A study on profile characteristics and constraints faced by the DAMU beneficiary farmers

Introduction

India is primarily an agriculture-dependent country, and its agricultural sector relies heavily on various climatic conditions. Every year, agriculture faces severe weather aberrations such as typhoons, erratic rainfall, droughts, cold winds, and frost, all of which significantly dictate crop production and productivity. Because agriculture and its allied sectors are highly vulnerable to micro-level weather parameters including temperature, rainfall, wind velocity, and frost the continuous monitoring and efficient utilization of meteorological data are crucial for sustainable farming. To address climate-related agricultural risks, the Gramin Krishi Mausam Seva (GKMS) scheme was launched as a flagship program by the Ministry of Earth Sciences (MoES), Government of India. This initiative aims to provide critical weather-related services that aid farmers in their day-to-day agricultural decision-making. Collaboratively undertaken by the India Meteorological Department (IMD) and the Indian www.extensionjournal.com Council of Agricultural Research (ICAR), the scheme has successfully facilitated the establishment of 200 District Agromet Units (DAMUs) across India to date. With recent advancements in observational networks and forecasting technology, the Agromet Advisory Service (AAS) network was systematically extended to the sub-district and block levels during the 2018-2019 period. These DAMUs were strategically set up within the premises of Krishi Vigyan Kendras (KVKs) and State Agricultural Universities through Agricultural Technology Application Research Institutes (ATARIs), operating under a formal Memorandum of Understanding (MOU) between the ICAR and the IMD. Accordingly, a District Agro-Met Unit was established and operationalized at the Dr. K. L. Rao Krishi Vigyan Kendra in Garikapadu in October 2019, followed by the installation and functioning of an Automatic Weather Station (AWS) on February 27, 2020. Since its inception, the unit has actively served the farming communities of the Krishna and NTR districts by issuing district-and blocklevel Agromet Advisory Services (AAS). These advisories are disseminated bi-weekly (on Tuesdays and Fridays) in both English and the regional language, supplemented by special emergency bulletins during extreme weather events. The AAS bulletins provide value-added weather forecasts for the upcoming five days, accompanied by crop-specific advisory messages formulated in consultation with KVK scientists. By disseminating this targeted information directly to the farming community, the DAMU empowers farmers to plan their agricultural and horticultural operations scientifically. Ultimately, the efficient adoption of these services aims to mitigate severe crop losses, optimize input usage, double farmers' incomes, and contribute to the overall growth of the Indian agricultural economy.

Methodology

The present study was conducted in the NTR district of Andhra Pradesh during the agricultural year 2023-24 to analyze the socio-economic characteristics, constraints, and suggestions of District Agro-Meteorological Unit (DAMU) beneficiary farmers. During the operational period of the 27th February 2020 DAMU scheme, bi-weekly agromet advisory bulletins were issued every Tuesday and Friday to key extension functionaries, including Assistant Directors of Agriculture (ADAs), Mandal Agricultural Officers (MAOs), and Village Agriculture Assistants (VAAs). These timesensitive weather and crop advisories were subsequently disseminated directly to the beneficiary farmers through digital channels, primarily WhatsApp groups, emails, and the Meghdoot mobile application. A purposive sampling technique was employed for the selection of both the study area and the respondents. The research was carried out across 12 selected mandals within the NTR district, from which 10 active DAMU beneficiary farmers were purposively chosen per mandal, resulting in a total sample size of 120 respondents. Primary data was collected directly from the farmers through face-to-face interviews using a pre-tested, well-structured interview schedule. Finally, to draw meaningful inferences from the raw data, the responses were tabulated and evaluated using descriptive statistical tools, specifically utilizing mean, median, frequencies, and percentages

Results and Discussions Socio Economic characteristics of KVK-DAMU beneficiary farmers 1. Age

Table 1 reveals that a significant majority (70.00%) of the DAMU beneficiary farmers were middle-aged. Young and old farmers constituted 22.50% and 7.50% of the respondents, respectively. This finding is strongly supported by Jayanthi and Asokhan (2016) [7] , who also reported a predominance of middle-aged farmers (54.17%) utilizing SMS-based agromet advisories.

Similarly, Venkatasubramanian et al. (2014) [2] and Hasan et al. (2018) [6] observed that middle-aged farmers form the majority of weather-advisory adopters, attributing this trend to their higher family responsibilities and readiness to integrate climate-risk mitigation tools into farm management.

