Big data for sustainable agri‐food supply chains: a review and future research perspectives

Ahumada O, Villalobos JR (2009) Application of planning models in the agri-food supply chain: A review. Eur J Oper Res 196:1–20. https://doi.org/10.1016/j.ejor.2008.02.014 Aljunid MF, Manjaiah DH (2019) Movie recommender system based on collaborative filtering using apache spark. In: Balas VE, Sharma N, Chakrabarti A (eds) Data Manag. Anal. Innov. Springer, Singapore, pp 283–295. https://doi.org/10.1007/978-981-13-1274-8_22 Aqueduct WRI (2019) World Resour. Inst. https://www.wri.org/aqueduct. Accessed 29 July 2020 Astill J, Dara RA, Fraser EDG, Roberts B, Sharif S (2020) Smart poultry management: Smart sensors, big data, and the internet of things. Comput Electron Agric 170. https://doi.org/10.1016/j.compag.2020.105291 Badia-Melis R, Mc Carthy U, Ruiz-Garcia L, Garcia-Hierro J, Villalba R (2018) New trends in cold chain monitoring applications - A review. Food Control 86:170–182. https://doi.org/10.1016/j.foodcont.2017.11.022 Bosona T, Gebresenbet G (2013) Food traceability as an integral part of logistics management in food and agricultural supply chain. Food Control 33:32–48. https://doi.org/10.1016/j.foodcont.2013.02.004 Cai Y, Zheng W, Zhang X, Zhangzhong L, Xue X (2019) Research on soil moisture prediction model based on deep learning. PLoS One 14. https://doi.org/10.1371/journal.pone.0214508 Camin F, Larcher R, Nicolini G, Bontempo L, Bertoldi D, Perini M, Schlicht C, Schellenberg A, Thomas F, Heinrich K, Voerkelius S, Horacek M, Ueckermann H, Froeschl H, Wimmer B, Heiss G, Baxter M, Rossmann A, Hoogewerff J (2010) Isotopic and elemental data for tracing the origin of European olive oils. J Agric Food Chem 58:570–577. https://doi.org/10.1021/jf902814s Capmourteres V, Adams J, Berg A, Fraser E, Swanton C, Anand M (2018) Precision conservation meets precision agriculture: A case study from southern Ontario. Agric Syst 167:176–185. https://doi.org/10.1016/j.agsy.2018.09.011 Carbonell IM (2016) The ethics of big data in big agriculture. Internet Policy Rev 5. https://doi.org/10.14763/2016.1.405 Chapman R, Cook S, Donough C, Lim YL, Vun Vui Ho P, Lo KW, Oberthür T (2018) Using Bayesian networks to predict future yield functions with data from commercial oil palm plantations: A proof of concept analysis. Comput Electron Agric 151:338–348. https://doi.org/10.1016/j.compag.2018.06.006 Christopher M, Holweg M (2011) Supply Chain 2.0”: managing supply chains in the era of turbulence. Int J Phys Distrib Logist Manag 41:63–82. https://doi.org/10.1108/09600031111101439 Ciruela-Lorenzo AM, Del-Aguila-Obra AR, Padilla-Meléndez A, Plaza-Angulo JJ (2020) Digitalization of agri-cooperatives in the smart agriculture context. Proposal of a digital diagnosis tool. Sustain Switz 12. https://doi.org/10.3390/su12041325 Coble KH, Mishra AK, Ferrell S, Griffin T (2018) Big data in agriculture: A challenge for the future. Appl Econ Perspect Policy 40:79–96. https://doi.org/10.1093/aepp/ppx056 Costello C, Ovando D (2019) Status, institutions, and prospects for global capture fisheries. Annu Rev Environ Resour 44:177–200. https://doi.org/10.1146/annurev-environ-101718-033310 Coyle P (2016) Taking a bite into big data. Dataconomy. https://dataconomy.com/2016/02/taking-a-bite-into-big-data/. Accessed 18 June 2020 Cronin P, Ryan F, Coughlan M (2008) Undertaking a literature review: a step-by-step approach. Br J Nurs 17:38–43. https://doi.org/10.12968/bjon.2008.17.1.28059 