Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 672

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics

Open access
Balafoutis, Athanasios, Beck, Bert, Fountas, Spyros, Vangeyte, Jurgen, Wal, Tamme, Soto, Iria, Gómez-Barbero, Manuel, Barnes, Andrew, Eory, Vera·2017·Sustainability

Abstract

Agriculture is one of the economic sectors that affect climate change contributing to greenhouse gas emissions directly and indirectly. There is a trend of agricultural greenhouse gas emissions reduction, but any practice in this direction should not affect negatively farm productivity and economics because this would limit its implementation, due to the high global food and feed demand and the competitive environment in this sector. Precision agriculture practices using high-tech equipment has the ability to reduce agricultural inputs by site-specific applications, as it better target inputs to spatial and temporal needs of the fields, which can result in lower greenhouse gas emissions. Precision agriculture can also have a positive impact on farm productivity and economics, as it provides higher or equal yields with lower production cost than conventional practices. In this work, precision agriculture technologies that have the potential to mitigate greenhouse gas emissions are presented providing a short description of the technology and the impacts that have been reported in literature on greenhouse gases reduction and the associated impacts on farm productivity and economics. The technologies presented span all agricultural practices, including variable rate sowing/planting, fertilizing, spraying, weeding and irrigation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/su9081339

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Research works printed but not linked: 108

