Scientia Agricultura Sinica ›› 2016, Vol. 49 ›› Issue (1): 132-141.doi: 10.3864/j.issn.0578-1752.2016.01.012

• HORTICULTURE • Previous Articles     Next Articles

Establishment of Non-Destructive System for Fruit Quality Grading of ‘Bingtang’ Sweet Orange and Its Application on Packing Line

LI Na1, YANG Xing-xing1, DAI Su-ming1, LI Rong-hua1, JIANG Hang1, LUO Yue-xiong2Alessandra Gentile1,3, DENG Zi-niu1   

  1. 1College of Horticulture and Landscape, Hunan Agricultural University, Changsha 410128, China
    2Hunan Huada Agricultural Science & Technology Co. Ltd, Yongxing 423300, Hunan, China
    3Catania University, Catania 95123, Italy
  • Received:2015-05-14 Online:2016-01-01 Published:2016-01-01

Abstract: 【Objective】 The inconsistency between external appearance and the internal quality of ‘Bingtang’ sweet orange (Citrus sinensis Osbeck) fruit has significantly reduced its marketing value. The present research intended to establish the classification standard for fruit quality and the non-destructive technologies for quality analysis and quality rating of ‘Bingtang’ orange, and then to quickly sort out the online products with different total soluble solids (TSS) and acidity. 【Method】 Fruit TSS and acid content were analyzed by sampling from the main production areas with the conventional destructive methods for a long period. The correlation among the external and internal key fruit quality parameters was calculated, and then the relationship between fruit diameter vs. TSS and acid content was determined. A standard for fruit quality classification of ‘Bingtang’ sweet orange was established. Based on the standard, the NIR transmission spectrum at 710-960 nm was utilized for fruit quality analyses, and repeated correction and verification were performed in comparison with the conventional quality analysis data to evaluate the accuracy in non-destructive fruit quality analysis and sorting. This non-destructive system was run on packing line, and the rating products were investigated in the market including the quantity, price and sold volume of different classes of ‘Bingtang’ sweet oranges. 【Result】 (1) Classification standard of ‘Bingtang’ sweet orange was established. Fruit size classification was set up based on fruit diameters: large 68-74 mm, medium 62-67 mm, and small 56-61 mm. And fruits were further classified into 4 classes based on the TSS and acid content, i.e. Super class: Birx≥14 and acidity≤0.4%, Class I: 12≤Birx<14 and acidity≤0.4%, Class II: Birx ≥14 and 0.6%≥acidity>0.4%, and Marketable class: Birx<12 and acidity≤0.4%. (2) Following repeated analyses of single fruits, non-destructive analytical standards for TSS and acidity were formulated. In the 1st TSS testing experimentation, the testing range was set up between 10.1-14.9 Brix and resulted in only 26% of conformity between the non-destructive and the conventional quality analyses; when the TSS testing range extended to 10.1-16.2 Brix in the 2nd experimentation, 90% of conformity was obtained; when the TSS lowered to 9.8 Brix (testing range of 9.8-16.2 Brix) in the 3rd TSS test, the conformity remained as high as 90%. For the acidity analysis, the testing range was set up between 0.1%-1.26% at first, only 64% of the conformity was obtained; when the testing range expanded to 0.1%-1.37%, up to 94% of conformity was realized; if the testing range of acidity increased further to 1.53%, the result was 92% of conformity indicating no improvement was gained. (3) The application of the technique on packing line resulted in a sorting speeds up to 10 oranges per second, and the sorted fruits had a highest price of 48 yuan per kg. On the packing ling, annual sorting output reached 4 500 tons, valuing 91.22 million yuan.【Conclusion】The results indicated that the established non-destructive system was accurate in TSS and acidity analysis and the analytical standards covered the full range of TSS and acidity contents of all the commercial fruits of ‘Bingtang’ sweet orange. The classification with the fast, high-quality and non-destructive online determination of the internal quality of ‘Bingtang’ sweet orange on a large scale combined with the grading standard of fruit size would ensure an unified internal and external quality of the products.

Key words: ‘Bingtang&rsquo, sweet orange, non-destructive, TSS, acidity, on line quality grading

