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Review Articles

Vol. 12 No. 2 (2025)

Weather based agro advisory services in promoting sustainable agriculture: A review

DOI
https://doi.org/10.14719/pst.7357
Submitted
22 January 2025
Published
18-05-2025 — Updated on 27-05-2025
Versions

Abstract

Agricultural production is closely linked with weather conditions, as fluctuations in temperature, rainfall, wind patterns and humidity significantly influence crop productivity. Adverse weather events often lead to considerable crop losses, emphasizing the need for timely and accurate weather information. Weather Based Agro Advisory Services (WBAAS) play a pivotal role in bridging this gap by providing farmers with real-time and forecasted weather information, enabling them to adopt strategic measures to mitigate risks and optimize agricultural outputs. WBAAS offers customized guidance based on weather predictions, including optimal sowing times, irrigation scheduling, pest and disease management and post-harvest strategies. By receiving accurate and timely advisories on parameters such as temperature, relative humidity, wind speed and rainfall, farmers can make informed decisions, reducing the likelihood of crop failure and improving yield quality and quantity. These services not only aid in minimizing production losses but also enhance economic returns by promoting resource efficiency and sustainable farming practices. The integration of technological innovations into weather based agro advisory services further strengthens their impact, facilitating the dissemination of precise weather data through mobile applications, SMS alerts and other digital platforms. Studies have demonstrated the transformative potential of these services in improving farmers' adaptive capacity and resilience against climate variability. This review analyses studies on how farmers utilize technological innovations combined with weather-based information to enhance agricultural productivity. It examines the impact of weather based agro advisory services on agriculture and explores their broader role in achieving sustainable farming practices and addressing challenges posed by climate change.

References

  1. 1. Beillouin D, Schauberger B, Bastos A, Ciais P, Makowski D. Impact of extreme weather conditions on European crop production in 2018. Philosophical Transactions of the Royal Society B. 2020;375(1810):20190510. https://doi.org/10.6084/m9.figshare.c.5077861.v2
  2. 2. Singh KK, Baxla AK, Singh P, Singh PK. Weather based information on risk management in agriculture. Climate change and agriculture in India: Impact and Adaptation. 2019:207-16. https://doi.org/10.1007/978-3-319-90086-5_16
  3. 3. Shil S. Weather parameters and its impact on agricultural production-A review. Innovative Farming. 2018;3(4):141-49.
  4. 4. Khobragade AM, Ade AU, Vaseem Ahmed MG. Usefulness of Agro advisory services (AAS) regarding climate change in selected villages of AICRPAM-NICRA project for Marathwada region. Journal of Agroecology and Natural Resource Management. 2014;1(3):127-29.
  5. 5. Dharanipriya A, Karthikeyan C, Panneerselvam S. Understanding the farmers’ preference for designing weather based agro advisory services. Journal of Pharmacognosy and Phytochemistry. 2019;8(3):870-73.
  6. 6. Ukhurebor KE, Adetunji CO, Olugbemi OT, Nwankwo W, Olayinka AS, Umezuruike C, et al. Precision agriculture: Weather forecasting for future farming. InAi, edge and iot-based smart agriculture. 2022:101-21. https://doi.org/10.1016/B978-0-12-823694-9.00008-6
  7. 7. Mase AS, Prokopy LS. Unrealized potential: A review of perceptions and use of weather and climate information in agricultural decision making. Weather, Climate and Society. 2014;6(1):47-61. https://doi.org/10.1175/WCAS-D-12-00062.1
  8. 8. Chaubey D, Prakash V, Patel AB, Yadav TC. Role of Agro-Meteological Advisory Services on risk mitigation in agriculture. International Journal of Pure and Applied Bioscience. 2018;6:27-32.
  9. 9. Dupdal R, Dhakar R, Rao CR, Samuel J, Raju BM, Kumar PV, et al. Farmers’ perception and economic impact assessment of agromet advisory services in rainfed regions of Karnataka and Andhra Pradesh. Journal of Agrometeorology. 2020;22(3):258-65. https://doi.org/10.54386/jam.v22i3.187
  10. 10. Singh M, Ghanghas BS, Sharma V, Sharma BC. Minimize weather risk in agricultural planning and management through agromet advisory services in rural areas. Transformation of Indian agriculture through innovative technologies. Daya Publishing House, Delhi, India. 2019:11-21.