  1. Montzka, 2011, Non-CO2 greenhouse gases and climate change, Nature, 476, 43, 10.1038/nature10322 · DOI · Paper page
  2. Angers, 2008, Full-Inversion Tillage and Organic Carbon Distribution in Soil Profiles: A Meta-Analysis, Soil Sci. Soc. Am. J., 72, 1370, 10.2136/sssaj2007.0342 · DOI · Paper page
  3. Waldrop, 2004, Nitrogen deposition modifies soil carbon storage through changes in microbial enzymatic activity, Ecol. Appl., 14, 1172, 10.1890/03-5120 · DOI · Paper page
  4. Khan, 2007, The Myth of Nitrogen Fertilization for Soil Carbon Sequestration, J. Environ. Qual., 36, 1821, 10.2134/jeq2007.0099 · DOI · Paper page
  5. Plant, 2000, Precision agriculture can increase profits and limit environmental impacts, Calif. Agric., 54, 66, 10.3733/ca.v054n04p66 · doi:10.3733/ca.v054n04p66
  6. Daberkow, 2003, Farm and Operator Characteristics Affecting the Awareness and Adoption of Precision Agriculture Technologies in the US, Precis. Agric., 4, 163, 10.1023/A:1024557205871 · DOI · Paper page
  7. Fountas, 2005, Farmer Experience with Precision Agriculture in Denmark and the US Eastern Corn Belt, Precis. Agric., 6, 121, 10.1007/s11119-004-1030-z · DOI
  8. Roland, B. (2016, May 25). Press Release. Available online: http://www.rolandberger.com/press_releases/market_for_smart_agriculture_applications_growing.html.
  9. Pedersen, 2004, Adoption and perspectives of precision farming in Denmark, Acta Agric. Scand. Sect. B, 54, 2
  10. McBratney, 2005, Future Directions of Precision Agriculture, Precis. Agric., 6, 7, 10.1007/s11119-005-0681-8 · DOI · Paper page
  11. Kutter, 2011, The role of communication and co-operation in the adoption of precision farming, Precis. Agric., 12, 2, 10.1007/s11119-009-9150-0 · DOI · Paper page
  12. Osenberg, 2011, Increased soil emissions of potent greenhouse gases under increased atmospheric CO2, Nature, 475, 214, 10.1038/nature10176 · DOI · Paper page
  13. Roger, 2001, Production, oxidation, emission and consumption of methane by soils: A review, Eur. J. Soil Biol., 37, 25, 10.1016/S1164-5563(01)01067-6 · DOI · Paper page
  14. Pathak, 2003, Methane emission from rice-wheat cropping system in the Indo-Gangetic plain in relation to irrigation, farmyard manure and dicyandiamide application, Agric. Ecosyst. Environ., 97, 309, 10.1016/S0167-8809(03)00033-1 · DOI
  15. Linquist, 2012, Fertilizer management practices and greenhouse gas emissions from rice systems: A quantitative review and analysis, Field Crops Res., 135, 10, 10.1016/j.fcr.2012.06.007 · DOI · Paper page
  16. Ma, 2007, Effects of nitrogen fertiliser and wheat straw application on CH4 and N2O emissions from a paddy rice field, Aust. J. Soil Resour., 45, 359, 10.1071/SR07039 · DOI
  17. Zou, J., Huang, Y., Jiang, J., Zheng, X., and Sass, R.L. (2005). A 3-year field measurement of methane and nitrous oxide emissions from rice paddies in China: Effects of water regime, crop residue, and fertilizer application. Glob. Biogeochem. Cycles, 19. · DOI · Paper page
  18. Smith, 2008, Greenhouse gas mitigation in agriculture, Phil. Trans. R. Soc. B, 363, 789, 10.1098/rstb.2007.2184 · DOI · Paper page
  19. Ma, 2013, Net global warming potential and greenhouse gas intensity of annual rice–wheat rotations with integrated soil–crop system management, Agric. Ecosyst. Environ., 164, 209, 10.1016/j.agee.2012.11.003 · DOI · Paper page
  20. Bouwman, 2002, Modeling Global Annual N2O and NO Emissions from Fertilized Fields, Glob. Biogeochem. Cycles, 16, 1080
  21. Cannell, 2003, Carbon sequestration and biomass energy offset: Theoretical, potential and achievable capacities globally, in Europe and the UK, Biomass Bioenergy, 24, 97, 10.1016/S0961-9534(02)00103-4 · DOI · Paper page
  22. Schneider, 2003, Economic Potential of Biomass Based Fuels for Greenhouse Gas Emission Mitigation, Environ. Resour. Econ., 24, 291, 10.1023/A:1023632309097 · DOI · Paper page
  23. Robertson, 2004, Greenhouse Gas Fluxes in Tropical and Temperate Agriculture: The need for a Full-Cost accounting of Global Warming Potentials, Environ. Dev. Sustain., 6, 51, 10.1023/B:ENVI.0000003629.32997.9e · DOI · Paper page