Davenport TH (2014) How strategists use “big data” to support internal business decisions, discovery and production. Strategy Leadersh 42:45–50. https://doi.org/10.1108/SL-05-2014-0034 Delgado JA Jr, Short NM, Roberts DP, Vandenberg B (2019) Big data analysis for sustainable agriculture on a geospatial cloud framework. Front Sustain Food Syst 3. https://doi.org/10.3389/fsufs.2019.00054 Donohoe T, Garnett K, Lansink AO, Afonso A, Noteborn H, E.F.S. Authority (EFSA) (2018) Emerging risks identification on food and feed – EFSA. EFSA J 16. https://doi.org/10.2903/j.efsa.2018.5359 Dupaľ A, Richnák P, Szabo Ľ, Porubanová K (2019) Modern trends in logistics of agricultural enterprises. Agric Econ 65(2019):359–365. https://doi.org/10.17221/367/2018-AGRICECON Eastwood C, Klerkx L, Ayre M, Dela Rue B (2019) Managing socio-ethical challenges in the development of smart farming: from a fragmented to a comprehensive approach for responsible research and innovation. J Agric Environ Ethics 32:741–768. https://doi.org/10.1007/s10806-017-9704-5 Eisler MC, Lee MRF, Tarlton JF, Martin GB, Beddington J, Dungait JAJ, Greathead H, Liu J, Mathew S, Miller H, Misselbrook T, Murray P, Vinod VK, Van Saun R, Winter M (2014) Agriculture: Steps to sustainable livestock. Nat News 507:32. https://doi.org/10.1038/507032a Fernández-Getino AP, Alonso-Prados JL, Santín-Montanyá MI (2018) Challenges and prospects in connectivity analysis in agricultural systems: Actions to implement policies on land management and carbon storage at EU level. Land Use Policy 71:146–159. https://doi.org/10.1016/j.landusepol.2017.11.035 Finger R, Swinton SM, El Benni N, Walter A (2019) Precision farming at the nexus of agricultural production and the environment. Annu Rev Resour Econ 11:313–335. https://doi.org/10.1146/annurev-resource-100518-093929 Fleming A, Jakku E, Lim-Camacho L, Taylor B, Thorburn P (2018) Is big data for big farming or for everyone? Perceptions in the Australian grains industry. Agron Sustain Dev 38. https://doi.org/10.1007/s13593-018-0501-y Forster-Carneiro T, Berni MD, Dorileo IL, Rostagno MA (2013) Biorefinery study of availability of agriculture residues and wastes for integrated biorefineries in Brazil. Resour Conserv Recycl 77:78–88. https://doi.org/10.1016/j.resconrec.2013.05.007 Garcia Martinez M, Briz J (2000) Innovation in the Spanish food & drink industry. Int Food Agribus Manag Rev 3:155–176. https://doi.org/10.1016/S1096-7508(00)00033-1 Garg R, Aggarwal H, Centobelli P, Cerchione R (2019) Extracting knowledge from big data for sustainability: A comparison of machine learning techniques. Sustain Switz 11. https://doi.org/10.3390/su11236669 Gašová M, Gašo M, Štefánik A (2017) Advanced industrial tools of ergonomics based on industry 4.0 concept. Procedia Eng 192:219–224. https://doi.org/10.1016/j.proeng.2017.06.038 George G, Haas MR, Pentland A (2014) Big data and management. Acad Manag J. https://doi.org/10.5465/amj.2014.4002 Gerber PJ, Steinfeld H, Henderson B, Mottet A, Opio C, Dijkman J, Falcucci A, Tempio G (2013) Tackling climate change through livestock: a global assessment of emissions and mitigation opportunities., Tackling Clim. Change Livest. Glob. Assess. Emiss. Mitig. Oppor. https://www.cabdirect.org/cabdirect/abstract/20133417883. Accessed 22 June 2020 Giagnocavo C, Bienvenido F, Ming L, Yurong Z, Sanchez-Molina JA, Xinting Y (2017) Agricultural cooperatives and the role of organisational models in new intelligent traceability systems and big data analysis. Int J Agric Biol Eng 10:115–125. https://doi.org/10.25165/ijabe.v10i5.3089 Grunert KG (1997) What’s in a steak? A cross-cultural study on the quality perception of beef. Food Qual Prefer 8:157–174. https://doi.org/10.1016/S0950-3293(96)00038-9 Guo T, Wang Y (2019) Big data application issues in the agricultural modernization of china. Ekoloji 28:3677–3688. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063972060&partnerID=40&md5=9242c206ed052dc847c93fc8cf10ce2e. Accessed 30 July 2020 Halewood M, Chiurugwi T, Sackville Hamilton R, Kurtz B, Marden E, Welch E, Michiels F, Mozafari J, Sabran M, Patron N, Kersey P, Bastow R, Dorius S, Dias S, McCouch S, Powell W (2018) Plant genetic resources for food and agriculture: opportunities and challenges emerging from the science and information technology revolution. New Phytol 217:1407–1419. https://doi.org/10.1111/nph.14993 He M, Sun Y, Zou D, Yuan H, Zhu B, Li X, Pang Y (2012) Influence of temperature on hydrolysis acidification of food waste. Procedia Environ Sci 16:85–94. https://doi.org/10.1016/j.proenv.2012.10.012 Hou D, Bolan NS, Tsang DCW, Kirkham MB, O’Connor D (2020) Sustainable soil use and management: An interdisciplinary and systematic approach. Sci Total Environ 729. https://doi.org/10.1016/j.scitotenv.2020.138961 Irani Z, Sharif AM, Lee H, Aktas E, Topaloğlu Z, van’t Wout T, Huda S (2018) Managing food security through food waste and loss: Small data to big data. Comput Oper Res 98:367–383. https://doi.org/10.1016/j.cor.2017.10.007 Jakku E, Taylor B, Fleming A, Mason C, Fielke S, Sounness C, Thorburn P (2019) “If they don’t tell us what they do with it, why would we trust them?” Trust, transparency and benefit-sharing in Smart Farming, NJAS - Wagening. J Life Sci :90–91. https://doi.org/10.1016/j.njas.2018.11.002 Jara-Rojas R, Bravo-Ureta BE, Engler A, Díaz J (2013) An analysis of the joint adoption of water conservation and soil conservation in Central Chile. Land Use Policy 32:292–301. https://doi.org/10.1016/j.landusepol.2012.11.001 Kamble SS, Gunasekaran A, Gawankar SA (2020) Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications. Int J Prod Econ 219:179–194. https://doi.org/10.1016/j.ijpe.2019.05.022 Kamilaris A, Kartakoullis A, Prenafeta-Boldú FX (2017) A review on the practice of big data analysis in agriculture. Comput Electron Agric 143:23–37. https://doi.org/10.1016/j.compag.2017.09.037 Kamilaris A, Anton A, Blasi AB, Boldú FXP (2018) Assessing and mitigating the impact of livestock agriculture on the environment through geospatial and big data analysis. Int J Sustain Agric Manag Inform 4:98. https://doi.org/10.1504/IJSAMI.2018.094809 Kellengere Shankarnarayan V, Ramakrishna H (2020) Paradigm change in Indian agricultural practices using Big Data: Challenges and opportunities from field to plate. Inf Process Agric. https://doi.org/10.1016/j.inpa.2020.01.001 Khalil RAA, Johar F, Sabri S (2015) The impact of new-build gentrification in Iskandar Malaysia: a case study of Nusajaya. Procedia Soc Behav Sci 202:495–504. https://doi.org/10.1016/j.sbspro.2015.08.192 Khanna M, Swinton SM, Messer KD (2018) Sustaining our natural resources in the face of increasing societal demands on agriculture: directions for future research. Appl Econ Perspect Policy 40:38–59. https://doi.org/10.1093/aepp/ppx055 Klerkx L, Jakku E, Labarthe P (2019) A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda, NJAS - Wagening. J Life Sci :100315. https://doi.org/10.1016/j.njas.2019.100315 Kolipaka VRR (2020) Predictive analytics using cross media features in precision farming. Int J Speech Technol 23:57–69. https://doi.org/10.1007/s10772-020-09669-z Li B (2019) Recommendation system of crop planting books based on big data. Rev Fac. Agron Univ Zulia 36. http://agronomiajournal.com/index.php/path/article/view/702. Accessed 29 July 2020 Li B, Ghose A, Ipeirotis PG (2011) Towards a theory model for product search. In: Proc. 20th Int. Conf. World Wide Web, ACM, New York, pp 327–336. https://doi.org/10.1145/1963405.1963453 Li J, Li X, Peng Y (2019) Application of big data in agricultural internet of things. Rev Fac Agron 36:1521–1529. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073269640&partnerID=40&md5=17165555014b0b7d5e3b60a2f691cf6e. Accessed 1 Sept 2020 Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, Clarke M, Devereaux PJ, Kleijnen J, Moher D (2009) The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med 151:W–65 Lioutas ED, Charatsari C (2020) Big data in agriculture: Does the new oil lead to sustainability? Geoforum 109:1–3. https://doi.org/10.1016/j.geoforum.2019.12.019 Lioutas ED, Charatsari C, La Rocca G, De Rosa M (2019) Key questions on the use of big data in farming: An activity theory approach, NJAS - Wagening. J Life Sci :90–91. https://doi.org/10.1016/j.njas.2019.04.003 Liu B (2019) The “internet +” intelligent agricultural products circulation channel based on the fourth party logistics. Rev Fac Agron 36:1122–1132. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070781334&partnerID=40&md5=91fcad3293bcaabc106616fa98e0af65. Accessed 12 Sept 2020 Mardani A, Kannan D, Hooker RE, Ozkul S, Alrasheedi M, Tirkolaee EB (2020) Evaluation of green and sustainable supply chain management using structural equation modelling: A systematic review of the state of the art literature and recommendations for future research. J Clean Prod 249:119383. https://doi.org/10.1016/j.jclepro.2019.119383 Marques Vieira L, Dutra M, De Barcellos A, Hoppe S, Bitencourt da, Silva (2013) An analysis of value in an organic food supply chain. Br Food J 115:1454–1472. https://doi.org/10.1108/BFJ-06-2011-0160 Marvin HJP, Janssen EM, Bouzembrak Y, Hendriksen PJM, Staats M (2017) Big data in food safety: An overview. Crit Rev Food Sci Nutr 57:2286–2295. https://doi.org/10.1080/10408398.2016.1257481 Mishra N, Singh A (2018) Use of twitter data for waste minimisation in beef supply chain. Ann Oper Res 270:337–359. https://doi.org/10.1007/s10479-016-2303-4 Munz J, Gindele N, Doluschitz R (2020) Exploring the characteristics and utilisation of Farm Management Information Systems (FMIS) in Germany. Comput Electron Agric 170. https://doi.org/10.1016/j.compag.2020.105246 Opara LU, Mazaud F (2001) Food traceability from field to plate. Outlook Agric 30:239–247. https://doi.org/10.5367/000000001101293724 Orts E, Spigonardo J (2014) Sustainability in the age of big data. IGEL Wharton Univ., Philadelphia. 