Abstract
Climate change is one of the biggest challenges of our times, and we are steadily marching towards a climate catastrophe. Among the various sectors which is fuelling the climate change through emission of greenhouse gases (GHGs), the contribution of agricultural sector is 24%. Unscientific farm management practices like imprudent fertilizer and pesticide application, livestock management practices, land use changes etc. are the driving forces which have led to increased GHG emissions from agriculture. Thus, strategies to reduce the emission and its subsequent impact on the changing climate is the need of the hour, as agriculture besides being a contributor is also one of the most vulnerable sectors affected by climate change. Precision farming or precision agriculture (PA) is one such instrument which is effective in making agriculture more ‘climate smart’ by reducing its impact on the environment. This technique of farming employs right management practices at the right place and time by capturing the heterogeneity of the land at a minute scale. Thus, PA is a technology intensive system, which requires the assistance of Global Positioning System; different sensors for monitoring soil moisture, nutrients etc. and geo-referenced maps for different soil properties but when adopted at a large scale would help to improve the productivity, increase the saving of resources and reduce the environmental impact. PA is the modern-day climate-smart agriculture strategy, which could answer the problem of food insufficiency in developing countries and emerge as a powerful tool, as well as solution to the innumerable challenges faced by the agriculture sector.
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References
Adamchuk VI, Christenson PT (2005) An integrated system for mapping soil physical properties on-the-go: the mechanical sensing component. In: Stafford J (ed) Precision agriculture: papers from the fifth European conference on precision agriculture, Uppsala, Sweden, 9–12 June 2005. Wageningen Academic Publishers, Wageningen, pp 449–456
Adamchuk VI, Morgan MT, Ess DR (1999) An automated sampling system for measuring soil pH. Trans ASAE 42(4):885
Adamchuk VI, Hummel JW, Morgan MT, Upadhyaya SK (2004) On-the-go soil sensors for precision agriculture. Comput Electron Agric 44(1):71–91
Adamchuk VI, Lund E, Sethuramasamyraja B, Morgan MT, Dobermann A, Marx DB (2005) Direct measurement of soil chemical properties on-the-go using ion-selective electrodes. Comput Electron Agric 48:272–294
Adsett JF, Thottan JA, Sibley KJ (1999) Development of an automated on-the-go soil nitrate monitoring system. Appl Eng Agric 15(4):351
Angers DA, Eriksen-Hamel NS (2008) Full-inversion tillage and organic carbon distribution in soil profiles: a meta-analysis. Soil Sci Soc Am J 72(5):1370–1374
Artigas J, Beltran A, Jimenez C, Baldi A, Mas R, Domınguez C, Alonso J (2001) Application of ion sensitive field effect transistor based sensors to soil analysis. Comput Electron Agric 31(3):281–293
Aziz FAA, Shariff ARM, Amin BM, Mohd S, Rahim AA, Jahanshiri E, Che’Ya NN (2008) GIS based system for paddy precision farming. In: Iaald Afita WCCA 2008 world conference on agricultural information and IT, 24–27 Aug. Tokyo University of Agriculture, Tokyo, pp 417–422
Babcock BA, Paustian K, Hatfield J, Kling CL, Lal R, McCarl B, McLaughlin S, Mosier A, Post W, Robertson GP (2004) Climate change and greenhouse gas mitigation: challenges and opportunities for agriculture. Council on Agricultural Science and Technology (CAST), Ames, IA
Bah A, Balasundram SK, Husni MHA (2012) Sensor technologies for precision soil nutrient management and monitoring. Am J Agric Biol Sci 7(1):43–49
Baharom SNA, Shibusawa S, Kodaira M, Kanda R (2015) Multiple-depth mapping of soil properties using a visible and near infrared real-time soil sensor for a paddy field. Eng Agric Environ Food 8(1):13–17
Balafoutis A, Bert 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 9(8):1339
Bates J, Brophy N, Harfoot M, Webb J (2009) Sectoral emission reduction potentials and economic costs for climate change (SERPEC-CC). In: Agriculture: methane and nitrous oxide. Ecofys, Utrecht
Batte MT, Arnholt MW (2003) Precision farming adoption and use in Ohio: case studies of six leading-edge adopters. Comput Electron Agric 38(2):125–139
Batte MT, Van Buren FN (1999) Precision farming—factor influencing productivity. Paper presented at the Northern Ohio Crops Day meeting, Wood County, Ohio, 21 Jan 1999
