review-article

Research directions in technology development to support real-time decisions of fresh produce logistics: : A review and research agenda

Authors:

J. René Villalobos,

Wladimir E. Soto-Silva,

Marcela C. González-Araya,

Rosa G. González–RamirezAuthors Info & Claims

Volume 167, Issue C

https://doi.org/10.1016/j.compag.2019.105092

Published: 01 December 2019 Publication History

Highlights

•

Recent developments in information technology are impacting the agri-food supply chains.

•

To take full advantage of the new technologies decision support systems need to be developed.

•

Decision support tools help improve efficiency and minimize waste in the supply chain.

•

The state of the art of the field and a research/application agenda is presented.

Abstract

Recent developments in consumption patterns, lowering of trade barriers, the emergence of low cost/miniature sensors and information technologies, and advanced business analytics tools are changing the playing field on which most of the agri-food supply chains operate. The intelligent use of sensing and information technologies has the potential to start a new food revolution in which limited resources such as water, capital, transportation capacity and labor could be optimally exploited so that fresh food, in particular fruits and vegetables, get to the consumer with minimal or no food waste. One of the keys for making this vision a reality is transforming the data collected as these products traverse the supply chain into effective and efficient supply chain decisions. This transformation relies on that the underlying decision systems that take advantage of this data exist or can be developed. The aim of this paper is to provide an overview of the state of the art and challenges and opportunities emerging from the integration of sensing data and information into decision support systems for supply chain of fresh fruits and vegetables.

References

[1]

E. Abad, F. Palacio, M. Nuin, A.G. de Zárate, A. Juarros, J.M. Gómez, S. Marco, RFID smart tag for traceability and cold chain monitoring of foods: Demonstration in an intercontinental fresh fish logistic chain, J. Food Eng. 93 (2009) 394–399,.

[2]

L. Afifa, T. Priyambodo, Review on internet of things, Int. J. Res. Appl. 3 (2016) 397–401.

[3]

O. Ahumada, J.R. Villalobos, A.N. Mason, Tactical planning of the production and distribution of fresh agricultural products under uncertainty, Agric. Syst. 112 (2012) 17–26,.

[4]

O. Ahumada, J.R. Villalobos, Operational model for planning the harvest and distribution of perishable agricultural products, Int. J. Prod. Econ. Towards High Perform. Manuf. 133 (2011) 677–687,.

[5]

O. Ahumada, J.R. Villalobos, Application of planning models in the agri-food supply chain: A review, Eur. J. Oper. Res. 196 (2009) 1–20,.

[6]

G. Alfian, J. Rhee, H. Ahn, J. Lee, U. Farooq, M.F. Ijaz, M.A. Syaekhoni, Integration of RFID, wireless sensor networks, and data mining in an e-pedigree food traceability system, J. Food Eng. 212 (2017) 65–75,.

[7]

C. Amador, J.-P. Emond, M.C. Nunes, N. do, Application of RFID technologies in the temperature mapping of the pineapple supply chain, Sens. Instrum. Food Qual. Saf. 3 (2009) 26–33,.

[8]

P. Amorim, H.-O. Günther, B. Almada-Lobo, Multi-objective integrated production and distribution planning of perishable products, Int. J. Prod. Econ. 138 (2012) 89–101,.

[9]

Aqeel-ur-Rehman, Abbasi, A.Z., Islam, N., Shaikh, Z.A., 2014. A review of wireless sensors and networks’ applications in agriculture. Comput. Stand. Interfaces 36, 263–270. 10.1016/j.csi.2011.03.004.

[10]

L. Atzori, A. Iera, G. Morabito, The internet of things: a survey, Comput. Netw. 54 (2010) 2787–2805,.

Digital Library

[11]

M.M. Aung, F.W. Liang, Y.S. Chang, C. Makatsoris, Juno Chang, RFID- and WSN-based intelligent cold chain management, Int. J. Manuf. Res. 6 (2011) 91–109,.

[12]

F. Avila, M. Mora, C. Fredes, A method to estimate Grape Phenolic Maturity based on seed images, Comput. Electron. Agric. 101 (2014) 76–83,.

Digital Library

[13]

R. Badia-Melis, U. Mc Carthy, I. Uysal, Data estimation methods for predicting temperatures of fruit in refrigerated containers, Biosyst. Eng. 151 (2016) 261–272,.

[14]

R. Badia-Melis, L. Ruiz-Garcia, J. Garcia-Hierro, J.I.R. Villalba, Refrigerated fruit storage monitoring combining two different wireless sensing technologies: RFID and WSN, Sensors 15 (2015) 4781–4795,.

[15]

W. Baoyun, Review on internet of things, J. Electron. Meas. Instrum. 12 (2009) 1–7.

[16]

M. Ben-Daya, E. Hassini, Z. Bahroun, Internet of things and supply chain management: a literature review, Int. J. Prod. Res. (2017) 1–24,.

[17]

Blasco, J., Munera, S., Aleixos, N., Cubero, S., Molto, E., 2017. Machine vision-based measurement systems for fruit and vegetable quality control in postharvest. In: Measurement, Modeling and Automation in Advanced Food Processing, Advances in Biochemical Engineering/Biotechnology. Springer, Cham, pp. 71–91. 10.1007/10_2016_51.