[1]    吴龙国, 何建国, 贺晓光, 刘贵珊, 王伟, 王松磊, 苏伟东, 罗阳, 思振华. 高光谱图像技术在水果无损检测中的研究进展. 激光与红外, 2013(9): 990-996.
Wu L G, He J G, He X G, Liu G S, Wang W, Wang S L, Su W D, Luo Y, Si Z H. Research progress of hyperspectral imaging technology in non-destructive detection of fruit. Laser & Infrared, 2013(9): 990-996. (in Chinese)
[2]    伍佳文, 祁春节. 中国柑橘鲜果出口市场细分研究. 湖南农业科学, 2014, 16: 59-62.
Wu J W, Qi C J. Export market segmentation of China’s citrus fruit. Hunan Agricultural Sciences, 2014, 16: 59-62. (in Chinese)
[3]    陈晓明. 中国柑橘出口国际竞争力研究. 林业经济, 2015(1): 82-86.
Chen X M. The research on international competitiveness of China’s citrus export. Forestry Economics, 2015(1): 82-86. (in Chinese)
[4]    戴莹, 冯晓元, 韩平, 王蒙, 王纪华. 近红外光谱技术在果蔬农药残留检测中的应用研究进展. 食品安全质量检测学报, 2014, 5(3): 658-664.
Dai Y, Feng X Y, Han P, Wang M, Wang J H. Application of near infrared spectrum analysis technique in pesticide residues detection of fruits and vegetables. Journal of Food Safety and Quality, 2014, 5(3): 658-664. (in Chinese)
[5]    王蒙, 冯晓元. 梨果实近红外光谱无损检测技术研究进展. 食品安全质量检测学报, 2014, 5(3): 681-690.
Wang M, Feng X Y. Progress on near-infrared non-destructive testing technology of pears. Journal of Food Safety and Quality, 2014, 5(3): 681-690. (in Chinese)
[6]    傅霞萍, 应义斌. 基于LTH和H3630光谱的果蔬质量检测研究进展与展望. 农业机械学报, 2013, 44(8): 148-164.
Fu X P, Ying Y B. Application of NIR and Raman spectroscopy for quality and safety inspection of fruits and vegetables: A review. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(8): 148-164. (in Chinese)
[7]    张鹏, 李江阔, 陈绍慧. 苹果品质近红外光谱无损检测技术研究进展. 保鲜与加工, 2013, 13(3): 1-7.
Zhang P, Li J K, Chen S H. Research advances in non-destructive measurement technology of apple quality by means of near infrared spectroscopy. Storage and Process, 2013, 13(3): 1-7. (in Chinese)
[8]    王平, 聂振朋, 罗君琴, 柯甫志, 徐建国. 无损伤检测技术在柑橘果实中的应用. 浙江柑橘, 2013, 30(4): 7-10.
Wang P, Nie Z P, Luo J Q, Ke P Z, Xu J G. Application of nondestructive determination technology in fruit quality. Zhejiang Citrus, 2013, 30(4): 7-10. (in Chinese)
[9]    王瑞庆, 徐新明, 冯建华, 张继澍. 果实品质无损伤检测研究进展. 果树学报, 2012, 29(4): 683-689.
Wang R Q, Xu X M, Fang J H, Zhang J S. An overview of nondestructive determination technology of fruit quality. Journal of Fruit Science, 2012, 29(4): 683-689. (in Chinese)
[10]   马海军. 水果品质近红外检测技术研究进展. 农业科学研究, 2011, 32(2): 72-76.
Ma H J. Progress of near infrared spectroscopy on checking fruit quality. Journal of Agricultural Sciences, 2011, 32(2): 72-76. (in Chinese)
[11]   Twomey M, Downey G, Mcnulty P.B. The potential of NIR spectroscopy for the detection of the adulteration of orange juice. Science of Food and Agriculture, 1995, 67(l): 77-84. (in Chinese)
[12]   Steuer B, Sehulz H, L?ger E. Classification and analysis of citrus oil by NIR spectroscopy. Food Chemistry, 2001, 72: 113-117. (in Chinese)
[13]   Miller W M, Zude M. Non-destructive brix sensing of Florida grapefruit and honey tangerine. Proceedings of the Florida State Horticultural Society, 2002, 115: 56-60.
[14]   薛龙, 黎静, 刘木华, 王晓, 罗春生. 基于遗传算法的脐橙可溶性固形物的可见/近红外光谱无损检测. 激光与光电子学进展, 2010, 47(12): 123001. doi: 10.3788/LOP47.123001.
Xue L, Li J, Liu M H, Wang X, Luo C S. Nondestructive detection of soluble solids content on Navel orange with vis/nir based on genetic algorithm. Laser & Optoelectronics Progress, 2010, 47(12): 123001. doi: 10.3788/LOP47.123001. (in Chinese)
[15]   曹乐平, 温芝元, 陈理渊. 基于统计纹理的柑橘糖度与有效酸度检测. 测试技术学报, 2009, 23(1): 63-67.