Education

From Table 2, it can be concluded that the majority of the DAMU beneficiary farmers possessed a high school education (53.33%), followed by middle school (20.83%) and primary school (10.00%). A smaller proportion had a college education and above (5.00%) or an intermediate education (4.16%), while the remaining minority were either illiterate (4.17%) or could only read and write (2.50%). This distribution indicates a highly literate beneficiary base, which serves as a fundamental catalyst for the successful adoption of digital extension services. Because over 84% of the respondents possess at least a primary to high school education, they have the foundational literacy required to independently read, comprehend, and act upon the KVK's bi-weekly Telugu SMS advisories and WhatsApp bulletins. This level of education allows extension teams to confidently include specific chemical names, dosages, and meteorological terms in their messages. This finding is in strict conformity with Gopi et al. (2023) [3] and Mandal and Jirli (2018) [15] , who similarly established that secondary and high school education is the dominant literacy level among active adopters of ICT-based agro-meteorological information, significantly enhancing a farming community's capacity to decode digital advisories and transition towards climate-resilient agriculture.

Family size

From Table 3, it can be concluded that the majority of the DAMU beneficiary farmers belonged to the medium family size category (72.50%), followed by large (12.50%) and small (11.67%) families. This finding is in line with Singh et al. (2019) [16] and the CCAFS, which similarly reported a predominance of medium-sized families among adopters of resilient agricultural practices. It can be inferred from these results that medium-sized farming households possess the optimal internal family labor force required to quickly execute time-sensitive farm operations such as irrigation scheduling or protective spraying based on real-time agromet advisories.

Land Holding

From the table 4, it can be concluded that the majority of the DAMU beneficiary farmers possessed marginal landholdings (35.83%), followed by small (29.16%), semimedium (15.83%), landless (8.34%), medium (5.84%), and large (5.00%) landholding. This distribution indicates that DAMU advisories are predominantly reaching resourcepoor farmers, with small and marginal landholders constituting a combined 64.99% of the beneficiaries. This finding is in conformity with Gopi et al. (2023) [3] and Dupdal et al. (2020) [2] , who similarly observed that small and marginal farmers form the majority of agromet advisory users, as they heavily rely on micro-level weather data to manage their limited resources and minimize input costs. Furthermore, access to these real-time advisories is vital for these vulnerable groups to mitigate climate risk and protect their crop yields (Nannewar et al., 2023) [11] . [12] . This is consistent with the findings of Harshavardhan et al.

(2023) [5] and Hanif et al. (2023) [4] , who established that higher social participation significantly increases a farmer's likelihood of adopting DAMU extension services and climate-resilient practices. [12] . This conclusion is strongly supported by Hanif et al. (2023) [4] and Hasan et al. (2018) [6] , who found that lower to medium farming experience positively correlates with the adoption of digital extension tools and climate-smart agricultural information.

Type of farming

From Table 7, it can be concluded that an overwhelming majority of the DAMU beneficiary farmers practiced irrigated farming (85.00%), while only a small proportion (15.00%) relied on rain-fed farming. This distribution strongly indicates that farmers with assured irrigation facilities are highly proactive in seeking and utilizing realtime meteorological data. In irrigated ecosystems, weather advisories are critical for resource optimization specifically, farmers use rainfall forecasts to decide when to pause their pumps, thereby saving groundwater, electricity, and preventing the leaching of expensive fertilizers. For extension functionaries at KVK Garikapadu, this underscores the importance of embedding precise irrigation scheduling advice (e.g., 'postpone irrigation for the next 48 hours') within the space-constrained Kisan Sarathi SMS bulletins. This finding is in line with Dupdal et al. (2020) [2] www.extensionjournal.com and Hanif et al. (2023) [4] , who similarly reported a higher adoption rate of agromet advisories among irrigated farmers, as they actively leverage predictive weather data to minimize input wastage and maximize crop efficiency. [12] and Sayyad and Jadhav (2023) [13] , who similarly concluded that SMS and WhatsApp are the dominant communication channels for Agromet Advisory Services due to their instant reach and accessibility. Furthermore, Dhulipala et al. (2021) [1] observed that mobile applications like Meghdoot are increasingly playing a vital role in providing locationspecific, climate-smart advisories directly to rural farmers.

Most suited and preferred medium of weather forecast and advisory services

From Table 7, it can be concluded that the most suited and preferred medium for receiving weather forecasts and advisory services among the DAMU beneficiary farmers was SMS/text messages (94.16%), followed closely by WhatsApp groups (78.33%). The remaining respondents preferred newspapers (55.83%), other sources (38.33%), the IMD website (36.66%), and the Meghdoot App (12.50%).

The data from Table 7 clearly establishes that mobile-based push technologies specifically SMS and WhatsApp are the overwhelmingly preferred channels for extension delivery. Considering that a significant majority (70.00%) of these farmers are middle-aged (as established in Table 1), this preference is highly logical; SMS is universally accessible even on basic feature phones, requiring minimal digital literacy compared to navigating specialized mobile applications like Meghdoot or the IMD website. For Krishi Vigyan Kendras (KVKs) and extension functionaries, this emphasizes the critical need to prioritize platforms like Kisan Sarathi. To maximize impact, advisories must be highly concise, accurately translated into the local language (Telugu), and carefully drafted to fit within standard SMS character limits. Concurrently, WhatsApp groups can be leveraged as a secondary medium to provide the multimedia support (such as photos of pest attacks) that basic SMS lacks. These findings are strongly supported by Gopi et al. (2023) [3] and Mittal and Mehar (2016) [10] , who similarly concluded that text messaging remains the most inclusive and preferred ICT tool for middle-aged farmers in India due to its instantaneous, low-cost, and direct-to-farmer approach.

