Abstract
The availability of timely and good-quality data on the organic farming sector is a crucial factor for the development of the organic food market. While data on hectares and farms are now widely available in Europe, data on organic yields are still relatively sparsely reported by official statistical sources for most European countries, including Italy. Information on organic yields is crucial to determine the volumes of organic production and supply. Issues such as the potential of organic farming for feeding the world, the understanding of the optimal conditions for conversion and the appropriate policy measures for supporting the organic sector are all dependent on the knowledge of organic productivity. In this study, we show how a statistical method known as multiple imputation can contribute to the improvement of the availability of organic data, through systematic exploitation of data from different sources. We apply the method to estimate missing data on organic fruit crop yields for the central regions of Italy, based on data from official national statistics and expert assessments. The results illustrate the advantages and limitations of such methods for estimating missing data on organic crops.
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References
Azur MJ, Stuart EA, Frangakis C, Leaf PJ (2011) Multiple imputation by chained equations: what is it and how does it work? Int J Method Psych 20(1):40–49. https://doi.org/10.1002/mpr.329
Allison PD (2001) Missing data. Sage, Thousand Oaks, CA
Arbenz M, Gould D, and Stopes C (2016) Organic 3.0 – for truly sustainable farming and consumption. IFOAM Organics International, Bonn
Badgley C, Moghtader J, Quintero E, Zakem E, Chappell MJ, Avilés-Vázquez K, Samulon A, Perfecto I (2007) Organic agriculture and the global food supply. Renew Agr Food Syst 22(2):86–108. https://doi.org/10.1017/S1742170507001640
Briggs A, Clark T, Wolstenholme J, Clarke P (2003) Missing presumed at random: cost-analysis of incomplete data. Health Econ 12(5):377–392. https://doi.org/10.1002/hec.766
Conrady S, Jouffe L (2015) Introduction to Bayesian networks: practical and technical perspectives. Bayesia, USA
CREA (2015) Annuario dell’agricoltura Italiana 2015 – Vol. LXIX, CREA, Roma
De Ponti T, Rijk B, Van Ittersum MK (2012) The crop yield gap between organic and conventional agriculture. Agric Syst 108:1–9. https://doi.org/10.1016/j.agsy.2011.12.004
European Commission (2014) Action plan for the future of organic production in the European Union, published by European Commission, Brussels, available at: https://ec.europa.eu/agriculture/organic/sites/orgfarming/files/docs/body/act_en.pdf.Accessed 8 January 2018
Feldmann C, Gerrard C., Hamm U, Home R, Lošták M, Padel S, Schaack D, Stolze M, Vairo D, Vieweger A, Willer H, Zanoli R (2014) Data network for better European organic market information - synthesis report. Università Politecnica delle Marche, Ancona, Italy. Available at: http://orgprints.org/28035/7/OrganicDataNetwork_D7_1_Synthesis%20Report_Annex1.pdf. Accessed 8 January 2018
Home R, Gerrard C, Hempel C, Lost'ak M, Vieweger A, Husák J, Stolze M, Hamm U, Padel S, Willer H, Vairo D, Zanoli R (2017) The quality of organic market data: providing data that is both fit for use and convenient. Organic Agric 7(2):141–152. https://doi.org/10.1007/s13165-016-0147-5
Howell DC (2008) The treatment of missing data. In: Outhwaite W, Turner S (eds) Handbook of social science methodology. Handbook. Sage, London
Gabriel D, Sait SM, Kunin WE, Benton TG (2013) Food production vs. biodiversity: comparing organic and conventional agriculture. J Appl Ecol 50(2):355–364. https://doi.org/10.1111/1365-2664.12035
Gerrard CL, Vieweger A, Padel S (2012) D2.1 report on data collectors: inventory of data collecting and publishing institutions, OrganicDataNetwork deliverable 2.1, Report to the EU Commission. The Organic Research Centre, UK
Graham JW (2009) Missing data analysis: making it work in the real world. Annu Rev Physiol 60:549–576. https://doi.org/10.1146/annurev.psych.58.110405.085530
Graham JW, Olchowski AE, Gilreath TD (2007) How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev Sci 8:206–213
Kenward MG, Carpenter J (2007) Multiple imputation: current perspective. Stat Methods Med Res 16(3):199–218. https://doi.org/10.1177/0962280206075304