[18]

Bogataj, D., Drobne, D., 2016. In: Control of Perishable Goods in Cold Logistic Chains by Bionanosensors, Applying Nanotechnology for Environmental Sustainability. IGI Global, pp. 376–402.

[19]

F. Bibi, C. Guillaume, N. Gontard, B. Sorli, A review: RFID technology having sensing aptitudes for food industry and their contribution to tracking and monitoring of food products, Trends Food Sci. Technol. 62 (2017) 91–103,.

[20]

T. Bosona, G. Gebresenbet, Food traceability as an integral part of logistics management in food and agricultural supply chain, Food Control 33 (2013) 32–48,.

[21]

Caon, T., Martelli, S.M., Fakhouri, F.M., 2017. 18-New trends in the food industry: application of nanosensors in food packaging. In: Grumezescu, A.M. (Ed.), Nanobiosensors. Academic Press, pp. 773–804. 10.1016/B978-0-12-804301-1.00018-7.

[22]

L.P. Catalá, G.A. Durand, A.M. Blanco, J. Alberto Bandoni, Mathematical model for strategic planning optimization in the pome fruit industry, Agric. Syst. 115 (2013) 63–71,.

[23]

D.P. Cavallo, M. Cefola, B. Pace, A.F. Logrieco, G. Attolico, Non-destructive automatic quality evaluation of fresh-cut iceberg lettuce through packaging material, J. Food Eng. 223 (2018) 46–52,.

[24]

R.-Y. Chen, An intelligent value stream-based approach to collaboration of food traceability cyber physical system by fog computing, Food Control 71 (2017) 124–136,.

[25]

R.-Y. Chen, Autonomous tracing system for backward design in food supply chain, Food Control 51 (2015) 70–84,.

[26]

C. Costa, F. Antonucci, F. Pallottino, J. Aguzzi, D. Sarriá, P. Menesatti, A review on agri-food supply chain traceability by means of RFID technology, Food Bioprocess Technol. 6 (2013) 353–366,.

[27]

F. Dabbene, P. Gay, Food traceability systems: Performance evaluation and optimization, Comput. Electron. Agric. 75 (1) (2011) 139–146,.

Digital Library

[28]

F. Dabbene, P. Gay, C. Tortia, Traceability issues in food supply chain management: A review, Biosyst. Eng. Oper. Manage. Bio-prod. Syst. 120 (2014) 65–80,.

[29]

H. De Steur, J. Wesana, M.K. Dora, D. Pearce, X. Gellynck, Applying Value Stream Mapping to reduce food losses and wastes in supply chains: A systematic review, Waste Manage. 58 (2016) 359–368,.

[30]

T. Defraeye, B. Nicolai, W. Kirkman, S. Moore, S. van Niekerk, P. Verboven, P. Cronjé, Integral performance evaluation of the fresh-produce cold chain: A case study for ambient loading of citrus in refrigerated containers, Postharvest Biol. Technol. 112 (2016) 1–13,.

[31]

T. Defraeye, W. Wu, K. Prawiranto, G. Fortunato, S. Kemp, S. Hartmann, P. Cronje, P. Verboven, B. Nicolai, Artificial fruit for monitoring the thermal history of horticultural produce in the cold chain, J. Food Eng. 215 (2017) 51–60,.

[32]

de-la-Fuente-Aragón, M.V., Ros-McDonnell, L., 2013. Designing a Web Platform for a Fruit-and-Vegetable Collaborative Network. Procedia Technol., CENTERIS 2013 - Conference on ENTERprise Information Systems / ProjMAN 2013 - International Conference on Project MANagement/ HCIST 2013 - International Conference on Health and Social Care Information Systems and Technologies 9, 247–252. 10.1016/j.protcy.2013.12.027.

[33]

S.E. Díaz, J.C. Pérez, A.C. Mateos, M.-C. Marinescu, B.B. Guerra, A novel methodology for the monitoring of the agricultural production process based on wireless sensor networks, Comput. Electron. Agric. 76 (2011) 252–265,.

Digital Library

[34]

Djatna, T., Luthfiyanti, R., 2015. An analysis and design of responsive supply chain for pineapple multi products SME Based on Digital Business Ecosystem (DBE). Procedia Manuf., Industrial Engineering and Service Science 2015, IESS 2015 4, 155–162. 10.1016/j.promfg.2015.11.026.

[35]

R. Elsheikh, A.R.B. Mohamed Shariff, F. Amiri, N.B. Ahmad, S.K. Balasundram, M.A.M. Soom, Agriculture Land Suitability Evaluator (ALSE): A decision and planning support tool for tropical and subtropical crops, Comput. Electron. Agric. 93 (2013) 98–110,.

[36]

M. Enea, L. Settanni, G.L. Scalia, R. Micale, Predictive shelf life model based on RF technology for improving the management of food supply chain: A case study, Int. J. RF Technol. Res. Appl. 7 (1) (2016) 31–42.