Baumgardner MF, Silva LF, Biehl LL, Stoner ER (1986) Reflectance properties of soils. Adv Agron 38:1–44
Bhatti AU, Mulla DJ, Frazier BE (1991) Estimation of soil properties and wheat yields on complex eroded hills using geostatistics and thematic mapper images. Remote Sens Environ 37(3):181–191
Bianchini AA, Mallarino AP (2002) Soil-sampling alternatives and variable-rate liming for a soybean—corn rotation. Agron J 94:1355–1366
Birrell SJ, Hummel JW (2000) Membrane selection and ISFET configuration evaluation for soil nitrate sensing. Trans ASAE 43(2):197
Bolotova Y (2006) Crop production using variable rate technology for PK in the United States midwest: evaluation of profitability (no. 379-2016-21882)
Christy C, Collings K, Drummond P Lund E (2004) A mobile sensor platform for measurement of soil pH and buffering. ASAE paper number: 041042. ASAE, St. Joseph, MI
Climate Central (2017). https://www.climatecentral.org/news/earth-day-climate-trends-18907
Crookston K (2006) A top 10 list of developments and issues impacting crop management and ecology during the past 50 years. Crop Sci 46:2253–2262
Donovan P (2012) Measuring soil carbon change. A flexible, practical, local method. https://soilcarboncoalition.org/files/MeasuringSoilCarbonChange.pdf
EEA (2015). https://www.eea.europa.eu/themes/climate-change-adaptation/intro
Elshorbagy A, Parasuraman K (2008) On the relevance of using artificial neural networks for estimating soil moisture content. J Hydrol 362(1–2):1–18
Eory V, Moran D (2012) Review of potential measures for RPP2-agriculture. http://www.climatexchange.org.uk/files/3413/7338/8148/
Esfahani LH, Torres-Rua A, McKee M (2015) Assessment of optimal irrigation water allocation for pressurized irrigation system using water balance approach, learning machines, and remotely sensed data. Agric Water Manag 153:42–50
Fitzgerald GJ, Maas SJ, Detar WR (2004) Spider mite detection and canopy component mapping in cotton using hyperspectral imagery and spectral mixture analysis. Precis Agric 5(3):275–289
Fulton JP, Sobolik CJ, Shearer SA, Higgins SF, Burks TF (2009) Grain yield monitor flow sensor accuracy for simulated varying field slopes. Appl Eng Agric 25(1):15–21
Gillies RR, Carlson TN (1995) Thermal remote sensing of the surface soil water content with partial vegetation cover for incorporation into climate models. J Appl Meteorol 34:745–756
Goulding K, Jarvis S, Whitmore A (2008) Optimizing nutrient management for farm systems. Philos Trans R Soc B 363:667–680. https://doi.org/10.1098/rstb.2007.2177
He Y, Huang M, García A, Hernández A, Song H (2007) Prediction of soil macronutrients content using near-infrared spectroscopy. Comput Electron Agric 58(2):144–153
Hellebrand HJ, Umeda M (2004) Soil and plant sensing for precision agriculture. Precis Agric 2(3):247–254
International Energy Agency, IEA (2011). https://www.iea.org/newsroom/news/2012/may/global-carbon-dioxide-emissions-increase-by-10-gt-in-2011-to-record-high.html
International Finance Corporation, IFC (2017). https://www.ifc.org/wps/wcm/connect/
IPCC (2014) In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects. Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, p 1132
Jain N, Ray SS, Singh JP, Panigrahy S (2007) Use of hyperspectral data to assess the effects of different nitrogen applications on a potato crop. Precis Agric 8(4–5):225–239
Jonjak AK, Adamchuk VI, Wortmann CS, Ferguson RB, Shapiro CA (2010) A comparison of conventional and sensor-based lime requirement maps. In: Kholsa R (ed) Proceedings of the tenth international conference on precision agriculture, Denver, Colorado, 18–21 July 2010. Colorado State University, Fort Collins, CO
Keskin M, Han YJ, Dodd RB (1999) A review of yield monitoring instrumentation applied to the combine harvesters for precision agriculture purposes. In: Seventh international congress on agricultural mechanization and energy, 26–27 May 1999, Adana, Turkey, pp 426–431
Khan SA, Mulvaney RL, Ellsworth TR, Boast CW (2007) The myth of nitrogen fertilization for soil carbon sequestration. J Environ Qual 36(6):1821–1832
Kim CG (2008) The impact of climate change on the agricultural sector: implications of the agro-industry for low carbon, green growth strategy and roadmap for the East Asian region. Korea Rural Economic Institute, Naju
Kim HJ, Hummel JW, Birrell SJ (2006) Evaluation of nitrate and potassium ion-selective membranes for soil macronutrient sensing. Trans ASABE 49(3):597–606
Kim HJ, Sudduth KA, Hummel JW (2009) Soil macronutrient sensing for precision agriculture. J Environ Monit 11(10):1810–1824