Farm operation for which weather forecast/ agro met advisories useful

From the table, it can be concluded that all DAMU beneficiaries (100.00%) found agromet advisories most useful for harvesting and threshing, followed by irrigation (94.16%), chemical application (92.50%), fertilizer application (76.67%), and sowing (60.00%). This demonstrates that farmers primarily rely on real-time weather data to prevent severe economic losses specifically by protecting mature crops from unseasonal rain and pausing irrigation or spraying to avoid input runoff. Consequently, local extension teams, such as KVK Garikapadu, should prioritize urgent SMS alerts via Kisan Sarathi for harvesting warnings and chemical/irrigation scheduling. These findings align with Dupdal et al. (2020) [2] and Gopi et al. (2023) [3] , who established that weather advisories crucially reduce input wastage and safeguard crop yields. 11, it can be concluded that a vast majority of DAMU beneficiaries (95.00%) perceived the weather-based agro-advisories as highly useful, while the remaining minority (5.00%) found them partially useful. Notably, zero farmers (0.00%) found the services to be not useful. This overwhelmingly positive feedback demonstrates the undeniable practical value and relevance of real-time meteorological data at the grassroots level. Because not a single farmer deemed the service useless, it strongly validates the continuous efforts of local extension units, such as KVK Garikapadu, in translating and broadcasting precise, actionable Telugu advisories via Kisan Sarathi. To sustain this high utility, extension teams must ensure future messages remain highly location-specific and timely. These findings perfectly align with previous studies Gopi et al. (2023) [3] , Dupdal et al. (2020) [2] which similarly reported a near-unanimous positive perception among farmers regarding the economic and agricultural utility of DAMU interventions. Highly useful 114 95.00 2.

Partially useful 6 5.00 3.

Not useful 0 0.00 120 100.00

Weather event most useful farm operation

From the table, it can be concluded that all DAMU beneficiaries (100.00%) found forecasts regarding rain to be the most useful for their farm operations. This was followed by cloud coverage (85.00%), soil temperature (66.67%), wind (58.33%), relative humidity (50.83%), and heavy rain (37.50%). Advisories for low temperature (27.50%), high temperature (15.00%), and thunderstorms (12.50%) were utilized to a lesser extent. This demonstrates that farmers primarily depend on precipitation and cloud-cover data to make critical, day-to-day decisions regarding irrigation scheduling and pest management, as cloudiness and humidity directly trigger pest outbreaks. Consequently, for extension teams drafting targeted Telugu advisories for the Kisan Sarathi platform, prioritizing precise, localized rain and cloud-cover predictions will deliver the highest value within strict SMS character limits. These findings align with Gopi et al. (2023) [3] and Dupdal et al. (2020) [2] , who noted that rainfall and cloud-cover forecasts are the most highly sought-after parameters by farmers to prevent crop damage and optimize chemical spraying. [8] and Rohit et al. (2024) [12] , integrating specific market and pesticide data into SMS bulletins is critical to driving adoption and providing true grassroots value. [12] and Gopi et al. (2023) [3] , who similarly reported that ensuring location-specific timeliness, mitigating rural network issues, and providing direct IT training are the most critical, farmer-driven suggestions for scaling the adoption of agromet services.

Conclusion

The study concludes that beneficiary farmers in the NTR district highly value and actively utilize DAMU weatherbased agro-advisories as a vital risk mitigation and resource optimization strategy. However, to maximize the utility of these services, the findings highlight the critical need for targeted institutional interventions, grassroots digital skill development, and policy support. Specifically, extension agencies must pivot toward providing hyper-local forecast precision and integrating actionable economic data such as current input prices and exact agro-chemical recommendations into mobile bulletins to strengthen the sustainability, widespread adoption, and overall economic impact of digital agricultural extension services.

Acknowledgement

AcknowledgementThe authors acknowledge the funding and institutional support provided by the India Meteorological Department (IMD) under the Gramin Krishi Mausam Seva (GKMS) scheme. We express our profound gratitude to the Director, ICAR-ATARI Zone X, Hyderabad, and the Director of Extension, Acharya N.G. Ranga Agricultural University (ANGRAU), for their continuous guidance, support, and encouragement. We are also deeply thankful to the Programme Coordinator and the administration of Dr. K.L. Rao Krishi Vigyan Kendra, Garikapadu, for providing the necessary facilities and facilitating this study. Finally, we extend our heartfelt thanks to the beneficiary farmers of the NTR district for their active participation and invaluable feedback.

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