[37]

FAO, 2009. 2050: A third more mouths to feed [WWW Document]. URL http://www.fao.org/news/story/en/item/35571/icode/ (accessed 10.13.17).

[38]

J.-C. Ferrer, A. Mac Cawley, S. Maturana, S. Toloza, J. Vera, An optimization approach for scheduling wine grape harvest operations, Int. J. Prod. Econ. Special Section RFID: Technol., Appl., Impact Bus. Oper. 112 (2008) 985–999,.

[39]

C. Fikar, A decision support system to investigate food losses in e-grocery deliveries, Comput. Ind. Eng. 117 (2018) 282–290,.

Digital Library

[40]

Floarea, A., Sgârciu, V., 2016. Smart refrigerator: A next generation refrigerator connected to the IoT. In: 2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). Presented at the 2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), pp. 1–6. 10.1109/ECAI.2016.7861170.

[41]

H. Flores, J.R. Villalobos, A modeling framework for the strategic design of local fresh-food systems, Agric. Syst. 161 (2018) 1–15,.

[42]

H. Flores, J.R. Villalobos, Using market intelligence for the opportunistic shipping of fresh produce, Int. J. Prod. Econ. Special Issue Behav. Oper. Manage./Prod. Econ. 142 (2013) 89–97,.

[43]

H. Flores, J.R. Villalobos, O. Ahumada, M. Uchanski, C. Meneses, O. Sanchez, Use of supply chain planning tools for efficiently placing small farmers into high-value, vegetable markets, Comput. Electron. Agric. 157 (2019) 205–217,.

Digital Library

[44]

H. Flores, J.R. Villalobos, A stochastic planning framework for the discovery of complementary, agricultural systems, Eur. J. Oper. Res. 280 (2) (2020) 707–729,.

[45]

A. Fredriksson, K. Liljestrand, Capturing food logistics: a literature review and research agenda, Int. J. Logist. Res. Appl. 18 (2015) 16–34,.

[46]

C. Ganeshkumar, M. Pachayappan, G. Madanmohan, Agri-food Supply Chain Management: Literature Review, Intell. Inf. Manage. 9 (2017) 68–96.

[47]

G. Gaukler, M. Ketzenberg, V. Salin, Establishing dynamic expiration dates for perishables: An application of rfid and sensor technology, Int. J. Prod. Econ. 193 (2017) 617–632,.

[48]

R. Gautam, A. Singh, K. Karthik, S. Pandey, F. Scrimgeour, M.K. Tiwari, Traceability using RFID and its formulation for a kiwifruit supply chain, Comput. Ind. Eng. 103 (2017) 46–58,.

Digital Library

[49]

González-Araya, M.C., Soto-Silva, W.E., Espejo, L.G.A., 2015. Harvest planning in apple orchards using an optimization model. In: Handbook of Operations Research in Agriculture and the Agri-Food Industry, International Series in Operations Research & Management Science. Springer, New York, NY, pp. 79–105. 10.1007/978-1-4939-2483-7_4.

[50]

M. Grunow, S. Piramuthu, RFID in highly perishable food supply chains – Remaining shelf life to supplant expiry date?, Int. J. Prod. Econ. 146 (2013) 717–727,.

[51]

V. Guillard, P. Buche, S. Destercke, N. Tamani, M. Croitoru, L. Menut, C. Guillaume, N. Gontard, A Decision Support System to design modified atmosphere packaging for fresh produce based on a bipolar flexible querying approach, Comput. Electron. Agric. 111 (2015) 131–139,.

Digital Library

[52]

Gustavsson, J., Cederberg, C., Sonesson, U., 2011. The methodology of the FAO study: “Global Food Losses and Food Waste - extent, causes and prevention”. FAO SIK Institutet För Livsmed. Och Biotek. 70.

[53]

R. Haass, P. Dittmer, M. Veigt, M. Lütjen, Reducing food losses and carbon emission by using autonomous control – A simulation study of the intelligent container, Int. J. Prod. Econ. 164 (2015) 400–408,.

[54]

Hayes, J., Crowley, K., Diamond, D., 2005. Simultaneous Web-based real-time temperature monitoring using multiple wireless sensor networks. In: IEEE Sensors, 2005. Presented at the IEEE Sensors, 2005, pp. 4 pp.-. 10.1109/ICSENS.2005.1597691.

[55]

F.J. He, C.A. Nowson, M. Lucas, G.A. MacGregor, Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: meta-analysis of cohort studies, J. Hum. Hypertens. 21 (2007) 717–728,.

[56]

F.J. He, C.A. Nowson, G.A. MacGregor, Fruit and vegetable consumption and stroke: meta-analysis of cohort studies, The Lancet 367 (2006) 320–326,.

[57]

J. He, J. Wang, D. He, J. Dong, Y. Wang, The design and implementation of an integrated optimal fertilization decision support system, Math. Comput. Model. 54 (2011) 1167–1174,.

Digital Library

[58]

W. He-Quan, Review on Internet of Things: application and challenges, J. Chongqing Univ. Posts Telecommun. 5 (2010).

[59]

A. Herbon, A. Ceder, Monitoring perishable inventory using quality status and predicting automatic devices under various stochastic environmental scenarios, J. Food Eng. (2017),.