  11. 11. Ministry of Earth Sciences, India. 2023. https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1913976
  12. 12. Ebhuoma EE, Simatele MD, Leonard L, Ebhuoma OO, Donkor FK, Tantoh HB. Theorising indigenous farmers’ utilisation of climate services: Lessons from the oil-rich Niger Delta. Sustainability. 2020;12(18):7349. https://doi.org/10.3390/su12187349
  13. 13. Doss DA, Asokhan M. Awareness on Weather Based Agro-advisory Services among farmers of Tamil Nadu, India. International Journal of Environment and Climate Change. 2024;14(3):177-82. https://doi.org/10.9734/ijecc/2024/v14i34030
  14. 14. Suciu G, Ijaz H, Zatreanu I, Dr?gulinescu AM. Real time analysis of weather parameters and smart agriculture using IoT. In future access enablers for ubiquitous and intelligent infrastructures: 4th EAI International Conference, FABULOUS 2019, Sofia, Bulgaria, Proceedings 283. Springer International Publishing. 2019:181-94. https://doi.org/10.1007/978-3-030-23976-3_18
  15. 15. Raj M, Gupta S, Chamola V, Elhence A, Garg T, Atiquzzaman M, et al. A survey on the role of internet of things for adopting and promoting agriculture 4.0. Journal of Network and Computer Applications. 2021;187:103107. https://doi.org/10.1016/j.jnca.2021.103107
  16. 16. Harshini A, Babu KM, Reddy CV, Suhasini K. Awareness of farmers on Weather Based Agro Advisory Services in Telangana State, India. International Journal of Environment and Climate Change. 2023;13(10):355-65. https://doi.org/10.9734/IJECC/2023/v13i102648
  17. 17. Kumar Y, Fatima K, Raghuvanshi MS, Nain MS, Sofi M. Impact of Meghdoot mobile app- A weather-based agro-advisory service in cold arid Ladakh. Indian Journal of Extension Education. 2022;58(3):142-46. https://doi.org/10.48165/IJEE.2022.58329.
  18. 18. Zhang Y, Wang L, Duan Y. Agricultural information dissemination using ICTs: A review and analysis of information dissemination models in China. Information Processing in Agriculture. 2016;3(1):17-29. https://doi.org/10.1016/j.inpa.2015.11.002.
  19. 19. Sanga C, Mlozi MR, Tumbo S, Mussa M, Sheto MC, Mwamkinga GH, et al. On search for strategies to increase the coverage of agricultural extension service: Web-based Farmers' Advisory Information System. International Journal of Computing & ICT Research. 2013;7(1).
  20. 20. Lobo C. Mobile phone delivered weather-based crop advisories in India: The case for an integrated approach. Watershed Organization Trust, Policy Brief. 2015:4.
  21. 21. Dharanipriya A, Sumathi P, Balasubramaniam P, Karthikeyan C. Dryland farmers’ adaptive behaviour towards climate variability. Madras Agricultural Journal. 2022;109(special):1:34-8. https://doi.org/10.29321/MAJ.10.000630
  22. 22. Ayaz M, Ammad-Uddin M, Sharif Z, Mansour A, Aggoune EH. Internet-of-things (IoT)-based smart agriculture: Toward making the fields talk. IEEE access. 2019;7:129551-83. https://doi.org/10.1109/ACCESS.2019.2932609
  23. 23. Caine A, Dorward P, Clarkson G, Evans N, Canales C, Stern D, et al. Mobile applications for weather and climate information: Their use and potential for smallholder farmers. CCAFS Working Paper. 2015.
  24. 24. Soyemi J, Adesi AB. A Web-based decision support system with SMS-based technology for agricultural information and weather forecasting. International Journal of Computer Applications. 2018;180(16):1-6. https://doi.org/10.5120/ijca2018916338
  25. 25. Kumar V, Kumar A, Sharma AK, Singh D. Web-AAS: A Web-based extension tool for dissemination of advisory bulletins. Indian Resarch Journal of Extension Education. 2015;15(4):234-36.