Cao L P, Wen Z Y, Chen L Y. Determination of sugar content and valid acidity of citrus fruit based on statistics texture. Journal of Test and Measurement Technology, 2009, 23(1): 63-67. (in Chinese)
[16]   胡桂仙, Antihus H G, 王俊, 王小骊. 电子鼻无损检测柑橘成熟度的试验研究. 食品与发酵工业, 2005, 31(8): 57-61.
Hu G X, Antihus H G, Wang J, Wang X L. A research on monitoring the orange maturity with the electronic nose. Food and Fermentation Industries, 2005, 31(8): 57-61. (in Chinese)
[17]   郭恩有, 刘木华, 赵杰文, 陈全胜. 脐橙糖度的高光谱图像无损检测技术. 农业机械学报, 2008, 39(5): 91-93.
Guo E Y, Liu M H, Zhao J W, Chen Q S. Nondestructive detection of sugar content on navel orange with hyperspectral imaging. Transactions of the Chinese Society for Agricultural Machinery, 2008, 39(5): 91-93. ( in Chinese)
[18]   Guthrie J A, Reid D J, Walsh K B. Assessment of internal quality attributes of mandarin fruit.2. NIR calibration model rubushness. Australian Journal of Agriculture Research, 2005, 56(4): 417-426.
[19]   孙梅, 付妍, 徐冉冉, 赵勇, 陈兴海. 基于高光谱成像技术的水果品质无损检测. 食品科学技术学报, 2013, 31(2): 67-71.
Sun M, Fu Y, Xu R R, Zhao Y, Chen X H. Nondestructive inspect of fruit quality with hyperspectral imaging technology. Journal of Food Science and Technology, 2013, 31(2): 67-71. (in Chinese)
[20]   孙通, 应义斌, 刘魁武, 胡雷秀. 梨可溶性固形物含量的在线近红外光谱检测. 光谱学与光谱分析, 2008, 28(11): 2536-2539.
Sun T, Ying Y B, Liu K W, Hu L X. Online detection of soluble solids content of pear by near infrared transmission spectrum. Spectroscopy and Spectral Analysis, 2008, 28(11): 2536-2539. (in Chinese)
[21]   苏东林, 李高阳, 何建新, 张菊华, 刘伟, 朱向荣, 单杨. 近红外光谱分析技术在我国大宗水果品质无损检测中的应用研究进展. 食品工业科技, 2012, 6: 460-464.
Su D L, Li G Y, He J X, Zhang J H, Liu W, Zhu X R, Shan Y. Progress in application of near infrared spectroscopy to nondestructive detection of big yield fruits’ quality in China. Science and Technology of Food Industry, 2012, 6: 460-464. (in Chinese)
[22]   夏俊芳, 李小昱, 李培武, 王为, 丁小霞. 小波变换在脐橙维生素C含量近红外光谱预测中的应用. 中国农业科学, 2007, 40(8): 1760-1766.
Xia J F, Li X Y, Li P W, Wang W, Ding X X. Application of wavelet transformation in umbilical orange Vitamin C content prediction with near-infrared spectroscopy. Scientia Agricultura Sinica, 2007, 40(8): 1760-1766. (in Chinese)
[23]   Cayuela J A, Weiland C. Intact orange quality prediction with two portable NIR spectrometers. Postharvest Biology and Technology, 2010, 58(2): 113-120.
[24]   Gómez A H, He Y, Pereira A G. Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques. Journal of Food Engineering, 2006, 77(2): 313-319.
[25]   Liu Y, Sun X, Ouyang A. Nondestructive measurement of soluble solid content of navel orange fruit by visible-NIR spectrometric technique with PLSR and PCA-BPNN. Food Science and Technology, 2010, 43(4): 602-607.
[26]   Antonucci F, Pallottino F, Paglia G, Palma A, D’Aquino S, Menesatti P. Non-destructive estimation of mandarin maturity status through portable IS-NIR spectrophotometer. Food Bioprocess Technology, 2011, 4: 809-813.
[27]   Olmo M, Nadas A, García J M. Nondestructive methods to evaluate maturity level of oranges. Journal of Food Science, 2000, 65(2): 365-369.
[28]   石健泉, 沈丽娟, 卢美玲, 蒋运宁. 甜橙品种果实糖、酸含量的分级标准与风味的关系. 广西柑桔, 1995, 3: 3-7.
Shi J Q, Shen L J, Lu M L, Jiang Y N. Sugar and acid content of content of sweet orange and its classification standard associated with flavor in different apple cultivars. Southern Horticulture,1995, 3: 3-7. (in Chinese)
[29]   高海生. 果实品质无损伤检测与自动分级技术的研究进展. 河北科技师范学院学报, 2014, 28(1): 5-10.