[60]

M.L.A.T.M. Hertog, I. Uysal, U. McCarthy, B.M. Verlinden, B.M. Nicolaï, Shelf life modelling for first-expired-first-out warehouse management, Philos. Trans. R. Soc. Lond. Math. Phys. Eng. Sci. 372 (2014) 20130306,.

[61]

Hong, G.-Z., Hsieh, C.-L., 2016. Application of integrated control strategy and bluetooth for irrigating romaine lettuce in greenhouse. In: IFAC-Pap., 5th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture AGRICONTROL 2016 49, 381–386. 10.1016/j.ifacol.2016.10.070.

[62]

C.-F. Hsueh, M.-S. Chang, A model for intelligent transportation of perishable products, Int. J. Intell. Transp. Syst. Res. 8 (2010) 36–41,.

[63]

Jedermann, R., Behrens, C., Westphal, D., Lang, W., 2006. Applying autonomous sensor systems in logistics—Combining sensor networks, RFIDs and software agents. Sens. Actuators Phys., The 19th European Conference on Solid-State Transducers 132, 370–375. 10.1016/j.sna.2006.02.008.

[64]

R. Jedermann, T. Pötsch, C. Lloyd, Communication techniques and challenges for wireless food quality monitoring, Phil. Trans. Roy. Soc. A 372 (2014) 20130304,.

[65]

R. Jedermann, L. Ruiz-Garcia, W. Lang, Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation, Comput. Electron. Agric. 65 (2009) 145–154,.

Digital Library

[66]

G. Ji, L. Hu, K.H. Tan, A study on decision-making of food supply chain based on big data, J. Syst. Sci. Syst. Eng. 26 (2017) 183–198,.

[67]

Juric, P., Brkic Bakaric, M, Wang, X., Zhang, X, Matetic, M, 2016. Mining data streams for the analysis of parameter fluctuations in IoT-aided fruit cold-chain. In: Presented at the 27th DAAAM International Symposium, DAAAM International, Vienna, Austria, pp. 756–761.

[68]

Kaushik, E., Singh, C., 2013. Monitoring and Controlling in Food Storage System using Wireless Sensor Networks Based on Zigbee & Bluetooth Modules.

[69]

T. Jimenez- Ariza, Supervisión multidistribuida para el control de procesos de conservación de productos agroalimentarios: optimización de calidad del producto. Doctoral Dissertation, Universidad Politécnica de Madrid, 2015.

[70]

Y. Kim, R.G. Evans, Software design for wireless sensor-based site-specific irrigation, Comput. Electron. Agric. 66 (2009) 159–165,.

Digital Library

[71]

Y. Kim, R.G. Evans, W.M. Iversen, Remote sensing and control of an irrigation system using a distributed wireless sensor network, IEEE Trans. Instrum. Meas. 57 (2008) 1379–1387,.

[72]

N. Kondo, Automation on fruit and vegetable grading system and food traceability, Trends Food Sci. Technol. Adv. Food Process. Packaging Automat. 21 (2010) 145–152,.

[73]

G. La Scalia, L. Settanni, R. Micale, M. Enea, Predictive shelf life model based on RF technology for improving the management of food supply chain: A case study, Int. J. RF Technol. 7 (2016) 31–42,.

[74]

D. Lamb, w. Weedon, M.m.R.g.v. Bramley, Using remote sensing to predict grape phenolics and colour at harvest in a Cabernet Sauvignon vineyard: Timing observations against vine phenology and optimising image resolution, Aust. J. Grape Wine Res. 10 (2004) 46–54,.

[75]

W. Lang, R. Jedermann, D. Mrugala, A. Jabbari, B. Krieg-Brückner, K. Schill, The “Intelligent Container”; A Cognitive Sensor Network for Transport Management, IEEE Sens. J. 11 (2011) 688–698,.

[76]

Latini, A., Campiotti, C.A., Pietrantonio, E., Viola, C., Peral, V., Fuentes-Pila, J., Sagarna, J., 2016. Identifying Strategies for Energy Consumption Reduction and Energy Efficiency Improvement in Fruit and Vegetable Producing Cooperatives: A Case Study in the Frame of TESLA Project. Agric. Agric. Sci. Procedia, Florence “Sustainability of Well-Being International Forum”. 2015: Food for Sustainability and not just food, FlorenceSWIF2015 8, 657–663. 10.1016/j.aaspro.2016.02.088.

[77]

S.Y. Lee, S.J. Lee, D.S. Choi, S.J. Hur, Current topics in active and intelligent food packaging for preservation of fresh foods, J. Sci. Food Agric. 95 (2015) 2799–2810,.

[78]

W.S. Lee, V. Alchanatis, C. Yang, M. Hirafuji, D. Moshou, C. Li, Sensing technologies for precision specialty crop production, Comput. Electron. Agric. 74 (2010) 2–33,.

Digital Library

[79]

R.J. Lehmann, R. Reiche, G. Schiefer, Future internet and the agri-food sector: State-of-the-art in literature and research, Comput. Electron. Agric. 89 (2012) 158–174,.