  26. 26. Manjusha K, Nitin P, Suvarna D, Vinaykumar HM. Exposure, perception and advantages about weather based agro advisory services by selected farmers of Anand District, India. International Journal of Current Microbiology and Applied Sciences. 2019;8(5):1934-44. https://doi.org/10.20546/ijcmas.2019.805.224.
  27. 27. Ratiya PB, Thakor RF, Solanki AH. Perception of farmers towards Agromet Advisory Service. Journal of Krishi Vigyan. 2022;11(1):289-92. https://doi.org/10.5958/2349-4433.2022.00144.1
  28. 28. Bierhoff HW. Person perception and attribution. Springer Science & Business Media. 2012.
  29. 29. Rajesh R, Mehta SK, Autade CD, Godara AK. The farmer's perception about weather forecasting advisory services. Asian science. 2016;11(2):98-104. https://doi.org/10.15740/HAS/AS/11.2/98-104
  30. 30. Dupdal R, Manjunatha BL, Dhakar R, Patil SL. Perception and economic impact of agromet advisory services: A case study of Thrissur AICRPAM centre of Kerala state. Indian Journal of Extension Education. 2020;56(3):10-16.
  31. 31. Dupdal R. Awareness and perception of farmers about weather based agromet advisory services: Evidence from Vijayapura district of Karnataka, India. Education (No.). 2023;12(2):23-7.
  32. 32. Kumar U, Werners SE, Paparrizos S, Datta DK, Ludwig F. Co-producing climate information services with smallholder farmers in the Lower Bengal Delta: How forecast visualization and communication support farmers’ decision-making. Climate Risk Management. 2021;33:100346. https://doi.org/10.1016/j.crm.2021.100346
  33. 33. Chaitanya TS, Babu TM, Veeraiah A, Maheswari KS, Mamatha A. Usage of agromet advisory services among the farmers of YSR District of Andhra Pradesh, India. International Journal of Plant & Soil Science. 2022;34(24):304-10. https://doi.org/10.9734/IJPSS/2022/v34i242643
  34. 34. Hanif NA, NK S. Adoption behavior among farmers of Tamil Nadu towards District Agro-meteorology Unit (DAMU) Agro Advisory Services in agriculture and allied Sectors. International Journal of Environment and Climate Change. 2023;13(10):1817-24. https://doi.org/10.9734/IJECC/2023/v13i102837
  35. 35. Naik FA, Manhas JS. Adoption of weather based agro-advisory services in Jammu district of J&K. Indian Journal of Extension Education. 2022;58(4):49-53.
  36. 36. Elias EH, Flynn R, Idowu OJ, Reyes J, Sanogo S, Schutte BJ, et al. Crop vulnerability to weather and climate risk: Analysis of interacting systems and adaptation efficacy for sustainable crop production. Sustainability. 2019;11(23):6619. https://doi.org/10.3390/su11236619
  37. 37. Bal SK, Sarath Chandran MA. Minimizing weather-related risks in agriculture through Agromet Advisory Services in India. Climate change and resilient food systems: Issues, Challenges and Way Forward. 2021:245-60. https://doi.org/10.1007/978-981-33-4538-6_9
  38. 38. WMO. Future of weather and climate forecasting. WMO open consultative platform white paper No 1. 2021. https://library.wmo.int/doc_num.php?explnum_id=10611
  39. 39. Khan N, Kumar A, Singh CB, Dubey V, Kumar N. Weather based agro-met advisory to enhance the production and income of the farmers under changing climate scenario of Central Plain Zone of Uttar Pradesh, India. International Journal of Current Microbiology and Applied Sciences. 2018;7(11):221-24. https://doi.org/10.20546/ijcmas.2018.711.027
  40. 40. Graham LP, Andersson L, Toucher MW, Wikner JJ, Wilk J. Seasonal local rainfall and hydrological forecasting for Limpopo communities–A pragmatic approach. Climate Services. 2022;27:100308. https://doi.org/10.1016/j.cliser.2022.100308
  41. 41. Nepal M, Ashfaq M, Sharma BR, Shrestha MS, Khadgi VR, Bruno Soares M. Impact of weather and climate advisories on agricultural outcomes in Pakistan. Scientific Reports. 2024;14(1):1036. https://doi.org/10.1038/s41598-023-51066-4
  42. 42. Falco C, Donzelli F, Olper A. Climate change, agriculture and migration: A survey. Sustainability. 2018;10(5):1405. https://doi.org/10.3390/su10051405.