  24. Schils, 2005, A farm level approach to define successful mitigation strategies for GHG emissions from ruminant livestock systems, Nutr. Cycl. Agroecosys., 71, 163, 10.1007/s10705-004-2212-9 · DOI
  25. Mangalassery, 2014, To what extent can zero tillage lead to a reduction in greenhouse gas emissions from temperate soils?, Sci. Rep., 4, 4586, 10.1038/srep04586 · DOI · Paper page
  26. Robertson, 1999, Keeping Track of Carbon, Science, 285, 1849, 10.1126/science.285.5435.1849k · DOI
  27. Eory, V., and Moran, D. (2017, March 15). Review of Potential Measures for RPP2-Agriculture. Available online: http://www.climatexchange.org.uk/files/3413/7338/8148/Review_of_Potential_Measures_for_RPP2_-_Agriculture.pdf.
  28. 2013, Variable Rate Control System Designed for Spinner Disc Fertiliser Spreader–“Pre Fer”, Agric. Eng., 2, 45
  29. Hijazi, 2014, High Speed Stereovision Setup for Position and Motion Estimation of Fertilizer Particles Leaving a Centrifugal Spreader, Sensors, 14, 21466, 10.3390/s141121466 · doi:10.3390/s141121466
  30. Calcante, 2015, A Retrofit Variable-Rate Control System for Pressurized Slurry Tankers, Appl. Eng. Agric., 31, 569
  31. Brambilla, M., Calcante, A., Oberti, R., and Bisaglia, C. (2015). Slurry tanker retrofitting with variable rate dosing system: A case study. Precision Agriculture ‘15, Wageningen Academic Publishers. · doi:10.3920/978-90-8686-814-8_44
  32. Morgan, 2013, Plant-soil interactions: Nutrient uptake, Nat. Educ. Knowl., 4, 2
  33. Wood, S., and Cowie, A. (2004). A Review of Greenhouse Gas Emission Factors for Fertiliser Production.
  34. Kang, 2015, Comparison of pooled standard deviation and standardized-t bootstrap methods for estimating uncertainty about average methane emission from rice cultivation, Atmos. Environ., 111, 39, 10.1016/j.atmosenv.2015.03.041 · DOI
  35. Liu, 2015, Net global warming potential and greenhouse gas intensity from the double rice system with integrated soil–crop system management: A three-year field study, Atmos. Environ., 116, 92, 10.1016/j.atmosenv.2015.06.018 · DOI
  36. Bausch, 2005, Impact of Residual Soil Nitrate on In-Season Nitrogen Applications to Irrigated Corn Based on Remotely Sensed Assessments of Crop Nitrogen Status, Precis. Agric., 6, 509, 10.1007/s11119-005-5641-9 · doi:10.1007/s11119-005-5641-9
  37. Millar, 2010, Nitrogen fertiliser management for nitrous oxide (N2O) mitigation in intensive corn (Maize) production: An emissions reduction protocol for US. Midwest agriculture, Mitig. Adapt. Strat. Glob. Change, 15, 185, 10.1007/s11027-010-9212-7 · DOI · Paper page
  38. Ribaudo, M., Delgado, J., Hansen, L., Livingston, M., Mosheim, R., and Williamson, J. (2011). Nitrogen in Agricultural Systems: Implications for Conservation Policy. Dept. Agric. Econ. Res. Serv. · DOI · Paper page
  39. Hoben, 2011, Nonlinear nitrous oxide (N2O) response to nitrogen fertilizer in on-farm corn crops of the US Midwest, Glob. Chang. Biol., 17, 1140, 10.1111/j.1365-2486.2010.02349.x · DOI · Paper page
  40. McSwiney, 2005, Nonlinear response of N2O flux to incremental fertilizer addition in a continuous maize (Zea mays L.) cropping system, Glob. Chang. Biol., 11, 1712, 10.1111/j.1365-2486.2005.01040.x · DOI · Paper page
  41. Ogle, S., Archibeque, S., Gurung, R., and Paustian, K. (2010). Report on GHG Mitigation Literature Review for Agricultural Systems.
  42. Sehy, 2003, Nitrous oxide fluxes from maize fields: Relationship to yield, site-specific fertilization, and soil conditions, Agric. Ecosys. Environ., 99, 97, 10.1016/S0167-8809(03)00139-7 · DOI · Paper page
  43. Kierkegaard, 1994, Yield Reduction Resulting from Uneven Fertilizer Distribution, Trans. ASAE, 37, 1749, 10.13031/2013.28262 · doi:10.13031/2013.28262
  44. Raun, 2001, In-Season Prediction of Potential Grain Yield in Winter Wheat Using Canopy Reflectance, Agron. J., 93, 131, 10.2134/agronj2001.931131x · DOI · Paper page
  45. Tekin, 2010, Variable rate fertiliser application in Turkish wheat agriculture: Economic assessment, Afr. J. Agric. Res., 5, 647
  46. Koch, 2004, Economic Feasibility of Variable-Rate Nitrogen Application Utilizing Site-Specific Management Zones This study was conducted through a USDA-IFAFS-funded grant, Agron. J., 96, 1572, 10.2134/agronj2004.1572 · doi:10.2134/agronj2004.1572
