine vision system for automatic quality grading of fruit" Biosystems Engineering, Vol. 85 no 4 (2003), pp. 415–423.
[72] Afrisal, H.; Faris, M.; Utomo, P.; Grezelda, L.; Soesanti, I.; Andri, F.; others: Portable smart sorting and grading machine for fruits using computer vision. Computer, Control, Informatics and Its Applications (IC3INA), 2013 International Conference on], pp. 71–75.
[73] Zhang, B.; Huang, W.; Li, J.; Zhao, C.; Fan, S.; Wu, J.; Liu, C.: "Principles, developments and applications of computer vision for external quality inspection of fruits and vegetables: A review" Food Research International, Vol. 62 no (2014), pp. 326–343.
[74] Ninomiya, K.; Kondo, N.; Chong, V.; Monta, M.: Machine vision systems of eggplant grading system. (Automation Technology for Off-Road Equipment, Proceedings of the 7-8 October 2004 Conference, Kyoto, Japan).
[75] Brosnan, T.; Sun, D.-W.: "Improving quality inspection of food products by computer vision--a review" Journal of Food Engineering, Vol. 61 no 1 (2004), pp. 3–16.
[76] Vaidya, A.; Pujari, D.; Desai, H.; Borse, K.; Patel, S.: "Leaf Recognition-A Technical Review" International Journal for Research in Emerging Science and Technology, Vol. 2 n.º 1 (2015).
[77] Ji, B.; Zhu, W.; Liu, B.; Ma, C.; Li, X.: Review of recent machine-vision technologies in agriculture. (Second International Symposium on Knowledge Acquisition and Modeling, 2009. KAM’09), pp. 330–334.
[78] Dang, H.; Song, J.; Guo, Q.: A Fruit Size Detecting and Grading System Based on Image Processing. (2010 2nd International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)), pp. 83–86.
[79] Studman, C.: "Computers and electronics in postharvest technology—a review" Computers and Electronics in Agriculture, Vol. 30 no 1 (2001), pp. 109–124.
[80] Mustafa, N.; Gandi, S.; Sharrif, Z.; Ahmed, S.: Real-time implementation of a fuzzy inference system for banana grading using DSP TMS320C6713 platform. (2010 IEEE Student Conference on Research and Development (SCOReD)), pp. 324–328.
[81] Wulfsohn, D.; Gundersen, H. J. G.; Vedel Jensen, E. B.; Nyengaard, J. R.: "Volume estimation from projections." Journal of Microscopy, Vol. 215 no Pt 2 (2004), pp. 111–20.
[82] Menguito, B. P.; Nagata, M.; Qixin, C.; others: "Study on sorting system for strawberry using machine vision" Journal of JSAM, Vol. 62 no 1 (2000), pp. 100–110.
[83] Nagata, M.; Cao, Q.; Bato, P.; Shrestha, B.; Kinoshita, O.: Basic study on strawberry sorting system in Japan. 1997 ASAE Annual International Meeting Technical Papers], pp. 49085–9659.
[84] Garcia-Ramos, F.J.; Valero, C.; Homer, I.; Ortiz-Cañavate, J.; Ruiz-Altisent, M.: "Non-destructive fruit firmness sensors: a review" Spanish Journal of Agricultural Research, Vol. 3 no 1 (2005), pp. 61–73.
[85] Lorente, D.; Aleixos, N.; Gómez-Sanchis, J.; Cubero, S.; Garc’\ia-Navarrete, O. L.; Blasco, J.: "Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment" Food and Bioprocess Technology, Vol. 5 no 4 (2012), pp. 1121–1142.
[86] Burger, J.: Hyperspectral NIR image analysis. Ph. D. thesis, pub. epsilon. slu. se, Umeå, Sweden.
[87] Aleixos, N.; Blasco, J.; Navarrón, F.; Moltó, E.: "Multispectral inspection of citrus in real-time using machine vision and digital signal processors" Computers and Electronics in Agriculture, Vol. 33 no 2 (2002), pp. 121–137.
[88] Blasco, J.; Aleixos, N.; Gómez-Sanchis, J.; Moltó, E.: "Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features" Biosystems Engineering, Vol. 103 no 2 (2009), pp. 137–145.
[89] Lathuiliere, A.; Mansouri, A.; Voisin, Y.; Marzani, F.; Gouton, P.: "Stereoscopic system for 3D reconstruction using multispectral camera and LCD projector" The Imaging Science Journal, Vol. 54 no 1 (2006), pp. 19–28.
[90] Wang, N.-N.; Sun, D.-W.; Yang, Y.-C.; Pu, H.; Zhu, Z.: "Recent Advances in the Application of Hyperspectral Imaging for Evaluating Fruit Quality" Food Analytical Methods, no (2015), pp. 1–14.
[91] Povey, M. J.: "Ultrasonics of food" Contemporary Physics, Vol. 39 no 6 (1998), pp. 467–478.
[92] Povey, M.: "Ultrasonics in food engineering Part II: Applications" Journal of Food Engineering, Vol. 9 no 1 (1989), pp. 1–20.
[93] Povey, M.; McClements, D.: "Ultrasonics in food engineering. Part I: Introduction and experimental methods" Journal of Food Engineering, Vol. 8 no 4 (1988), pp. 217–245.
[94] Mizrach, A.: "Ultrasonic technology for quality evaluation of fresh fruit and vegetables in pre-and postharvest processes" Postharvest Biology and Technology, Vol. 48 no 3 (2008), pp. 315–330.
[95] Morrison, D.; Abeyratne, U.: "Ultrasonic technique for non-destructive quality evaluation of oranges" Journal of Food Engineering, Vol. 141 no (2014), pp. 107–112.
[96] Lee, S.; Cho, B.-K.: Evaluation of the firmness measurement of fruit by using a non-contact ultrasonic technique. (2013 8th IEEE Conference on Industrial Electronics and Applications (ICIEA)), pp. 1331–1336.
[97] Patel, K. K.; Khan, M. A.; Kar, A.: "Recent developments in applications of MRI techniques for foods and agricultural produce—an overview" Journal of Food Science and Technology, Vol. 52 no 1 (2015), pp. 1–26.
[98] Nicolai, B. M.; Beullens, K.; Bobelyn, E.; Peirs, A.; Saeys, W.; Theron, K. I.; Lammertyn, J.: "Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review" Postharvest Biology and Technology, Vol. 46 no 2 (2007), pp. 99–118.
[99] Walsh, K. B.: "Commercial adoption of technologies for fruit grading, with emphasis on NIRS" Information and technology for sustainable fruit and vegetable production, Frutic, Vol. 5 no (2005).
[100] Ma, Y.; Wang, Q.; Wang, X.; Wang, H.: Research of pesticide residues on fruit by terahertz spectroscopy technology.
[International Conference on Optical Instruments and Technology (OIT2011)], pp. 820125–820125.