  43. 43. Hansen J, Hellin J, Rosenstock T, Fisher E, Cairns J, Stirling C, et al. Climate risk management and rural poverty reduction. Agricultural Systems. 2019;172:28-46. https://doi.org/10.1016/j.agsy.2018.01.019
  44. 44. Jayalakshmi M, Mahadevaiah M, Prasadbabu G, Sivaramakrishna M. Weather-based Agro advisory services: Impact on cotton yield, economics and perception of farmers in rainfed areas of the Kurnool District Andhra Pradesh, India. 2023;29(3):1053-59. http://doi.org/10.53550/EEC.2023.v29i03.005
  45. 45. Patel N, Dixit AK, Singh SR. Effectiveness of whatsapp messages regarding improved agricultural production technology. Indian Journal of Extension Education. 2020;56(1):54-8.
  46. 46. Kumar Y, Raghuvanshi MS, Fatima K, Nain MS, Manhas JS, Namgyal D, et al. Impact assessment of weather based agro-advisory services of Indus plain farming community under cold arid Ladakh. Mausam. 2021;72(4):897-904. https://doi.org/10.54302/mausam.v72i4.3556
  47. 47. Ramachandrappa BK, Thimmegowda MN, Krishnamurthy R, Babu PN, Savitha MS, Srinivasarao C, Gopinath KA, et al. Usefulness and impact of agromet advisory services in eastern dry zone of Karnataka. Indian Journal of Dryland Agricultural Research and Development. 2018;33(1):32-6. https://doi.org/6701.2018.00005.2
  48. 48. Jaidka M, Bathla S, Kaur R. Improved technologies for higher maize production. In Maize-production and use, London, UK: IntechOpen. 2019.https://doi.org/10.5772/intechopen.88997
  49. 49. Buckland S, Campbell D. Agro-climate services and drought risk management in Jamaica: A case study of farming communities in Clarendon Parish. Singapore Journal of Tropical Geography. 2022;43(1):43-61. https://doi.org/10.1111/sjtg.12414
  50. 50. Muema E, Mburu J, Coulibaly J, Mutune J. Determinants of access and utilisation of seasonal climate information services among smallholder farmers in Makueni County, Kenya. Heliyon. 2018;4(11). https://doi.org/10.1016/j.heliyon.2018. e00889.
  51. 51. Oyekale AS. Access to risk mitigating weather forecasts and changes in farming operations in East and West Africa: Evidence from a baseline survey. Sustainability. 2015;7(11):14599-617. https://doi.org/10.3390/su71114599.
  52. 52. Alant BP, Bakare OO. A case study of the relationship between smallholder farmers' ICT literacy levels and demographic data wrt their use and adoption of ICT for weather forecasting. Heliyon. 2021;7(3). https://doi.org/10.1016/j.heliyon.2021. e06403.
  53. 53. Paparrizos S, Kumar U, Amjath-Babu TS, Ludwig F. Are farmers willing to pay for participatory climate information services? Insights from a case study in peri-urban Khulna, Bangladesh. Climate Services. 2021;23:100241. https://doi.org/10.1016/j.cliser.2021.100241.
  54. 54. Kolawole OD, Wolski P, Ngwenya B, Mmopelwa G. Ethno-meteorology and scientific weather forecasting: Small farmers and scientists’ perspectives on climate variability in the Okavango Delta, Botswana. Climate risk management. 2014;4:43-58. https://doi.org/10.1016/j.crm.2014.08.002
  55. 55. Muita R, Dougill A, Mutemi J, Aura S, Graham R, Awolala D, et al. Understanding the role of user needs and perceptions related to sub-seasonal and seasonal forecasts on farmers' decisions in Kenya: A systematic review. Frontiers in Climate. 2021;3:580556. https://doi.org/10.3389/fclim.2021.580556.