  47. Raun, 2002, Improving Nitrogen Use Efficiency in Cereal Grain Production with Optical Sensing and Variable Rate Application, Agron. J., 94, 815, 10.2134/agronj2002.8150 · doi:10.2134/agronj2002.8150 · Paper page
  48. Mamo, 2003, Spatial and temporal variation in economically optimum nitrogen rate for corn, Agron. J., 95, 958, 10.2134/agronj2003.9580 · doi:10.2134/agronj2003.9580 · Paper page
  49. Huber, D.M., Sutton, A.L., Jones, D.D., Joern, B.C., and Mitchell, J.K. (1993, January 13–14). Nutrient management of manure to enhance crop production and protect the environment. Proceedings of the Integrated Resource Mgt. Landscape Modifications for Environ. Protect. Conference, ASABE, Chicago, IL, USA.
  50. Morris, 1999, Development of a site-specific application system for liquid animal manures, Appl. Eng. Agric., 15, 633, 10.13031/2013.5829 · doi:10.13031/2013.5829
  51. Schellberg, 2009, A site-specific slurry application technique on grassland and on arable crops, Bioresour. Technol., 100, 280, 10.1016/j.biortech.2008.05.044 · doi:10.1016/j.biortech.2008.05.044
  52. Weisz, 2003, Long-Term Variable Rate Lime and Phosphorus Application for Piedmont No-Till Field Crops, Precis. Agric., 4, 311, 10.1023/A:1024908724491 · doi:10.1023/a:1024908724491
  53. Kuang, B., Tekin, Y., Waine, T., and Mouazen, A.M. (2014, January 6–10). Variable rate lime application based on on-line visible and near infrared (vis-NIR) spectroscopy measurement of soil properties in a Danish field. Proceedings of the AgEng Conference, Zurich, Switzerland.
  54. Swinton, 1998, Evaluating the Profitability of Site-Specific Farming, J. Produc. Agric., 11, 439, 10.2134/jpa1998.0439 · DOI · Paper page
  55. Pierce, 2000, Soil and crop response to variable-rate liming for two Michigan fields, Soil Sci. Soc. Am. J., 64, 774, 10.2136/sssaj2000.642774x · DOI
  56. Lambert, D., and Lowenberg-De Boer, J. (2000). Precision Agriculture Profitability Review, Purdue University.
  57. Bongiovanni, 2000, Economics of Variable Rate Lime in Indiana, Precis. Agric., 2, 55, 10.1023/A:1009936600784 · doi:10.1023/a:1009936600784
  58. McCann, 1997, Variable rate water and chemical application for continuous-move sprinkler irrigation systems, Appl. Eng. Agric., 13, 609, 10.13031/2013.21649 · doi:10.13031/2013.21649
  59. King, 1999, Computer control system for spatially varied water and chemical application studies with continuous-move irrigation systems, Comput. Electon. Agric., 24, 177, 10.1016/S0168-1699(99)00063-0 · doi:10.1016/s0168-1699(99)00063-0
  60. Omary, 1997, Center pivot irrigation system modification to provide variable water application depths, Appl. Eng. Agric., 13, 235, 10.13031/2013.21604 · doi:10.13031/2013.21604
  61. Stone, 2006, Water flow rates from a site-specific irrigation system, Appl. Eng. Agric., 22, 73, 10.13031/2013.20194 · doi:10.13031/2013.20194
  62. Dukes, 2006, Uniformity testing of variable-rate center pivot irrigation control systems, Precis. Agric., 7, 205, 10.1007/s11119-006-9020-y · doi:10.1007/s11119-006-9020-y
  63. Han, 2009, Development of Clemson variable-rate lateral irrigation system, Comput. Electon. Agric., 68, 108, 10.1016/j.compag.2009.05.002 · doi:10.1016/j.compag.2009.05.002
  64. Pierce, 2010, A remote irrigation monitoring and control system (RIMCS) for continuous move systems. Part B: Field testing and results, Precis. Agric., 11, 11, 10.1007/s11119-009-9110-8 · doi:10.1007/s11119-009-9110-8
  65. King, 2004, A variable flow rate sprinkler for site-specific irrigation management, Tran. ASAE, 20, 765
  66. Evans, 2013, Adoption of site-specific variable rate sprinkler irrigation systems, Irrig. Sci., 31, 871, 10.1007/s00271-012-0365-x · DOI · Paper page
  67. Camp, 1998, Subsurface drip irrigation: A review, Tran. ASAE, 41, 1353, 10.13031/2013.17309 · doi:10.13031/2013.17309
  68. Sadler, 2005, Opportunities for conservation with precision irrigation, J. Soil Water Conserv., 60, 371, 10.1080/00224561.2005.12435829 · DOI · Paper page
  69. La Rua, J., and Evans, R. (2012, January 21–22). Considerations for variable rate irrigation. Proceedings of the 24th Annual Central Plains Irrigation Conference, Colby, Kansas, USA.