16 Östergren K, Davis J, Menna FD, Vittuari M, Unger N, Loubiere M (2017) Food supply chain side flows management through Life Cycle Assessment and Life Cycle Costing: a practitioner’s perspective. Proc Food Syst Dyn :300–303. https://doi.org/10.18461/pfsd.2017.1731 Otles S, Despoudi S, Bucatariu C, Kartal C (2015) Food waste management, valorization, and sustainability in the food industry. Food Waste Recovery. Elsevier, Amsterdam, pp 3–23 Pralle RS, White HM (2020) Symposium review: Big data, big predictions: Utilizing milk Fourier-transform infrared and genomics to improve hyperketonemia management. J Dairy Sci 103:3867–3873. https://doi.org/10.3168/jds.2019-17379 Rajeswari S, Suthendran K (2019) C5.0: Advanced Decision Tree (ADT) classification model for agricultural data analysis on cloud. Comput Electron Agric 156:530–539. https://doi.org/10.1016/j.compag.2018.12.013 Ramirez BC, Xin H, Halbur PG, Beermann DH, Hansen SL, Linhares DCL, Peschel JM, Rademacher CJ, Reecy JM, Ross JW, Shepherd TA, Koltes JE (2019) At the intersection of industry, academia, and government: How do we facilitate productive precision livestock farming in practice? Animals 9. https://doi.org/10.3390/ani9090635 Ramos-Rodríguez A-R, Ruíz‐Navarro J (2004) Changes in the intellectual structure of strategic management research: a bibliometric study of the Strategic Management Journal, 1980–2000. Strateg Manag J 25:981–1004. https://doi.org/10.1002/smj.397 Reynolds M, Kropff M, Crossa J, Koo J, Kruseman G, Molero Milan A, Rutkoski J, Schulthess U, Singh B, Sonder K, Tonnang H, Vadez V (2018) Role of modelling in international crop research: Overview and some case studies. Agronomy 8. https://doi.org/10.3390/agronomy8120291 Rotz S, Duncan E, Small M, Botschner J, Dara R, Mosby I, Reed M, Fraser EDG (2019) The politics of digital agricultural technologies: a preliminary review. Sociol Rural 59:203–229. https://doi.org/10.1111/soru.12233 Rowley J, Slack F (2004) Conducting a literature review. Manag Res News 27:31–39. https://doi.org/10.1108/01409170410784185 Rubens P (2014) Helping feed the world with big data, BBC News. https://www.bbc.com/news/business-26424338.. Accessed 28 July 2020 Ryan M (2020) Agricultural big data analytics and the ethics of power. J Agric Environ Ethics 33:49–69. https://doi.org/10.1007/s10806-019-09812-0 Saiz-Rubio V, Rovira-Más F (2020) From smart farming towards agriculture 5.0: A review on crop data management. Agronomy 10. https://doi.org/10.3390/agronomy10020207 Sarangi A, Madramootoo CA, Cox C (2004) A decision support system for soil and water conservation measures on agricultural watersheds. Land Degrad Dev 15:49–63. https://doi.org/10.1002/ldr.589 Sarkar MB, Butler B, Steinfield C (1995) Intermediaries and cybermediaries: Sarkar, butler and steinfield. J Comput-Mediat Commun 1:JCMC132 Serazetdinova L, Garratt J, Baylis A, Stergiadis S, Collison M, Davis S (2019) How should we turn data into decisions in AgriFood? J Sci Food Agric 99:3213–3219. https://doi.org/10.1002/jsfa.9545 Sethuraman MS 2012 Big data’s impact on the data supply chain. Cognizant, New Jersey Sgarbossa F, Russo I (2017) A proactive model in sustainable food supply chain: Insight from a case study. Int J Prod Econ 183:596–606. https://doi.org/10.1016/j.ijpe.2016.07.022 Sharma R, Kamble SS, Gunasekaran A (2018) Big GIS analytics framework for agriculture supply chains: A literature review identifying the current trends and future perspectives. Comput Electron Agric 155:103–120. https://doi.org/10.1016/j.compag.2018.10.001 Sharma R, Kamble SS, Gunasekaran A, Kumar V, Kumar A (2020) A systematic literature review on machine learning applications for sustainable agriculture supply chain performance. Comput Oper Res 119. https://doi.org/10.1016/j.cor.2020.104926 Singh A, Kumari S, Malekpoor H, Mishra N (2018) Big data cloud computing framework for low carbon supplier selection in the beef supply chain. J Clean Prod 202:139–149. https://doi.org/10.1016/j.jclepro.2018.07.236 