  56. 56. Henriksson R, Vincent K, Archer E, Jewitt G. Understanding gender differences in availability, accessibility and use of climate information among smallholder farmers in Malawi. Climate and Development. 2021;13(6):503-14. https://doi.org/10.1080/17565529.2020.1806777
  57. 57. Roncoli C, Ingram K, Kirshen P. Reading the rains: Local knowledge and rainfall forecasting in Burkina Faso. Society & Natural Resources. 2002;15(5):409-27. https://doi.org/10.1080/08941920252866774.
  58. 58. Ruzol C, Lomente LL, Pulhin J. Mapping access and use of weather and climate information to aid farm decisions in the Philippines. Philipp Agric Sci. 2020;103(Sp):25-39.
  59. 59. Chiputwa B, Wainaina P, Nakelse T, Makui P, Zougmoré RB, Ndiaye O, et al. Transforming climate science into usable services: The effectiveness of co-production in promoting uptake of climate information by smallholder farmers in Senegal. Climate services. 2020;20:100203. https://doi.org/10.1016/j. cliser.2020.100203.
  60. 60. Amegnaglo CJ, Anaman KA, Mensah-Bonsu A, Onumah EE, Gero FA. Contingent valuation study of the benefits of seasonal climate forecasts for maize farmers in the Republic of Benin, West Africa. Climate Services. 2017;6:1. https://doi.org/10.1016/j.cliser.2017.06.007
  61. 61. Nyadzi E, Werners ES, Biesbroek R, Long PH, Franssen W, Ludwig F. Verification of seasonal climate forecast toward hydroclimatic information needs of rice farmers in Northern Ghana. Weather, Climate and Society. 2019;11(1):127-42. https://doi.org/10.1175/WCAS-D-17-0137.1.
  62. 62. Nkuba MR, Chanda R, Mmopelwa G, Kato E, Mangheni MN, Lesolle D. Influence of indigenous knowledge and scientific climate forecasts on arable farmers’ climate adaptation methods in the Rwenzori region, Western Uganda. Environmental Management. 2020;65:500-16. https://doi.org/10.1007/s00267-020-01264-x.
  63. 63. Vogel C. Usable science: An assessment of long-term seasonal forecasts amongst farmers in rural areas of South Africa. South African Geographical Journal. 2000;82(2):107-16. https://doi.org/10.1080/03736245.2000.9713700
  64. 64. Satishkumar N, Tevari P, Singh A. Utilization pattern of different sources and channels of weather information by the rainfed farmers. Indian Journal of Agricultural Research. 2013;47(3):248-52.
  65. 65. Nargawe L, Mishra YD. Constraints and suggestions faced by the scientists/service providers and beneficiaries of kisan mobile advisory services in Barwani district of Madhya Pradesh. Journal of Pharmacognosy and Phytochemistry. 2019;8(1S):487-89.
  66. 66. Chavhan PN. Constraints faced and suggestions provided during the use of mobile based agro advisory services by state department of agriculture in Marathwada region. IJCS. 2018;6(3):1715-19.
  67. 67. Patil KV, Patel VT, Prajapati RR. Constraints in using Kisan Mobile Advisory Service as perceived by farmers in Banaskantha District of Gujarat, India. Int J Curr Microbiol App Sci. 2017;6(11):237-40. https://doi.org/10.20546/ijcmas.2017.611.028
  68. 68. Neeralgi AF, Santhosha HM, Manju MJ. Study on constraints affecting the use of Kisan Mobile Advisory Services in Uttara Kannada District, India. Int J Curr Microbio App Sci. 2019;8(7):2641-46. https://doi.org/10.20546/ijcmas.2019.807.325.
  69. 69. Prabha D, Arunachalam R. Constraints in adoption of mobile agro advisories by the farmers. Agriculture. 2017;12(7):1782-85. https://doi.org/10.15740/has/au/12.
  70. 70. Jayanthi M, Asokhan M. Constraints faced by M-Kisan users. Journal of Extension Education. 2016;28(1):5622-24. https://doi.org/10.26725/JEE.2016.1.28.5622-5624
  71. 71. Malik AK, Kumar R. Constraints faced by agricultural extension personnel in utilization of internet as an Agro-Advisory tool: A study of CCS HAU Hisar. Indian Journal of Economics and Development. 2019;15(4):586-90. https://doi.org/10.5958/2322-0430.2019.00075.1

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