Kristof SJ (1971) Preliminary multispectral studies of soil. J Soil Water Conserv 26:15–18
Link A, Panitzki M, Reusch S (2002) Hydro N-sensor: tractor mounted remote sensing for variable nitrogen fertilization. In: Robert PC (ed) Proceedings of the 6th international conference on precision agriculture and other precision resources management [CD-ROM]. ASA, CSSA, and SSSA, Madison, WI, pp 1012–1018
Lipper L, Thornton P, Campbell B et al (2014) Climate-smart agriculture for food security. Nat Clim Chang 4:1068–1072. https://doi.org/10.1038/nclimate2437
Liu D, Wang Z, Zhang B, Song K, Li X, Li J, Li F, Duan H (2006) Spatial distribution of soil organic carbon and analysis of related factors in croplands of the black soil region, Northeast China. Agric Ecosyst Environ 113(1–4):73–81
Liu CY, Wang K, Meng S, Zheng XH, Zhou ZX, Han SH, Chen D, Yang ZP (2011) Effects of irrigation, fertilization and crop straw management on nitrous oxide and nitric oxide emissions from a wheat-maize rotation field in northern China. Agric Ecosyst Environ 140:226–233
Livesly SJ, Dougherty BJ, Smith AJ, Navaud D, Wylie LJ, Arndt SK (2010) Soil-atmosphere exchange of carbon dioxide, methane and nitrous oxide in urban garden systems: impact of irrigation, fertilizer and mulch. Urban Ecosyst 13:273–293
Lund ED, Collings KL, Drummond PE, Christy CD, Adamchuk VI (2004) Managing pH variability with on-the-go pH mapping. In: Proceedings of the seventh international conference on precision agriculture, pp 120–132
Lund ED, Adamchuk VI, Collings KL, Drummond PE, Christy CD (2005) Development of soil pH and lime requirement maps using on-the-go soil sensors. In: Stafford J (ed) Precision agriculture: papers from the fifth European conference on precision agriculture, Uppsala, Sweden, 9–12 June 2005. Wageningen Academic Publishers, Wageningen, pp 457–464
Mackay D (2012) Precision farming: connecting the pieces. http://www.personal.psu.edu/pwl5119/blogs/bill_lim/assets/Limpisathian
MacLeod M, Eory V, Gruere G, Lankoski J (2015) Cost-effectiveness of greenhouse gas mitigation measures for agriculture, vol 89. OECD Publishing, Paris
Mandal SK, Maity A (2013) Precision farming for small agricultural farm: Indian scenario. Am J Exp Agric 3(1):200
Montzka SA, Dlugokencky EJ, Butler JH (2011) Non-CO2 greenhouse gases and climate change. Nature 476(7358):43
Mouazen AM, De Baerdemaeker J, Ramon H (2005) Towards development of on-line soil moisture content sensor using a fibre-type NIR spectrophotometer. Soil Tillage Res 80(1–2):171–183
Mulla DJ (1997) Geostatistics, remote sensing and precision farming. In: Precision agriculture: spatial and temporal variability of environmental quality. Wiley, Chichester, pp 100–119
Mulla DJ (2013) Twenty five years of remote sensing in precision agriculture: key advances and remaining knowledge gaps. Biosyst Eng 114(4):358–371
National Research Council (NRC) (1997) Precision agriculture in the 21st century. (Committee on assessing crop yield: site-specific farming, information systems, and research opportunities). National Academy Press, Washington, DC, p 149
Neményi M, Mesterházi PÁ, Pecze Z, Stépán Z (2003) The role of GIS and GPS in precision farming. Comput Electron Agric 40(1–3):45–55
Nielsen HJ, Hansen EH (1976) New nitrate ion-selective electrodes based on quaternary ammonium compounds in nonporous polymer membranes. Anal Chim Acta 85(1):1–16
Pan Y, Koopmans GF, Bonten LT, Song J, Luo Y, Temminghoff EJ, Comans RN (2015) In-situ measurement of free trace metal concentrations in a flooded paddy soil using the Donnan Membrane Technique. Geoderma 241:59–67
Park SJ, Vlek PLG (2002) Environmental correlation of three-dimensional soil spatial variability: a comparison of three adaptive techniques. Geoderma 109:117–140
Plant R, Pettygrove G, Reinert W (2000) Precision agriculture can increase profits and limit environmental impacts. Calif Agric 54(4):66–71
Raun WR, Solie JB, Johnson GV, Stone ML, Mullen RW, Freeman KW, Lukina EV (2002) Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agron J 94(4):815–820
Rossel RV, Walter C (2004) Rapid, quantitative and spatial field measurements of soil pH using an ion sensitive field effect transistor. Geoderma 119(1–2):9–20
Rossel RV, Walvoort DJJ, McBratney AB, Janik LJ, Skjemstad JO (2006) Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma 131(1–2):59–75
Rossel RV, Rizzo R, Demattê JAM, Behrens T (2010) Spatial modeling of a soil fertility index using visible–near-infrared spectra and terrain attributes. Soil Sci Soc Am J 74(4):1293–1300