Digital Library

[80]

Lu, S., Wang, X., 2016. Toward an intelligent solution for perishable food cold chain management. In: 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS). Presented at the 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS), pp. 852–856. 10.1109/ICSESS.2016.7883200.

[81]

M. Lütjen, P. Dittmer, M. Veigt, Quality driven distribution of intelligent containers in cold chain logistics networks, Prod. Eng. 7 (2013) 291–297,.

[82]

P.V. Mahajan, A. Luca, M. Edelenbos, Development of a small and flexible sensor-based respirometer for real-time determination of respiration rate, respiratory quotient and low O2 limit of fresh produce, Comput. Electron. Agric. 121 (2016) 347–353,.

Digital Library

[83]

Mahalik, N., Kim, K., 2015. The role of information technology developments in food supply chain integration and monitoring. In: Innovation and Future Trends in Food Manufacturing and Supply Chain Technologies. Woodhead Publishing, pp. 21–37.

[84]

K.A. Mane, A review on active packaging: an innovation in food packaging, Int. J. Environ. Agric. Biotechnol. 1 (3) (2016) 544–549.

[85]

S.W. Martinez, Hedonic analysis of US fresh produce prices at direct-to-consumer sales outlets versus competing retailers, Br. Food J. 118 (2016) 1665–1681,.

[86]

H.J.P. Marvin, E.M. Janssen, Y. Bouzembrak, P.J.M. Hendriksen, M. Staats, Big data in food safety: An overview, Crit. Rev. Food Sci. Nutr. 57 (2017) 2286–2295,.

[87]

A.N. Mason, J.R. Villalobos, Coordination of perishable crop production using auction mechanisms, Agric. Syst. 138 (2015) 18–30,.

[88]

S. Mejjaouli, R.F. Babiceanu, Cold supply chain logistics: System optimization for real-time rerouting transportation solutions, Comput. Ind. 95 (2018) 68–80,.

[89]

Mekala, M.S., Viswanathan, P., 2017. A novel technology for smart agriculture based on IoT with cloud computing. In: 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). Presented at the 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), pp. 75–82. 10.1109/I-SMAC.2017.8058280.

[90]

A. Meneghetti, L. Monti, Greening the food supply chain: an optimisation model for sustainable design of refrigerated automated warehouses, Int. J. Prod. Res. 53 (2015) 6567–6587,.

[91]

S. Mercier, S. Villeneuve, M. Mondor, I. Uysal, Time-temperature management along the food cold chain: a review of recent developments, Compr. Rev. Food Sci. Food Saf. 16 (2017) 647–667,.

[92]

N. Mishra, A. Singh, Use of twitter data for waste minimisation in beef supply chain, Ann. Oper. Res. 1–23 (2016),.

[93]

R. Montanari, Cold chain tracking: a managerial perspective, Trends Food Sci. Technol. Central Eur. Congr. Food - CEFood 19 (2008) 425–431,.

[94]

H. Morande, S. Maturana, Design and validation of a decision support system for oenologists, Rev. ICHIO 1 (2010) 46–58.

[95]

Musa, Z., Vidyasankar, K., 2017. A Fog Computing Framework for Blackberry Supply Chain Management. Procedia Comput. Sci., The 8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2017)/The 7th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2017)/Affiliated Workshops 113, 178–185. 10.1016/j.procs.2017.08.338.

[96]

Nadal-Roig, E., Plà-Aragonés, L.M., 2015. Optimal Transport Planning for the Supply to a Fruit Logistic Centre, in: Handbook of Operations Research in Agriculture and the Agri-Food Industry, International Series in Operations Research & Management Science. Springer, New York, NY, pp. 163–177. 10.1007/978-1-4939-2483-7_7.

[97]

H. Navarro-Hellín, J. Martínez-del-Rincon, R. Domingo-Miguel, F. Soto-Valles, R. Torres-Sánchez, A decision support system for managing irrigation in agriculture, Comput. Electron. Agric. 124 (2016) 121–131,.

Digital Library

[98]

Nukala, R., Panduru, K., Shields, A., Riordan, D., Doody, P., Walsh, J., 2016. Internet of Things: A review from ‘Farm to Fork’. In: 2016 27th Irish Signals and Systems Conference (ISSC). Presented at the 2016 27th Irish Signals and Systems Conference (ISSC), pp. 1–6. 10.1109/ISSC.2016.7528456.

[99]

A. Ogasawara, K. Yamasaki, A Temperature-Managed Traceability System Using RFID Tags with Embedded Temperature Sensors, Nec Tech. J. 1 (2006) 82–86.

[100]

L.-B. Oh, H.-H. Teo, V. Sambamurthy, The effects of retail channel integration through the use of information technologies on firm performance, J. Oper. Manage. 30 (2012) 368–381,.

Digital Library

[101]

L.U. Opara, Traceability in agriculture and food supply chain: A review of basic concepts, technological implications, and future prospects, Food Agric. Environ. 1 (2003) 101–106.

