https://doi.org/10.4081/jae.2020.1098
Non-destructive method for monitoring tomato ripening based on chlorophyll fluorescence induction
Published: 10 November 2020
Abstract Views: 2947
PDF: 1061
HTML: 306
HTML: 306
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Maturity is one of the most important factors in the assessment of tomato quality. The aim of this study is to develop a new device to measure the degree of tomato ripeness based on chlorophyll fluorescence. The results of this method in terms of chlorophyll fluorescence were compared with those from the most widely used colorimeter. The botanical variety of tomatoes ‘Alkazar’ was used at different stages of maturity: green, breakers, turning, pink, light red, and red. The results indicated that specific parameters of slow induction of chlorophyll fluorescence, such as maximum chlorophyll fluorescence (Fm) and the coefficient of specific photosynthetic activity (Rfd), can be used to classify tomatoes according to their maturity stage as efficiently as with the hue angle parameter of color measurements. The correlation coefficient between the hue angle and the slow induction of chlorophyll fluorescence parameters was 0.96 with Fm, and 0.97 with Rfd. Using the hue angle or Fm, tomatoes of all six-maturity stages were accurately classified. In conclusion, this new measurement method is a nondestructive, innovative and convenient approach, which is less time-consuming than the colour-based method.
Agati G., D’Onofrio C., Ducci E., Cuzzola A., Remorini D., Tuccio L. 2013. Potential of a multiparametric optical sensor for determining in situ the maturity components of red and white Vitis vinifera wine grapes. J. Agric. Food Chem. 61:12211-8.
DOI: https://doi.org/10.1021/jf405099n
Arias R., Lee T.C., Logendra L., Janes H. 2000. Correlation of lycopene measured by HPLC with the L*, a*, b* color readings of a hydroponic tomato and the relationship of maturity with color and lycopene content. J. Agric. Food Chem. 48:1697-702.
DOI: https://doi.org/10.1021/jf990974e
Betemps D.L., Fachinello J.C., Galarça S.P., Portela N.M., Remorini D., Massai R. 2012. Nonâ€destructive evaluation of ripening and quality traits in apples using a multiparametric fluorescence sensor. J. Sci. Food Agric. 92:1855-64.
DOI: https://doi.org/10.1002/jsfa.5552
Bramley P.M. 2002. Regulation of carotenoid formation during tomato fruit ripening and development. J. Exper. Botany. 53:2107-13.
DOI: https://doi.org/10.1093/jxb/erf059
Cerovic Z.G., Goutouly J.-P., Hilbert G., Destrac-Irvine A., Martinon V., Moise N. 2009. Mapping winegrape quality attributes using portable fluorescence-based sensors. Frutic. 9:301-10.
Chang C.-H., Lin H.-Y., Chang C.-Y., Liu Y.-C. 2006. Comparisons on the antioxidant properties of fresh, freeze-dried and hot-air-dried tomatoes. J. Food Engine. 77:478-85.
DOI: https://doi.org/10.1016/j.jfoodeng.2005.06.061
Choi K., Lee G., Han Y., Bunn J. 1995. Tomato maturity evaluation using color image analysis. Trans. ASAE. 38:171-6.
DOI: https://doi.org/10.13031/2013.27827
DeEll J.R., Toivonen P.M.A. 2003. Use of chlorophyll fluorescence in postharvest quality assessments of fruits and vegetables. pp 203-242 in: J.R. DeEll, P.M.A. Toivonen (Eds.), Practical applications of chlorophyll fluorescence in plant biology. Springer, Boston, MA, USA.
DOI: https://doi.org/10.1007/978-1-4615-0415-3_7
Gedamu A.G. 2008. Non-destructive (laser induced chlorophyll fluorescence) technique for determining tissue integrity in tomato (Lycopersicon esculentum Mill.). Degree Diss., Universiteit Gent.
Geyer L.H., Perry R.F. 1982. Variation in detectability of multiple flaws with allowed inspection time. Human Factors. 24:361-5.
DOI: https://doi.org/10.1177/001872088202400311
Ghozlen N.B., Cerovic Z.G., Germain C., Toutain S., Latouche G. 2010. Non-destructive optical monitoring of grape maturation by proximal sensing. Sensors. 10:10040-68.