Kniss AR, Savage SD, Jabbour R (2016) Commercial crop yields reveal strengths and weaknesses for organic agriculture in the United States. PLoS One 11(11):e0165851. https://doi.org/10.1371/journal.pone.0165851.g001
Lokupitiya RS, Lokupitiya E, Paustian K (2006) Comparison of missing value imputation methods for crop yield data. Environmetrics 17(4):339–349. https://doi.org/10.1002/env.773
Lotter DW, Seidel R, Liebhardt W (2003) The performance of organic and conventional cropping systems in an extreme climate year. Am J Alternative Agr 18(2):146–154. https://doi.org/10.1079/AJAA200345
Offermann F, Nieberg H (2000) Economic performance of organic farms in Europe. Organic Farming in Europe: Economics and Policy, Vol. 5. University of Hohenheim, Stuttgart, 198 p
Penning de Vries FWT, Rabbinge R, de Groot JJR (1997) Potential and attainable food production and food security in different regions. Philos Trans R Soc 352:917–928
Ponisio LC, M’Gonigle LK, Mace KC, Palomino J, de Valpine P, Kremen C (2015) Diversification practices reduce organic to conventional yield gap. Proceeding Royal Soc 282. https://doi.org/10.1098/rspb.2014.1396
Rigby D, Cáceres D (2001) Organic farming and the sustainability of agricultural systems. Agric Syst 68:21–40
Royston P (2004) Multiple imputation of missing values. Stata J 4(3):227–241
Rubin DB (1976) Inference and missing data. Biometrika 63:581–592
Rubin DB (1987) Multiple imputation for nonresponse in surveys. John Wiley & Sons, New York
Sanders J, Gambelli D, Lernoud J, Orsini S, Padel S, Stolze M, Willer H, Zanoli R (2017) Distribution of the added value of the organic food chain (Final Report). Pubblications Office of the Europena Union, Luxembourg. Available at: https://publications.europa.eu/en/publication-detail/-/publication/a911740b-4cbe-11e7-a5ca-01aa75ed71a1/language-en/format-PDF
Schafer JL (1997) Analysis of incomplete multivariate data. Chapman and Hall, New York
Schafer JL, Graham JW (2002) Missing data: our view of the state of the art. Psychol Methods 7:147–177. https://doi.org/10.1111/1467-9574.00218
Schmitt P, Mandel J, Guedj M (2015) A comparison of six methods for missing data imputation. J Biomet Biostat 6:224. https://doi.org/10.4172/2155-6180.1000224
Seufert V, Ramankutty N, Foley JA (2012) Comparing the yields of organic and conventional agriculture. Nature 485:229–232. https://doi.org/10.1038/nature11069
SINAB (2016). Bio in Cifre 2016. Uffici SINAB Mipaaf, Roma IT. Available at: http://www.sinab.it/sites/default/files/share/tempUploadVideo/Bio%20in%20cifre%202016.pdf
Stanhill G (1990) The comparative productivity of organic agriculture. Agric Ecosyst Environ 30:1–26
Stolze M, Lampkin N (2009) Policy for organic farming: rationale and concepts. Food Policy 34(3):237–244
White IR, Royston P, Wood AM (2011) Multiple imputation using chained equations: issues and guidance for practice. Stat Med 30(4):377–399. https://doi.org/10.1002/sim.4067
Willer H, Lernoud J, (2017) The world of organic agriculture – statistics and emerging trends 2017. Research Institute of Organic Agriculture (FiBL), Frick, and International Federation of Organic Agriculture Movements (IFOAM), Bonn
Willer H, Schaack D (2013) D4.2 intermediate report on compilation of key organic market data. Data Network for better European Organic Market Information, Università Politecnica delle Marche, Ancona, Italy
Acknowledgements
This study was undertaken as part of the research project ‘Data network for better European Organic Market Information’ (OrganicDataNetwork). This project received funding from the European Union Seventh Framework Programme for Research, Technological Development and Demonstration, under grant agreement no. 289376. The opinions expressed in this contribution are those of the authors and do not necessarily represent the views of the European Commission.
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Solfanelli, F., Gambelli, D., Vairo, D. et al. Estimating missing data for organic farming by multiple imputation: the case of organic fruit yields in Italy. Org. Agr. 9, 295–303 (2019). https://doi.org/10.1007/s13165-018-0228-8
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DOI: https://doi.org/10.1007/s13165-018-0228-8