Schepers JS, Francis DD, Vigil M, Below FE (1992) Comparison of corn leaf nitrogen concentration and chlorophyll meter readings. Commun Soil Sci Plant Anal 23(17–20):2173–2187
Seelan SK, Laguette S, Casady GM, Seielstad GA (2003) Remote sensing applications for precision agriculture: a learning community approach. Remote Sens Environ 88(1–2):157–169
Sehy U, Ruser R, Munch JC (2003) Nitrous oxide fluxes from maize fields: relationship to yield, site-specific fertilization, and soil conditions. Agric Ecosyst Environ 99:97–111
Shibusawa S (2001) Precision farming approaches for small scale farms. IFAC Proc Vol 34(11):22–27
Shonk JL, Gaultney LD, Schulze DG, Van Scoyoc GE (1991) Spectroscopic sensing of soil organic matter content. Trans ASAE. 34(5):1978–1984
Simojoki A, Jaakkola A (2000) Effect of nitrogen fertilization, cropping and irrigation on soil air composition and nitrous oxide emissions in a loamy clay. Eur J Soil Sci 51:413–424
SKY-Farm (1999) Opportunities for precision framing in Europe: updated report 1999, p 126
Smith P, Bustamante M, Ahammad H et al (2014) Agriculture, forestry and other land use (AFOLU). In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds) Climate change 2014: mitigation of climate change. Contribution of working group III to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Sun Y, Schulze Lammers P, Ma D, Lin J, Zeng Q (2008) Determining soil physical properties by multi-sensor technique. Sensors Actuators 147:352–357
Tekin AB (2010) Variable rate fertiliser application in Turkish wheat agriculture: economic assessment. Afr J Agric Res 5:647–652
Tercek M (2018). https://www.nature.org/en-us/explore/magazine/magazine-articles/the-climate-challenge-unites-us
Tran DV, Nguyen NV (2006) The concept and implementation of precision farming and rice integrated crop management systems for sustainable production in the twenty-first century. Int Rice Comm Newsl 55:91–102
Trost B, Prochnow A, Drastig K, Meyer-Aurich A, Ellmer F, Baumecker M (2013) Irrigation, soil organic carbon and N2O emissions. Agron Sustain Dev 33:733–749
Vachaud G, Passerat de Silans A, Balabanis P, Vauclin M (1985) Temporal stability of spatially measured soil water probability density function 1. Soil Sci Soc Am J 49(4):822–828
Venkatramanan V, Shah S (2019) Climate smart agriculture technologies for environmental management: the intersection of sustainability, resilience, wellbeing and development. In: Shah S et al (eds) Sustainable green technologies for environmental management. Springer Nature Singapore Pte Ltd., Singapore, pp 29–51. https://doi.org/10.1007/978-981-13-2772-8_2
Victor DG, Zhou D, Ahmed EHM, Dadhich PK, Olivier JGJ, Rogner HH, Sheikho K, Yamaguchi M (2014) Introductory chapter. In: Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann B, Savolainen J, Schlömer S, von Stechow C, Zwickel T, Minx JC (eds) Climate change 2014: mitigation of climate change. Contribution of working group III to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Waldrop MP, Zak DR, Sinsabaugh RL, Gallo M, Lauber C (2004) Nitrogen deposition modifies soil carbon storage through changes in microbial enzymatic activity. Ecol Appl 14(4):1172–1177
Whalley WR (1991) Development and evaluation of a microwave soil moisture sensor for incorporation in a narrow cultivator tine. J Agric Eng Res 50:25–33
Xiao D, Yuan HY, Li J, Yu RQ (1995) Surface-modified cobalt-based sensor as a phosphate-sensitive electrode. Anal Chem 67(2):288–291
Yang HQ, Kuang BY, Mouazen AM (2011) Prediction of soil TN and TC at a farm-scale using VIS-NIR spectroscopy. Adv Mater Res 225:1258–1261
Yousefi MR, Razdari AM (2015) Application of GIS and GPS in precision agriculture (a review). Int J Adv Biol Biomed Res 3(1):7–9
Yufeng GE, Thomasson JA, Sui R (2011) Remote sensing of soil properties in precision agriculture: a review. Front Earth Sci 5(3):229–238
Zhang Q (2015) Precision agriculture technology for crop farming. CRC Press, Boca Raton, FL
Zhang XY, Sui YY, Zhang XD, Meng K, Herbert SJ (2007) Spatial variability of nutrient properties in black soil of Northeast China. Pedosphere 17:19–29
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Roy, T., George K, J. (2020). Precision Farming: A Step Towards Sustainable, Climate-Smart Agriculture. In: Venkatramanan, V., Shah, S., Prasad, R. (eds) Global Climate Change: Resilient and Smart Agriculture. Springer, Singapore. https://doi.org/10.1007/978-981-32-9856-9_10
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