[102]

C.-M. Ou, J.-F. Tu, The WSN and 3G/NFC embedded into IoV (Internet-of-Vehicle) fulfill cold chain logistics, Microsyst. Technol. 1–7 (2017),.

Digital Library

[103]

V. Overbeck, M. Schmitz, M. Blanke, Non-destructive sensor-based prediction of maturity and optimum harvest date of sweet cherry fruit, Sensors 17 (2017) 277,.

[104]

E. Papargyropoulou, R. Lozano, J.K. Steinberger, N. Wright, Z. bin Ujang, The food waste hierarchy as a framework for the management of food surplus and food waste, J. Clean. Prod. 76 (2014) 106–115,.

[105]

Perdana, Y.R., 2012. Logistics Information System for Supply Chain of Agricultural Commodity. Procedia - Soc. Behav. Sci., International Congress on Interdisciplinary Business and Social Sciences 2012 (ICIBSoS 2012) 65, 608–613. 10.1016/j.sbspro.2012.11.172.

[106]

S.W. Rajurkar, R. Jain, Food supply chain management: review, classification and analysis of literature, Int. J. Integr. Supply Manage. 6 (2011) 33–72,.

[107]

Ramundo, L., Taisch, M., Terzi, S., 2016. State of the art of technology in the food sector value chain towards the IoT. In: 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow (RTSI). Presented at the 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI), pp. 1–6. 10.1109/RTSI.2016.7740612.

[108]

P.P. Ray, Internet of things for smart agriculture: Technologies, practices and future direction, J. Ambient Intell. Smart Environ. 9 (2017) 395–420,.

Digital Library

[109]

E. Riboli, T. Norat, Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk, Am. J. Clin. Nutr. 78 (2003) 559S–569S,.

[110]

Rouillard, J., 2012. The Pervasive Fridge. A smart computer system against uneaten food loss. In: Seventh International Conference on Systems (ICONS2012). Saint-Gilles, Réunion, pp. 135–140.

[111]

J. Ruan, Y. Shi, Monitoring and assessing fruit freshness in IOT-based e-commerce delivery using scenario analysis and interval number approaches, Inf. Sci. 373 (2016) 557–570,.

Digital Library

[112]

M. Ruiz-Altisent, L. Ruiz-García, G.P. Moreda, R. Lu, N. Hernández-Sánchez, E.C. Correa, B. Diezma, B. Nicolaï, J. García-Ramos, Sensors for product characterization and quality of specialty crops—A review, Comp. Electron. Agric. 74 (2) (2010) 176–194,.

Digital Library

[113]

L. Ruiz-Garcia, P. Barreiro, J.I. Robla, Performance of ZigBee-Based wireless sensor nodes for real-time monitoring of fruit logistics, J. Food Eng. 87 (2008) 405–415,.

[114]

L. Ruiz-Garcia, P. Barreiro, J.I. Robla, L. Lunadei, Testing ZigBee motes for monitoring refrigerated vegetable transportation under real conditions, Sensors 10 (2010) 4968–4982,.

[115]

L. Ruiz-Garcia, G. Steinberger, M. Rothmund, A model and prototype implementation for tracking and tracing agricultural batch products along the food chain, Food Control 21 (2) (2010) 112–121,.

[116]

I. Sanchez-Cohen, G. Díaz-Padilla, M. Velasquez-Valle, D.C. Slack, P. Heilman, A. Pedroza-Sandoval, A decision support system for rainfed agricultural areas of Mexico, Comput. Electron. Agric. 114 (2015) 178–188,.

Digital Library

[117]

Shan, Q., Liu, Y., Prosser, G., Brown, D., 2004. Wireless intelligent sensor networks for refrigerated vehicle. In: Proceedings of the IEEE 6th Circuits and Systems Symposium on Emerging Technologies: Frontiers of Mobile and Wireless Communication (IEEE Cat. No.04EX710). Presented at the Proceedings of the IEEE 6th Circuits and Systems Symposium on Emerging Technologies: Frontiers of Mobile and Wireless Communication (IEEE Cat. No.04EX710), pp. 525-528 Vol.2. 10.1109/CASSET.2004.1321941.

[118]

M. Shukla, S. Jharkharia, Agri-fresh produce supply chain management: a state-of-the-art literature review, Int. J. Oper. Prod. Manage. 33 (2013) 114–158,.

[119]

A. Silwal, J.R. Davidson, M. Karkee, C. Mo, Q. Zhang, K. Lewis, Design, integration, and field evaluation of a robotic apple harvester, J. Field Robot. 34 (2017) 1140–1159,.

[120]

A.K. Singh, N. Subramanian, K.S. Pawar, R. Bai, Cold chain configuration design: location-allocation decision-making using coordination, value deterioration, and big data approximation, Ann. Oper. Res. 1–25 (2016),.

[121]

A. Skic, M. Szymańska-Chargot, B. Kruk, M. Chylińska, P.M. Pieczywek, A. Kurenda, A. Zdunek, K.P. Rutkowski, Determination of the optimum harvest window for apples using the non-destructive biospeckle method, Sensors 16 (2016) 661,.