DOI: https://doi.org/10.3390/s101110040
Gould W.V. 1992. Tomato production, processing, and technology (1st ed.): CTI Publications, Baltimore, MD, USA.
DOI: https://doi.org/10.1533/9781845696146
Grass J. 1991. Pigments in vegetables: chlorophylls and carotenoids. Van Nostrand Reinhold: AVI books, New York, NY, USA.
Greer D.H. 2005. Nonâ€destructive chlorophyll fluorescence and colour measurements of ‘Braeburn’and ‘Royal Gala’apple (Malus domestica) fruit development throughout the growing season. N. Zeal. J. Crop Hortic. Sci. 33:413-21.
DOI: https://doi.org/10.1080/01140671.2005.9514378
Hobson G., Grierson D. 1993. Tomato. pp 405-442 in Biochemistry of fruit ripening. Springer-Chapman and Hall, London, UK.
DOI: https://doi.org/10.1007/978-94-011-1584-1_14
Hoffmann A.M., Noga G., Hunsche M. 2015. Fluorescence indices for monitoring the ripening of tomatoes in pre-and postharvest phases. Sci. Hortic. 191:74-81.
DOI: https://doi.org/10.1016/j.scienta.2015.05.001
Huybrechts C., Deckers T., Valcke R. 2002. Predicting fruit quality and maturity of apples by fluorescence imaging: effect of ethylene and AVG. pp 243-247 in International Conference: Postharvest Unlimited, 599.
Kim D.S., Choi J.H., Kim S., Lim J.H. 2019. Prediction of carotenoid content in tomato fruit using a fluorescence screening method. Postharv. Biol. Technol. 156:110917.
DOI: https://doi.org/10.1016/j.postharvbio.2019.05.018
Kim D.S., Na H., Kwack Y., Chun C. 2014. Secondary metabolite profiling in various parts of tomato plants. Korean J. Hortic. Sci. 32:252-60.
DOI: https://doi.org/10.7235/hort.2014.13165
Lai A., Santangelo E., Soressi G., Fantoni R. 2007. Analysis of the main secondary metabolites produced in tomato (Lycopersicon esculentum, Mill.) epicarp tissue during fruit ripening using fluorescence techniques. Postharv. Biol. Technol. 43:335-42.
Lambers H.F.C. III, Pons T. 2008. Plant physiological ecology. 2nd ed. Springer, New York, NY, USA.
DOI: https://doi.org/10.1007/978-0-387-78341-3
Lechaudel M., Urban L., Joas J. 2010. Chlorophyll fluorescence, a nondestructive method to assess maturity of mango fruits (Cv. ‘Cogshall’) without growth conditions bias. J. Agric. Food Chem. 58:7532-8.
Lichtenthaler H., Buschmann C., Knapp M. 2005. How to correctly determine the different chlorophyll fluorescence parameters and the chlorophyll fluorescence decrease ratio RFd of leaves with the PAM fluorometer. Photosynthetica. 43:379-93.
DOI: https://doi.org/10.1007/s11099-005-0062-6
López Camelo A.F., Gómez P.A. 2004. Comparison of color indexes for tomato ripening. Hortic. Brasil. 22:534-7.
DOI: https://doi.org/10.1590/S0102-05362004000300006
Lu H., Lou H., Zheng H., Hu Y., Li Y. 2012. Nondestructive evaluation of quality changes and the optimum time for harvesting during jujube (Zizyphus jujuba Mill. cv. Changhong) fruits development. Food Bioproc. Technol. 5:2586-95.
DOI: https://doi.org/10.1007/s11947-011-0640-5
Pathare P.B., Opara U.L., Al-Said F.A.-J. 2013. Colour measurement and analysis in fresh and processed foods: a review. Food Bioproc. Technol. 6:36-60.
DOI: https://doi.org/10.1007/s11947-012-0867-9
Pék Z., Helyes L., Lugasi A. 2010. Color changes and antioxidant content of vine and postharvest-ripened tomato fruits. HortSci. 45:466-8.