Skilton PF, Robinson JL (2009) Traceability and normal accident theory: how does supply network complexity influence the traceability of adverse events? J Supply Chain Manag 45:40–53. https://doi.org/10.1111/j.1745-493X.2009.03170.x Smith P, Martino D, Cai Z, Gwary D, Janzen H, Kumar P, McCarl B, Ogle S, O’Mara F, Rice C, Scholes B, Sirotenko O, Howden M, McAllister T, Pan G, Romanenkov V, Schneider U, Towprayoon S (2007) Policy and technological constraints to implementation of greenhouse gas mitigation options in agriculture. Agric Ecosyst Environ 118:6–28. https://doi.org/10.1016/j.agee.2006.06.006 Soto-Silva WE, Nadal-Roig E, González-Araya MC, Pla-Aragones LM (2016) Operational research models applied to the fresh fruit supply chain. Eur J Oper Res 251:345–355. https://doi.org/10.1016/j.ejor.2015.08.046 Steinfeld H, Gerber P, Wassenaar TD, F. and AO of the U Nations, Castel V, Rosales M, M MR, de Haan C 2006 Livestock’s long shadow: environmental issues and options. Food & Agriculture Org, Rome Subudhi BN, Rout DK, Ghosh A (2019) Big data analytics for video surveillance. Multimed Tools Appl 78: 26129–26162. https://doi.org/10.1007/s11042-019-07793-w Sun D-W (2014) Emerging technologies for food processing. Elsevier, Amsterdam Tan B, Yin Y (2017) Environmental sustainability analysis and nutritional strategies of animal production in China. Annu Rev Anim Biosci 5:171–184. https://doi.org/10.1146/annurev-animal-022516-022935 Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag 14:207–222. https://doi.org/10.1111/1467-8551.00375 van Evert FK, Fountas S, Jakovetic D, Crnojevic V, Travlos I, Kempenaar C (2017) Big Data for weed control and crop protection. Weed Res 57:218–233. https://doi.org/10.1111/wre.12255 Villa-Henriksen A, Edwards GTC, Pesonen LA, Green O, Sørensen CAG (2020) Internet of Things in arable farming: Implementation, applications, challenges and potential. Biosyst Eng 191:60–84. https://doi.org/10.1016/j.biosystemseng.2019.12.013 Vlajic JV, van Lokven SWM, Haijema R, van der Vorst JGAJ (2013) Using vulnerability performance indicators to attain food supply chain robustness. Prod Plan Control 24:785–799. https://doi.org/10.1080/09537287.2012.666869 Wang S, Zhang C, Li D (2016) A big data centric integrated framework and typical system configurations for smart factory. In: Ind. IoT Technol. Appl., Springer, Cham pp 12–23. https://doi.org/10.1007/978-3-319-44350-8_2 Weersink A, Fraser E, Pannell D, Duncan E, Rotz S (2018) Opportunities and challenges for big data in agricultural and environmental analysis. Annu Rev Resour Econ 10:19–37. https://doi.org/10.1146/annurev-resource-100516-053654 Wiese MV (1982) Crop management by comprehensive appraisal of yield determining variables. Annu Rev Phytopathol 20:419–432 Wolfert S, Ge L, Verdouw C, Bogaardt M-J (2017) Big data in smart farming – a review. Agric Syst 153:69–80. https://doi.org/10.1016/j.agsy.2017.01.023 World Bank (2020) Agriculture and Food. World Bank. https://www.worldbank.org/en/topic/agriculture/overview.. Accessed 29 July 2020 Xia H, Houghton JA, Clark JH, Matharu AS (2016) Potential utilization of unavoidable food supply chain wastes–valorization of pea vine wastes. ACS Sustain Chem Eng 4:6002–6009. https://doi.org/10.1021/acssuschemeng.6b01297 Zhang Z, Huisingh D (2018) Combating desertification in China: Monitoring, control, management and revegetation. J Clean Prod 182:765–775. https://doi.org/10.1016/j.jclepro.2018.01.233