Gao H S. Advances in studies on non-destructive detection and automatic grading of fruits. Journal of Hebei Normal University of Science & Technology, 2014, 28(1): 5-10. (in Chinese)
[30]   胡晓男, 彭云发, 罗雪宁, 罗华平. 果品质量近红外光谱检测技术应用与研究进展. 农业工程, 2014, 4(5): 53-58.
Hu X N, Peng Y F, Luo X N, Luo H P. Application and progress of near infrared spectroscopy technique for measurement on fruit qualities. Agricultural Engineering, 2014, 4(5): 53-58. (in Chinese)
[31]   毛莎莎, 曾明, 何绍兰, 郑永强, 易时来, 邓烈. 近红外光谱技术在水果成熟期预测中的应用. 亚热带植物科学, 2010, 39(1): 82-87.
Mao S S, Zeng M, He S L, Zheng Y Q, Yi S L, Deng L. Application of Near Infrared Spectra (NIRS) technology in prediction of maturity stage of fruit. Subtropical Plant Science, 2010, 39(1): 82-87. (in Chinese)
[32]   褚小立, 陆婉珍. 近五年我国近红外光谱分析技术研究与应用进展. 光谱学与光谱分析, 2014, 34(10): 2596-2605.
Chu X L, Lu W Z. Research and application progress of near infrared spectroscopy analytical technology in China in the past five years. Spectroscopy and Spectral Analysis, 2014, 34(10): 2596-2605. (in Chinese)
[33]   谢丽娟, 应义斌, 王爱臣, 介邓飞, 饶秀勤. 基于可见/近红外的水果品质快速无损在线检测系统: 中国专利 CN102928357A. 2013.02.13.
Xie L J, Ying Y B, Wang A C, Jie D F, Rao X Q. Non-destructive and fast detection of fruit quality based on Vis/NIR: Chinese Patent CN102928357A. 2013.02.13. (in Chinese)
[1] YAN ZhiHao,HU ZhiHua,WANG ShiChao,HUAI ShengChang,WU HongLiang,WANG JinYu,XING TingTing,YU XiChu,LI DaMing,LU ChangAi. Effects of Lime Content on Soil Acidity, Soil Nutrients and Crop Growth in Rice-Rape Rotation System [J]. Scientia Agricultura Sinica, 2019, 52(23): 4285-4295.
[2] HU Min, XIANG Yong-sheng, LU Jian-wei. Effects of Lime Application Rates on Soil Acidity and Barley Seeding Growth in Acidic Soils [J]. Scientia Agricultura Sinica, 2016, 49(20): 3896-3903.
[3] LI Fang, DENG Zi-niu, ZHAO Ya, LI Da-zhi, DAI Su-ming. Construction and Transformation of RNAi Vector for Citrus tristeza virus Gene p23 [J]. Scientia Agricultura Sinica, 2016, 49(20): 3927-3933.
[4] GE Hong-juan, LONG Gui-you, DAI Su-ming, LI Da-zhi, LI Na, DENG Zi-niu. The Influence of ‘Bingtang’ Sweet Orange or Citron C-05 on the Growth Characteristics of Xanthomonas axonopodis pv. citri [J]. Scientia Agricultura Sinica, 2015, 48(7): 1383-1391.
[5] ZHAO Kai-li, CAI Ze-jiang, WANG Bo-ren, WEN Shi-lin, ZHOU Xiao-yang, SUN Nan. Changes in pH and Exchangeable Acidity at Depths of Red Soils Derived from 4 Parent Materials Under 3 Vegetations [J]. Scientia Agricultura Sinica, 2015, 48(23): 4818-4826.
[6] TU Yan;QIU Guo-liang; ZHOU Yi; YUN Qiang; QI Dong; WANG Jia-jie; DIAO Qi-yu. The Regulation of pH Value of Liquid Feed on Blood Gas Parameters in Holstein Bull Calves [J]. Scientia Agricultura Sinica, 2014, 47(17): 3465-3474.
[7] ZHENG Yong-Qiang, LIU Yan-Mei, HE Shao-Lan, YI Shi-Lai, DENG Lie, ZHOU Zhi-Qin, JIAN Shui-Xian, LI Song-Wei. Analysis of the Specificity of Rootstock and Scion Combinations of ‘Hamlin’ Sweet Orange Related to Fruit Oleocellosis by FTIR [J]. Scientia Agricultura Sinica, 2012, 45(19): 4032-4039.
[8] ZHENG Yong-qiang,DENG Lie,HE Shao-lan,ZHOU Zhi-qin,YI Shi-lai,ZHAO Xu-yang ,WANG Liang
. Screening for the Agronomic Traits Regulating Fruit Oleocellosis with the Specificity Between Rootstocks and Scions of ‘Hamlin’ Sweet Orange
[J]. Scientia Agricultura Sinica, 2010, 43(23): 4877-4885 .
[9] .

Identification of Type III Secration System in Erwinia amylovora and Analyse of HrpA in Erwinia spp.

[J]. Scientia Agricultura Sinica, 2009, 42(2): 505-510 .
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!