  70. Trost, 2013, Irrigation, soil organic carbon and N2O emissions, Agron. Sustain. Dev., 33, 733, 10.1007/s13593-013-0134-0 · DOI · Paper page
  71. Tomasiewicz, D.J., Hingley, L., Derdall, E., and Vestre, B. (2013, January 5–6). Variable Rate Irrigation: The Next Big Thing in Irrigated Agriculture?. Proceedings of the Soils and Crops Conference, Saskatchewan, SK, Canada.
  72. Seo, 2008, Irrigation technology adoption and its implication for water conservation in the Texas High Plains: A real options approach, Agric. Econ., 38, 47, 10.1111/j.1574-0862.2007.00280.x · doi:10.1111/j.1574-0862.2007.00280.x
  73. Booker, 2015, Temporal and spatial simulation of production-scale irrigated cotton systems, Precis. Agric., 16, 630, 10.1007/s11119-015-9397-6 · DOI
  74. Evans, 2012, Site-Specific Sprinkler Irrigation in a Water-Limited Future, Tran. ASABE., 55, 493, 10.13031/2013.41382 · doi:10.13031/2013.41382
  75. Hedley, 2009, Soil water status mapping and two variable-rate irrigation scenarios, Precis. Agric., 10, 342, 10.1007/s11119-009-9119-z · doi:10.1007/s11119-009-9119-z
  76. Daccache, 2015, Implementing precision irrigation in a humid climate – Recent experiences and on-going challenges, Agric. Water Manag., 147, 135, 10.1016/j.agwat.2014.05.018 · DOI
  77. Shockley, 2015, A Whole Farm Analysis of the Influence of Auto-Steer Navigation on Net Returns, Risk, and Production Practices, J. Agric. Appl. Econ., 43, 57, 10.1017/S1074070800004053 · DOI
  78. Bora, 2012, Energy savings by adopting precision agriculture in rural USA, Energy Sustain. Soc., 2, 22, 10.1186/2192-0567-2-22 · DOI
  79. Ortiz, 2013, Evaluation of agronomic and economic benefits of using RTK-GPS-based auto-steer guidance systems for peanut digging operations, Precis. Agric., 14, 357, 10.1007/s11119-012-9297-y · doi:10.1007/s11119-012-9297-y
  80. Bergtold, 2009, The Economic Benefit of Improving the Proximity of Tillage and Planting Operations in Cotton Production with Automatic Steering, Appl. Eng. Agric., 25, 133, 10.13031/2013.26322 · doi:10.13031/2013.26322
  81. Jensen, 2012, Socioeconomic impact of widespread adoption of precision farming and controlled traffic systems in Denmark, Precis. Agric., 13, 661, 10.1007/s11119-012-9276-3 · DOI
  82. Zhang, Q., and Pierce, F.J. (2013). Automation of pesticide application systems. Agricultural Automation, Fundamentals and Practices, CRC Press.
  83. Timmermann, 2003, The Economic Impact of Site-Specific Weed Control, Precis. Agric., 4, 249, 10.1023/A:1024988022674 · DOI
  84. Vasileiadis, 2013, Sustainability of European maize-based cropping systems: Economic, environmental and social assessment of current and proposed innovative IPM-based systems, Eur. J. Agron., 48, 1, 10.1016/j.eja.2013.02.001 · DOI
  85. Gerhards, R., Sökefeld, M., Timmermann, C., Reichart, S., Kühbauch, W., and Williams, M.M. (1999, January 11–15). Results of a four-year study on site-specific herbicide application. Proceedings of the 2nd European Conference on Precision Agriculture, Odense, Denmark.
  86. Heisel, T., Christensen, S., and Walter, A.M. (1999, January 11–15). Whole-field experiments with site-specific weed management. Proceeding of the 2nd European Conference on Precision Agriculture, Odense, Denmark.
  87. Dammer, 2007, Sensor-based weed detection and application of variable herbicide rates in real time, Crop Prot., 26, 270, 10.1016/j.cropro.2005.08.018 · doi:10.1016/j.cropro.2005.08.018
  88. Solanelles, 2006, An Electronic Control System for Pesticide Application Proportional to the Canopy Width of Tree Crops, Biosyst. Eng., 95, 473, 10.1016/j.biosystemseng.2006.08.004 · doi:10.1016/j.biosystemseng.2006.08.004
  89. Gil, 2007, Variable rate application of plant protection products in vineyard using ultrasonic sensors, Crop Prot., 26, 1287, 10.1016/j.cropro.2006.11.003 · doi:10.1016/j.cropro.2006.11.003
  90. Llorens, 2010, Variable rate dosing in precision viticulture: Use of electronic devices to improve application efficiency, Crop Prot., 29, 239, 10.1016/j.cropro.2009.12.022 · doi:10.1016/j.cropro.2009.12.022
  91. Chen, 2013, Spray Deposition inside Tree Canopies from a Newly Developed Variable-Rate Air-Assisted Sprayer, Tran. ASABE, 56, 1263