[122]

W.E. Soto-Silva, M.C. González-Araya, M.A. Oliva-Fernández, L.M. Plà-Aragonés, Optimizing fresh food logistics for processing: Application for a large Chilean apple supply chain, Comput. Electron. Agric. 136 (2017) 42–57,.

Digital Library

[123]

W.E. Soto-Silva, E. Nadal-Roig, M.C. González-Araya, L.M. Pla-Aragones, Operational research models applied to the fresh fruit supply chain, Eur. J. Oper. Res. 251 (2016) 345–355,.

[124]

W.A. Spagnol, V. Silveira Junior, E. Pereira, N. Guimarães Filho, W.A. Spagnol, V. Silveira Junior, E. Pereira, N. Guimarães Filho, Monitoring the cold chain: new technologies and recent advances, Braz. J. Food Technol. 21 (2018),.

[125]

S. Srivastava, S. Sadisatp, Development of a low cost optimized handheld embedded odor sensing system (HE-Nose) to assess ripeness of oranges, J. Food Meas. Charact. 10 (2016) 1–15,.

[126]

S. Srivastava, S. Sadistap, Non-destructive sensing methods for quality assessment of on-tree fruits: a review, J. Food Meas. Charact. 1–30 (2017),.

[127]

J.V. Stafford, Implementing Precision Agriculture in the 21st Century, J. Agric. Eng. Res. 76 (2000) 267–275,.

[128]

J.M. Talavera, L.E. Tobón, J.A. Gómez, M.A. Culman, J.M. Aranda, D.T. Parra, L.A. Quiroz, A. Hoyos, L.E. Garreta, Review of IoT applications in agro-industrial and environmental fields, Comput. Electron. Agric. 142 (2017) 283–297,.

Digital Library

[129]

Tian, F., 2016. An agri-food supply chain traceability system for China based on RFID blockchain technology. In: 2016 13th International Conference on Service Systems and Service Management (ICSSSM). Presented at the 2016 13th International Conference on Service Systems and Service Management (ICSSSM), pp. 1–6. 10.1109/ICSSSM.2016.7538424.

[130]

Toth, C., Jóźków, G., 2016. Remote sensing platforms and sensors: A survey. ISPRS J. Photogramm. Remote Sens., Theme issue “State-of-the-art in photogrammetry, remote sensing and spatial information science” 115, 22–36. 10.1016/j.isprsjprs.2015.10.004.

[131]

P. Tsang, K.L. Choy, C.H. Wu, G.T.S. Ho, H.Y. Lam, P.S. Koo, An IoT-based cargo monitoring system for enhancing operational effectiveness under a cold chain environment, Int. J. Eng. Bus. Manage. 9 (2017),. 1847979017749063.

[132]

Tsironi, T., Dermesonlouoglou, E., Giannoglou, M., Gogou, E., Katsaros, G., Taoukis, P., 2017. Shelf-life prediction models for ready-to-eat fresh cut salads: Testing in real cold chain. Int. J. Food Microbiol., Special Issue: 9th International Conference on Predictive Modelling in Food (Rio de Janeiro, Brazil) 240, 131–140. 10.1016/j.ijfoodmicro.2016.09.032.

[133]

Tzounis, A., Katsoulas, N., Bartzanas, T., Kittas, C., 2017. Internet of Things in agriculture, recent advances and future challenges. 10.1016/j.biosystemseng.2017.09.007.

[134]

Urien, P., Piramuthu, S., 2013. Internet Smart Card for perishable food cold supply chain. In: 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing. Presented at the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp. 83–88. 10.1109/ISSNIP.2013.6529769.

[135]

J.G.A.J. Van der Vorst, S.-O. Tromp, D.-J. van der Zee, Simulation modelling for food supply chain redesign; integrated decision making on product quality, sustainability and logistics, Int. J. Prod. Res. 47 (2009) 6611–6631,.

[136]

M. Vanderroost, P. Ragaert, F. Devlieghere, B. De Meulenaer, Intelligent food packaging: The next generation, Trends Food Sci. Technol. 39 (2014) 47–62,.

[137]

C.N. Verdouw, J. Wolfert, A.J.M. Beulens, A. Rialland, Virtualization of food supply chains with the internet of things, J. Food Eng. Virtualiz. Process. Food Eng. 176 (2016) 128–136,.

[138]

J. Wang, H. Wang, J. He, L. Li, M. Shen, X. Tan, H. Min, L. Zheng, Wireless sensor network for real-time perishable food supply chain management, Comput. Electron. Agric. 110 (2015) 196–207,.

Digital Library

[139]

L. Wang, S.K. Kwok, W.H. Ip, A radio frequency identification and sensor-based system for the transportation of food, J. Food Eng. 101 (2010) 120–129,.

[140]

Wu, H., Chuang, Y., 2017. Low-Cost Smart Refrigerator. In: 2017 IEEE International Conference on Edge Computing (EDGE). Presented at the 2017 IEEE International Conference on Edge Computing (EDGE), pp. 228–231. 10.1109/IEEE.EDGE.2017.41.