DOI: https://doi.org/10.21273/HORTSCI.45.3.466
Saad A.M., Ibrahim A., El-Bialee N. 2016. Internal quality assessment of tomato fruits using image color analysis. Agric. Engine. Int. CIGR J. 18:339-52.
Seifert B., Pflanz M., Zude M. 2014. Spectral shift as advanced index for fruit chlorophyll breakdown. Food Bioproc. Technol. 7:2050-9.
DOI: https://doi.org/10.1007/s11947-013-1218-1
Smillie R. 1987. Application of chlorophyll fluorescence to the postharvest physiology and storage of mango and banana fruit and the chilling tolerance of mango cultivars. Asian Food J. 3:55-9.
Thimann K. 1980. Senescence in plants. CRC Press, Boca Raton, FL, USA.
Toivonen P.M.A. 1992. Chlorophyll fluorescence as a nondestructive indicator of freshness in harvested broccoli. Hort. Sci. 27:1014-5.
USDA. 1991. Visual Aid TM-L-I. The John Henry Co., Lansing, MI, USA.
How to Cite
Abdelhamid, M. A. . (2020) “Non-destructive method for monitoring tomato ripening based on chlorophyll fluorescence induction”, Journal of Agricultural Engineering, 52(1). doi: 10.4081/jae.2020.1098.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Luhua Han, Haorui Ma, Menghan Mo, Francis Kumi, Jianping Hu, Hanping Mao, Design and test of an efficient seedling pick-up device with a combination of air jet ejection and mechanical action , Journal of Agricultural Engineering: Vol. 55 No. 3 (2024)
- Andrea De Montis, Simone Caschili, Amedeo Ganciu, Antonio Ledda, Filippo Paoli, Federico Puddu, Mario Barra, Strategic environmental assessment implementation of transport and mobility plans. The case of Italian regions and provinces , Journal of Agricultural Engineering: Vol. 47 No. 2 (2016)
- So Ishizaki, Hironori Hirai, Takayasu Sakagaito, Tomohiro Takeyama, Naoyuki Oido, Tokuo Tamura, Mikio Mizutani, Yoshiki Watanabe, Mikio Umeda, Development of a transplanter-based transplanter for vegetable seedlings cultured in a cuttable nursery mat , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
- Pietro Picuno, Vernacular farm buildings in landscape planning: a typological analysis in a southern Italian region , Journal of Agricultural Engineering: Vol. 43 No. 3 (2012)
- Irene Diti, Daniele Torreggiani, Patrizia Tassinari, Rural landscape and cultural routes: a multicriteria spatial classification method tested on an Italian case study , Journal of Agricultural Engineering: Vol. 46 No. 1 (2015)
- Fernando Ferreira Abreu, Luiz Henrique Antunes Rodrigues, Monitoring mini-tomatoes growth: A non-destructive machine vision-based alternative , Journal of Agricultural Engineering: Vol. 53 No. 3 (2022)
- Qazeem Opeyemi Ogunlowo, Wook Ho Na, Anis Rabiu, Misbaudeen Aderemi Adesanya, Timothy Denen Akpenpuun, Hyeon Tae Kim, Hyun Woo Lee, Effect of envelope characteristics on the accuracy of discretised greenhouse model in TRNSYS , Journal of Agricultural Engineering: Vol. 53 No. 3 (2022)
- Melis Inalpulat, Monitoring and multi-scenario simulation of agricultural land changes using Landsat imageries and future land use simulation model on coastal of Alanya , Journal of Agricultural Engineering: Vol. 55 No. 1 (2024)
- Carlo Bibbiani, Patrizio Biagini, Federica Salari, Mina Martini, Dairy donkey: an alternative building layout , Journal of Agricultural Engineering: Vol. 48 No. s1 (2017): Special Issue
- Xiaoqiang Du, Tengfei Shen, Kaizhan Chen, Guofeng Zhang, Xiaohua Yao, Juanjuan Chen, Yongqing Cao, Simulation study and field experiments on the optimal canopy shaking action for harvesting Camellia oleifera fruits , Journal of Agricultural Engineering: Vol. 53 No. 3 (2022)
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.