  92. Dammer, 2012, Sensor-Based Insecticide Spraying to Control Cereal Aphids and Preserve Lady Beetles, Agron. J., 104, 1694, 10.2134/agronj2012.0021 · DOI
  93. Batte, 2006, The economics of precision guidance with auto-boom control for farmer-owned agricultural sprayers, Comput. Electron. Agric., 53, 28, 10.1016/j.compag.2006.03.004 · DOI
  94. Oriade, 1996, A Bioeconomic Analysis of Site-Specific Management for Weed Control, Rev. Agric. Econ., 18, 523
  95. den Hond, F., Groenewegen, P., and van Straalen, N.M. (2003). Site-specific pest management. Pesticides—Problems, Improvements, Alternatives, Oxford. · doi:10.1002/9780470995457
  96. Stafford, J.V., and Werner, A. (2003). Precision farming in weed control—System components and economic benefits. Precision Agric, Wageningen Academic Publishers. · doi:10.3920/978-90-8686-514-7
  97. Vasileiadis, 2011, Crop protection in European maize-based cropping systems: Current practices and recommendations for innovative Integrated Pest Management, Agric. Syst., 104, 533, 10.1016/j.agsy.2011.04.002 · DOI
  98. Amado, 2013, Optimization of corn plant population according to management zones in Southern Brazil, Precis. Agric., 14, 450, 10.1007/s11119-013-9308-7 · DOI
  99. Bullock, 1998, Does variable rate seeding of corn pay?, Agron. J., 90, 830, 10.2134/agronj1998.00021962009000060019x · doi:10.2134/agronj1998.00021962009000060019x
  100. Lowenberg-DeBoer, J.M. (1998). Economics of Variable Rate Planting for Corn. Proceedings of the 4th International Conference on Precision Agriculture, Lafayette.
  101. Taylor, R.K., and Staggenborg, S. (2000, January 9–12). Using a GIS to Evaluate the Potential of Variable Rate Corn Seeding. Proceedings of the ASAE Meeting Presentation, Milwaukee, WI, USA.
  102. Shanahan, 2004, Feasibility of Site-Specific Management of Corn Hybrids and Plant Densities in the Great Plains, Precis. Agric., 5, 207, 10.1023/B:PRAG.0000032762.72510.10 · doi:10.1023/b:prag.0000032762.72510.10
  103. Lokhorst, C., Huijsmans, J.F.M., and de Louw, R.P.M. (2009). Variable rate seeding for French wheat production: Profitability and production risk management potential. JIAC2009 Book of Abstracts, Wageningen Academic Publishers. · doi:10.3920/978-90-8686-675-5
  104. Velandia, 2013, The economics of automatic section control technology for planters: A case study of middle and west Tennessee farms, Comput. Electron. Agric., 95, 1, 10.1016/j.compag.2013.03.006 · doi:10.1016/j.compag.2013.03.006
  105. Martelloni, L. (2014). Design and Realization of an Innovative Automatic Machine Able to Perform Site-Specific Thermal Weed Control in Maize. [Ph.D. Thesis, Università degli Studi di Firenze].
  106. Stafford, J.V. (2015). Precision harrowing with a flexible tine harrow and an ultrasonic sensor. Precision Agriculture ’15, Wageningen Academic Publishers. · doi:10.3920/978-90-8686-814-8
  107. Norremark, M. (2010, January 19–21). Technologies for precision weed control. Proceedings of the 3rd Conference of Precision crop Protection, Bonn, Germany.
  108. Peruzzi, A., Raffaelli, M., Ginanni, M., Lulli, L., Frasconi, C., and Fontanelli, M. (2008, January 15–17). Innovative operative machines for physical weed control on tomato in the Serchio Valley (Central Italy). Proceedings of the International Conference “Innovation Technology to Empower Safety, Health and Welfare in Agriculture and Agro-food Systems”, Ragusa, Italy.

Cited by

See all 672

Metadata

Authors
Balafoutis, A., Beck, B., Fountas, S., Vangeyte, J., Wal, T., Soto, I., Gómez-Barbero, M., Barnes, A., & Eory, V.
Venue
Sustainability
Publisher
MDPI AG
Published
2017-07-31
Volume
9
Issue
8
Pages
1339
ISSN
2071-1050 (ISSN-L)
OpenAlex
W2741850261
Cited by
672
References
1
FWCI
23.93
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. https://app.cochat.ai/papers/10.3390/su9081339
The paper
Balafoutis, A., Beck, B., Fountas, S., Vangeyte, J., Wal, T., Soto, I., Gómez-Barbero, M., Barnes, A., & Eory, V. (2017). Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. Sustainability. https://doi.org/10.3390/su9081339

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.