[141]

Wyman, O., 2018. FRUIT LOGISTICA Trend Report 2018: Disruption in Fruit and Vegetable Distribution (Februar 07, 2018) - FRUIT LOGISTICA [WWW Document]. URL https://www.fruitlogistica.de/Presse/Pressemitteilungen/News_51594.html?referrer=/de/Presse/Pressemitteilungen/ (accessed 8.5.18).

[142]

B. Xie, L. Wang, H. Yang, Y. Wang, M. Zhang, Consumer perceptions and attitudes of organic food products in Eastern China, Br. Food J. 117 (2015) 1105–1121,.

[143]

X. Yang, J. Qian, J. Li, Z. Ji, B. Fan, B. Xing, W. Li, A real-time agro-food authentication and supervision system on a novel code for improving traceability credibility, Food Control 66 (2016) 17–26,.

[144]

J. Zhang, Lichang Chen, Xiuying Tang, Quan Gao, A remote monitoring system for cold chain logistics by means of social networks, Open Cybern. Syst. J. 9 (2015) 888–893.

[145]

J. Zhang, L. Liu, W. Mu, M. Moga, L.Z. Xiaoshuan, Development of temperature-managed traceability system for frozen and chilled food during storage and transportation, J. Food Agric. Environ. 7 (2009) 28–31.

[146]

Z. Zhang, P. Heinemann, J. Liu, T. Baugher, J. Schupp, The development of mechanical apple harvesting technology: a review, Trans. ASABE 59 (2016) 1165–1180,.

[147]

Z. Zou, Q. Chen, I. Uysal, L. Zheng, Radio frequency identification enabled wireless sensing for intelligent food logistics, Phil. Trans. Roy. Soc. A 372 (2017) (2014) 20130313,.

Cited By

Benabdellah AOberoi STyagi SBag SBanerjee S(2024)Transforming Food SystemsJournal of Global Information Management10.4018/JGIM.34996232:1(1-33)Online publication date: 17-Sep-2024
https://dl.acm.org/doi/10.4018/JGIM.349962
Zahran S(2024)Optimizing Supply Chain Management of Fresh E-Commerce Agri-Consumer Products Using Energy-Efficient Vehicle RoutingIEEE Transactions on Consumer Electronics10.1109/TCE.2024.337084570:1(1685-1693)Online publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3370845
Gómez-Lagos JGonzález-Araya MAcosta-Espejo LSoto-Silva W(2024)Supporting tactical harvest planning decisions of major fruits through a multi-objective modeling approach by using exact methodsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123929251:COnline publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123929

Index Terms

Research directions in technology development to support real-time decisions of fresh produce logistics: A review and research agenda
1. Applied computing
  1. Enterprise computing
  2. Operations research
    1. Decision analysis
2. Information systems
  1. Information systems applications
    1. Decision support systems

Index terms have been assigned to the content through auto-classification.

Recommendations

B2C or O2O? The strategic implications for the fresh produce supply chain based on blockchain technology
Highlights
- Construct a Stackelberg model for the blockchain-based fresh produce supply chain.
- Study equilibrium strategies of the fresh produce supply chain in four scenarios.
- Investigate the impact of government subsidy on blockchain ...
Abstract
The breakout of COVID-19 has made consumers pay attention to the quality and source of fresh produce sold on e-commerce platforms, while the information traceability feature of blockchain can effectively monitor fresh produce quality and cope ...
Sustainable development of the fresh agricultural products supply chain through the application of RFID technology

This study discusses the sustainable development of a fresh agricultural product (FAP) supply chain, which consists of one manufacturer and one retailer, from the perspective of supply chain coordination. The study includes a centralized FAP supply ...
An OGSM-based multi-objective optimization model for partner selection in fresh produce supply chain considering carbon emissions
Abstract
Incorporating partner selection with environmental commitment is recognized as a crucial aspect of green development in fresh produce supply chains. This paper presents a multi-objective programming (MOP) model for partner selection considering ...
Highlights
- OGSM-MOP is adjustable for the foresight of sustainable fresh produce supply chain.
- OGSM scheme enables activities of supply chain partners aligned with common goals.
- MOP transforms goals set by OGSM into an optimization model to ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Computers and Electronics in Agriculture

Computers and Electronics in Agriculture Volume 167, Issue C

Dec 2019

556 pages

ISSN:0168-1699

Issue’s Table of Contents

Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 2019

Author Tags

Qualifiers

Review-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 14 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Benabdellah AOberoi STyagi SBag SBanerjee S(2024)Transforming Food SystemsJournal of Global Information Management10.4018/JGIM.34996232:1(1-33)Online publication date: 17-Sep-2024
https://dl.acm.org/doi/10.4018/JGIM.349962
Zahran S(2024)Optimizing Supply Chain Management of Fresh E-Commerce Agri-Consumer Products Using Energy-Efficient Vehicle RoutingIEEE Transactions on Consumer Electronics10.1109/TCE.2024.337084570:1(1685-1693)Online publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3370845
Gómez-Lagos JGonzález-Araya MAcosta-Espejo LSoto-Silva W(2024)Supporting tactical harvest planning decisions of major fruits through a multi-objective modeling approach by using exact methodsExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.123929251:COnline publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.123929

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents