Influence Of Technology Integration On Agricultural Sustainability Among Farmers In Kadingilan, Bukidnon

Influence of Technology Integration on Agricultural Sustainability Among Farmers in Kadingilan, Bukidnon

Lara Mechaella C. Corroz, Christdian B. Rueles, Jonna Mae R. Sumondong, Fretzie Joy M. Medico, Ronalyn G. Caramogan, James S. Palabrica

Business administration, Bukidnon State University, Kadingilan Campus

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000399

Received: 06 September 2025; Accepted: 12 September 2025; Published: 13 October 2025

ABSTRACT

The integration of technology in agriculture had a big influence in enhancing sustainability, productivity, and resource efficiency. This study examines the influence of technological adoption of automated machinery, low-cost drip irrigation systems, and mobile phone-based farm management on agricultural sustainability among farmers in Kadingilan, Bukidnon. Grounded in the Diffusion of Innovations Theory, this research employs a descriptive quantitative design to assess the extent to which technology improves environmental conservation, food security, and farmers’ economic stability. Data were collected from 100 farmers across multiple barangays, utilizing structured surveys and statistical analyses to evaluate adoption levels and sustainability outcomes. The findings indicate that automated machinery significantly increases farm productivity, mobile technology enhances decision-making and market access, and drip irrigation improves resource conservation but faces financial barriers to widespread implementation. Additionally, the results highlight that crop diversity and land size significantly influence technology adoption, while demographic factors such as age and education exhibit minimal statistical impact. Overall, the study confirms that technology integration positively affects agricultural sustainability, reinforcing the need for financial assistance, training programs, and infrastructure development to optimize adoption. These insights provide valuable recommendations for policymakers, agricultural institutions, and farmers to enhance sustainability through innovative farming practices.

Keywords: Technology integration, agricultural sustainability, precision farming, food security, rural development

INTRODUCTION

The global agricultural sector faces the challenge of meeting the food needs of a growing population while reducing the serious environmental impacts of traditional farming, such as soil degradation, water depletion, and greenhouse gas emissions. In this situation, using technology in farming has become a key method for improving sustainability, productivity, and resource use. Advances in precision farming, including GPS-guided tractors, automated planters, and drones for crop monitoring, have enabled farmers to make informed decisions that optimize resource use and boost yields. Research by Kalfas et al. (2024) and Méndez-Zambrano et al. (2023) highlights how innovations in artificial intelligence (AI), the Internet of Things (IoT), and digital tools can greatly improve resource efficiency and overall agricultural yields.

The need for agricultural modernization is especially urgent in developing countries like the Philippines. Agriculture is vital for rural livelihoods but often rely on small-scale, traditional farming methods. Acknowledging this, the Philippine government has introduced measures like Republic Act No. 8435, the Agriculture and Fisheries Modernization Act of 1997, and Republic Act No. 10915, the Philippine Agricultural and Bio-systems Engineering Act of 2016, both aimed at modernizing the sector through technology. Programs such as PLDT Smart Agriculture in Bukidnon have provided real support, offering farmers digital tools and training to enhance agricultural practices and increase digital skills. Despite these efforts, significant research gaps remain, especially regarding the specific challenges and opportunities of adopting technology among small-scale and subsistence farmers in rural areas. In this study, low-cost drip irrigation refers to systems priced between ₱3,000 to ₱7,000 per hectare, which, while affordable compared to commercial setups, remain financially inaccessible for many smallholder farmers in Kadingilan. Limited access to subsidies, lack of awareness, and installation challenges contribute to the slow adoption of these technologies.This study addresses this gap by examining the role of technology integration in promoting agricultural sustainability within the community of Kadingilan, Bukidnon.

This research is based on the Diffusion of Innovations Theory (DOI), developed by Everett Rogers. This framework offers a useful way to analyze how new agricultural technologies spread and gain acceptance within a social system. The theory suggests that the perceived features of an innovation, such as its perceived benefits, compatibility with existing practices, complexity, trialability, and observability, are key factors in its adoption rate. In this study, the idea of relative advantage is especially important, as it explains why farmers are more likely to adopt new technologies if they see clear benefits over traditional methods. Additionally, the theory highlights the important role of social networks and communication in sharing information about new technologies, which is crucial in a community-focused agricultural context.

This study seeks to examine how technology integration affects agricultural sustainability among farmers in Kadingilan, Bukidnon. Specifically, it aims to answer the following questions: What is the demographic and agricultural profile of the respondents? How integrated is technology among farmers regarding automated machinery, low-cost drip irrigation, and mobile phone-based farm management? What is the perceived level of agricultural sustainability in reducing environmental impact, enhancing food security, and improving farmers’ livelihoods? Is there a significant difference in technology integration when grouping farmers by their profiles? Finally, does technology integration positively affect agricultural sustainability? The findings aim to provide useful insights for policymakers, agricultural extension services, and farmers to encourage fairer and more sustainable adoption of technology in the sector.

Statement of the Problem

This research aimed to explore the influence of technology integration on agricultural sustainability among farmers in Kadingilan, Bukidnon. Specifically, it answered the following research problems:

What is the profile of respondent in terms of:

1.1 Annual household income;

1.2 Years of farming;

1.3 Types of crops;

1.4 Land size; and

1.5 Land ownership?

2. What is the level of technology integration in terms of:

2.1 Automated machinery;

2.2 Low-cost drip irrigation system; and

2.3 Mobile phone for farm management?

3. What is the level of agricultural sustainability in terms of:

3.1 Reducing environmental impact;

3.2 Enhancing food security; and

3.3 Farmers livelihood?

4. Is there a significant difference the respondents technology integration when grouped according to their profile?
5. Does the technology integration influence agricultural sustainability?

METHODOLOGY 

This study used a descriptive quantitative research design to examine how technology integration affects agricultural sustainability among farmers in Kadingilan, Bukidnon. The approach measured the relationships between specific technological tools and sustainability indicators. It applied statistical methods to analyse adoption patterns and perceived outcomes.

Research Design

This study utilized a descriptive quantitative research design to assess how technology integration influences agricultural sustainability among farmers in Kadingilan, Bukidnon. Structured surveys were used to collect numerical data on farmer profiles, technology usage, and sustainability indicators. Descriptive statistics highlighted adoption levels and perceived benefits, while inferential methods such as correlation and regression analysis examined relationships between technology use and sustainability outcomes. This approach provided a clear, evidence-based understanding of how modern tools impact sustainable farming practices.

Research Locale

This study was conducted in Kadingilan, a rural municipality in southern Bukidnon known for its diverse agricultural practices. Surrounded by Maramag, Don Carlos, and Kalilangan, Kadingilan serves as a strategic hub for farming activities. Its fertile soil and favourable climate support a wide range of crops, including rice, corn, sugarcane, vegetables, and fruits. The community is culturally diverse, comprising indigenous groups, local settlers, and migrants, which contributes to varied farming techniques from traditional methods to modern technologies. Local government units, cooperatives, and farmer associations actively promote sustainable agriculture through training and resource support. Kadingilan’s strong agricultural identity and diversity in farming practices made it an ideal setting for examining how technology integration influences sustainability and farmer livelihoods.

Research Participants

To ensure a diverse and representative sample, the study included 100 farmers from Kadingilan, Bukidnon. Participants were selected based on active engagement in farming, varied land sizes, crop types (e.g., rice, corn, sugarcane, vegetables), and differing levels of technology use. Stratified random sampling was employed, grouping farmers by barangay, farm size, and crop type, and then randomly selecting individuals within each group. This approach captured the diversity of farming practices and technology adoption across the municipality.

Sampling Method

A stratified random sampling method was used to select 100 farmers from various barangays in Kadingilan, Bukidnon. Farmers were grouped by key characteristics such as farm size, crop type, and location to ensure diverse representation. Based on the 2020 Census, Kadingilan has a population of 33,735. The sample size was determined based on the demographic diversity and accessibility of farmers within the municipality. While practical constraints such as time and resources limited broader coverage, the sample reflects key patterns relevant to the study’s scope. Stratified sampling ensured representation across barangays and farm types. This approach enabled systematic data collection and provided a reliable foundation for analysing the impact of technology integration on agricultural sustainability. Future research may employ power analysis to enhance statistical generalizability.

Data Gathering Procedure

Structured surveys were used to collect quantitative data on farmer profiles, technology usage, and sustainability indicators. The instrument was developed based on the study’s objectives and validated through pilot testing. A stratified random sampling method was applied to select 100 farmers across various barangays in Kadingilan, ensuring diverse representation. Ethical clearance and informed consent were secured prior to data collection. Survey results were analysed using descriptive and inferential statistics to identify trends and relationships. To enrich the findings, follow-up interviews, focus group discussions, and field observations were conducted, ensuring a comprehensive and reliable dataset aligned with the research goals.

Research Instrument

A researcher-made questionnaire was developed to collect quantitative data aligned with the study’s objectives. It consisted of three main sections:

1. Demographic Profile – Gathered data on income, years in farming, crop types, land size, and ownership to contextualize technology adoption.
2. Technology Integration – Assessed the types, frequency, and perceived impact of technologies used, using a 4-point Likert scale (1 = Strongly Disagree to 4 = Strongly Agree).
3. Agricultural Sustainability – Measured indicators such as productivity, resource efficiency, environmental impact, and economic stability, also rated on the same scale.

The instrument included targeted statements to examine the relationship between technology use and sustainability outcomes. Its structured format ensured consistent data collection for both descriptive and inferential analysis.

Validity and Reliability

To ensure the instrument’s validity, experts reviewed the questionnaire and provided feedback, leading to necessary revisions. A pilot test involving 30 non-respondent farmers was conducted to assess reliability. The instrument achieved a Cronbach’s alpha of 0.80, indicating strong internal consistency. Quantitative data were analysed for coherence and accuracy, reinforcing the trustworthiness of the findings.

Scoring Procedure

Responses were measured using a 4-point scale, with each item assigned a numerical Likert value. Mean scores were computed to represent overall levels of technology integration and agricultural sustainability. These scores were then interpreted using predefined rating schemes, ensuring consistency and clarity in evaluating participant responses and drawing insights into the impact of technology on sustainable farming practices.

Table 1: Scoring scheme on the level of  Technology Integration

Table 1 outlines the 4-point Likert scale used to assess technology integration among farmers. Scores from 3.25 to 4.00 indicate “Strongly Agree” and reflect Very High Integration, while scores from 1.00 to 1.75 represent “Strongly Disagree” and Very Low Integration. Intermediate ranges 2.50 to 3.24 (“Agree”) and 1.75 to 2.49 (“Disagree”) denote High and Low Integration, respectively. This scale provided a consistent framework for interpreting survey responses and quantifying technology adoption levels.

Table 2: Scoring Scheme on the Agricultural Sustainability

Table 2 outlines the 4-point Likert scale used to evaluate agricultural sustainability. Scores from 3.25 to 4.00 indicate “Strongly Agree” and reflect Very High Sustainability, while scores from 1.00 to 1.75 represent “Strongly Disagree” and Very Low Sustainability. Intermediate ranges 2.50 to 3.24 (“Agree”) and 1.75 to 2.49 (“Disagree”)—denote High and Low Sustainability, respectively. This framework provided a consistent basis for interpreting farmer responses and assessing sustainability levels across key indicators.

Treatment of Data

Data analysis was structured around the study’s core research questions. Descriptive statistics such as frequencies, percentages, means, and standard deviations were used to summarize the socio-demographic profile of respondents and assess levels of technology integration and agricultural sustainability. Mean scores were interpreted using established scoring schemes. To examine the relationship between technology integration and sustainability, inferential methods including correlation and regression analysis were applied. These techniques provided a comprehensive understanding of patterns and associations, supporting evidence-based conclusions and recommendations.

Ethical Considerations

Prior to data collection, participants were fully informed about the study’s purpose, procedures, and their rights, including voluntary participation and the option to withdraw at any time. Informed consent was obtained, and all data were treated with strict confidentiality, used solely for academic purposes.

The instrument was screened for plagiarism to ensure originality and proper attribution. Data collection adhered to principles of honesty and transparency, with no fabrication, exaggeration, or manipulation of results. The study maintained neutrality, avoided conflicts of interest, and safeguarded participants’ privacy and well-being.

The research underwent multiple revisions based on adviser and panel feedback, and followed the ethical guidelines set by the Bukidnon State University Ethics Review Committee.

RESULTS AND DISCUSSION

This section shows the presentation, analysis, and interpretation of the data gathered by the researcher.

Table 3: Demographic Profile of Farmers in Kadingilan, Bukidnon

Table 3 shows the background of the farmers who joined the study. Most of them earn a moderate income, which means they have enough to cover basic needs but may struggle to afford expensive farming tools. About one-third are in the lowest income group, showing that many farmers face financial challenges. Only a small number belong to the high or upper-income levels, which means fewer farmers have the extra money to invest in advanced technologies like automated machines or drip irrigation systems.

When it comes to farming experience, more than half of the farmers have been working in agriculture for over 21 years. This shows that farming in Kadingilan is mostly done by older, experienced individuals. While their knowledge is valuable, they may be more comfortable with traditional methods and less open to trying new technologies. On the other hand, younger farmers though fewer in number might be more willing to explore modern tools and systems, especially if they receive proper training and support.

Most farmers own medium-sized farms between 1 to 5 hectares. This size is common for smallholder farming and is suitable for adopting affordable technologies. Farmers with very small land may not see the benefit of investing in new tools, while those with large farms can take advantage of bulk operations and cost savings. This means that medium-sized farms are in a good position to benefit from technology, as long as the tools are affordable and easy to use.

In terms of land ownership, most farmers own the land they work on. This is important because owning land gives farmers more confidence to invest in long-term improvements like irrigation systems or soil management tools. Farmers who lease land may hesitate to spend money on technologies if they’re unsure how long they’ll be able to use the land. Those with mixed ownership arrangements face both opportunities and challenges.

Overall, these findings help us understand how income, experience, land size, and ownership affect farmers’ decisions to use technology. Farmers with more money, secure land, and medium-sized farms are more likely to adopt new tools. To help others catch up, the government and other organizations should offer financial support, training, and policies that make technology more accessible to all farmers especially those with fewer resources.

Technology Integration among Farmers in Kadingilan

This section presented the level of technology adoption among farmers, focusing on three key technological tools: Automated Machinery, Low-cost Drip Irrigation System, and Mobile Phone for Farm Management. The analysis provided insights into how extensively these technologies were integrated into agricultural practices.

Table 4: Automated Machinery

Farmers in Kadingilan strongly agreed on the benefits of automated machinery, with high mean scores for ease of use (3.61), efficiency (3.59), and labour cost reduction (3.57). While they acknowledged its long-term cost-effectiveness (3.38) and productivity gains (3.27), these slightly lower scores suggest financial constraints may affect adoption, especially among smallholders. The findings align with the Diffusion of Innovations Theory, showing that perceived advantages drive adoption, but economic barriers and access to training limit integration. Larger farms more readily adopt automation, while smaller ones may need financial and technical support. Supporting studies (Santiteerakul et al., 2020; Garcia et al., 2024; Vanovskaya et al., 2022) confirm that mechanization enhances sustainability, resilience, and competitiveness reinforcing the need for inclusive programs to expand access to automated farming technologies.

Table 5: Low-Cost Drip Irrigation System

Farmers in Kadingilan strongly agreed that drip irrigation increased crop yield (Mean = 3.33), conserved water (3.06), and maintained soil moisture (3.02). However, setup cost scored lower (2.73), indicating affordability concerns among small-scale farmers. Despite this, the overall mean of 3.02 reflects high integration and recognition of its practical benefits. Aligned with the Diffusion of Innovations Theory, farmers prioritized technologies with clear advantages, though financial barriers slowed adoption. Government support and subsidies are essential to expand access to drip irrigation. Supporting studies (Khamis et al., 2015; Ali et al., 2021; Sharma & Jha, 2018) confirm that drip irrigation enhances sustainability but requires cost-reduction strategies to ensure broader implementation.

Table 6: Mobile Phone for Farm Management

Farmers in Kadingilan showed high integration of mobile phones in their operations. The highest mean scores were for weather tracking (3.18) and accessing farming information (3.17), highlighting their reliance on digital tools for planning and decision-making. Monitoring farm activities and management decisions followed (3.11), while market access scored lowest (3.02), suggesting limited use of mobile phones for trade. These findings support the study’s framework, showing that mobile technology enhances sustainability through climate awareness and resource management. However, lower scores in market access point to structural barriers, reinforcing the need for financial support, digital literacy, and infrastructure development. Supporting studies (Wang et al., 2023; Roehlano et al., 2023; Kalfas et al., 2024) confirm that mobile tools improve productivity but require policy-driven support for full adoption and economic impact.

Table 7: Summary of Technology Integration

Among the technologies assessed, automated machinery had the highest mean score (3.48), reflecting strong adoption due to its efficiency and labour-saving benefits. Mobile phones for farm management followed (3.12), showing high usage for weather tracking, market access, and crop monitoring. Drip irrigation scored lower (3.02), with adoption hindered by cost concerns. Overall, the mean score of 3.21 indicated high technology integration, though financial barriers affected uptake. The findings affirm that technology adoption enhances agricultural sustainability. Mechanization boosts productivity, mobile tools support informed decision-making, and drip irrigation promotes resource efficiency. However, affordability remains a challenge, especially for small-scale farmers. Guided by the Diffusion of Innovations Theory, the study shows that farmers favour accessible technologies with immediate benefits. Supporting research (Santiteerakul et al., 2020; Wang et al., 2023; Pingali et al., 2002) confirms these trends and highlights the need for financial support and infrastructure to ensure equitable access to agricultural innovations.

Agricultural Sustainability among Farmers in Kadingilan

This section evaluated the level of agricultural sustainability among farmers, focusing on three key aspects: Reducing Environmental Impact, Enhancing Food Security, and Farmers’ Livelihood. The analysis provided insights into how sustainable farming practices were influenced by technology integration.

Table 8:  Agricultural Sustainability in terms of Reducing Environmental Impact

Farmers strongly agreed that technology helped reduce soil degradation (Mean = 3.42), supporting long-term land health. However, reducing chemical overuse scored lower (3.31), suggesting continued reliance on traditional fertilizers due to financial or access limitations. The findings affirm that technology supports environmental sustainability, especially in soil conservation. Yet, full adoption of eco-friendly practices remains limited, highlighting the need for financial aid and training. The Diffusion of Innovations Theory explains that farmers adopt technologies with clear benefits, though uptake varies with cost and accessibility. Supporting studies (Singh et al., 2024; Ebora et al., 2022; Hrustek, 2020) confirm that smart farming tools improve sustainability but require better infrastructure and education to ensure widespread adoption.

Table 9: Agricultural Sustainability in terms  Of Enhancing Food Security

Farmers rated technology’s impact on food availability highest (Mean = 3.50), recognizing its role in boosting productivity and reliability. Climate adaptation scored lower (3.36), indicating challenges in managing unpredictable weather through technology. These results align with the Diffusion of Innovations Theory farmers adopt tools with clear benefits, but climate-related integration is limited by access and external conditions. Supporting studies (Osburg et al., 2024; Singh et al., 2024; Ebora et al., 2022) confirm that while technology strengthens food resilience, climate adaptation requires further innovation and support. Technology was seen as highly effective in improving work-life balance (Mean = 3.56), streamlining farm management and reducing labour strain. Market access received the lowest score (3.28), suggesting that some farmers faced barriers in fully leveraging digital tools for trade. These findings reflect the need for training, infrastructure, and policy support to help farmers maximize market opportunities. The Diffusion of Innovations Theory explains that adoption depends on perceived value and accessibility.

Table 10: Agricultural Sustainability in terms  Of Farmers’ Livelihood

Farmers reported strong benefits from technology in improving work efficiency and financial stability. While market access also improved, its slightly lower mean score suggests challenges related to competition, pricing, and digital literacy. Consistent with the Diffusion of Innovations Theory, farmers adopted technology when it enhanced productivity and income. However, maximizing market benefits may require additional support through training and infrastructure. Supporting studies (Arhin et al., 2024; Rakholia et al., 2024; Vanovskaya et al., 2022) affirm that technology boosts economic resilience and work-life balance, though external factors can limit market success.

Table 11: Summary of Agricultural Sustainability

Farmers in Kadingilan rated food security highest (Mean = 3.43), reflecting strong agreement that technology improved crop yield and supply stability. Livelihood enhancement also scored well, indicating benefits to financial stability and work efficiency. Reducing environmental impact received the lowest score (3.37), suggesting challenges in adopting eco-friendly practices due to cost or accessibility. These results align with the Diffusion of Innovations Theory, showing that farmers prioritize technologies with clear economic benefits. The lower score for environmental impact highlights the need for financial support and access to sustainable methods. Supporting studies (Osburg et al., 2024; Singh et al., 2024) confirm that precision agriculture and smart fertilizers enhance sustainability, but broader adoption requires targeted interventions.

Significant Differences in Technology Integration by Profile

A one-way ANOVA revealed significant differences in technology integration when farmers were grouped by crop type (F = 2.85, p = 0.00) and land size (F = 3.73, p = 0.02). These results suggest that the kind of crops cultivated and the extent of landholdings influence how farmers adopt technology in their practices.

Table 12: Dependent Variable: Technology Integration

Farmers in Kadingilan recognized the environmental benefits of technology, especially in soil conservation (Mean = 3.42). However, reducing chemical overuse scored lower (Mean = 3.31), suggesting continued reliance on traditional inputs due to financial or access limitations. This highlights the need for training and funding to support eco-friendly practices. ANOVA results showed no significant differences in technology integration based on income, experience, or land ownership, indicating uniform adoption across demographics. Instead, crop diversity and land size significantly influenced adoption, with farmers managing larger or more varied farms more likely to use advanced tools for efficiency and sustainability. Supporting studies (Pingali et al., 2002; Rakholia et al., 2024; Santiteerakul et al., 2020; Dugan et al., 2001) confirm that diverse and large-scale farms require specialized technologies. Batz et al. (2020) and Osburg et al. (2024) emphasized that financial support, infrastructure, and operational needs not personal traits drive adoption. These findings suggest that targeted programs addressing farm-specific challenges are keys in expanding sustainable technology use in Kadingilan.

Influence of Technology Integration on Agricultural Sustainability

A simple linear regression revealed a significant positive relationship between technology integration and agricultural sustainability (t = 5.54, p < 0.00). The standardized coefficient (β = 0.26) indicates that each one-unit increase in technology integration corresponds to a 0.26-unit rise in sustainability score, holding other factors constant.

Table 13: Technology Integration Influence  Agricultural Sustainability

Regression analysis revealed a significant positive relationship between technology integration and agricultural sustainability (t = 5.54, p < 0.00; β = 0.26), with the model explaining 23.8% of the variance (R² = 0.24). This indicates that technology plays a meaningful role in enhancing resource efficiency, productivity, and environmental responsibility. Farmers adopting tools like precision farming, automated irrigation, and digital monitoring reported improved sustainability outcomes. Crop type and land size significantly influenced technology adoption, while income, experience, and land ownership showed minimal impact, suggesting that farming needs drive adoption more than personal background. Supporting studies (Osburg et al., 2024; Santiteerakul et al., 2020; Rakholia et al., 2024; Pingali et al., 2002; Batz et al., 2020; Dugan et al., 2001) confirm that innovations such as AI-powered fertilization, smart crop rotation, and mobile-based management strengthen resilience and sustainability. These findings highlight the need for targeted investments in precision technologies, infrastructure, and digital education to ensure inclusive agricultural advancement in Kadingilan.

DISCUSSION

The findings reveal three major themes: (1) Financial Barriers to Technology Adoption, (2) Digital Tools as Catalysts for Change, and (3) Environmental Gaps in Sustainability. Mobile phones emerged as the most adopted technology due to affordability and ease of use, while drip irrigation lagged behind because of cost and technical complexity. Interestingly, demographic factors such as age and education showed minimal influence compared to farm structure and income level. These insights suggest that structural support and targeted training may be more effective than demographic targeting alone.

The respondents’ profile and technology adoption revealed that crop diversity and land size significantly influenced technology adoption, while factors such as household income, years in farming, and land ownership had minimal impact. Farmers with diverse crops were more likely to integrate modern technology due to varying production requirements, while those with larger landholdings adopted advanced tools to enhance efficiency and productivity. The hypothesis stating that there is no significant difference in technology adoption based on respondents’ profiles (Ho₁) was rejected, confirming that structural farming characteristics play a more decisive role than personal demographics.

The level of technology integration demonstrated high adoption rates, particularly in automated machinery and mobile farm management, which improved operational efficiency and decision-making. However, drip irrigation, despite its recognized benefits, faced financial barriers that limited its adoption among small-scale farmers. These findings highlight that while farmers are receptive to technological advancements, affordability and accessibility remain key challenges in integrating sustainable farming solutions.

In terms of agricultural sustainability outcomes, the study confirmed that technology integration significantly enhances food security, environmental sustainability, and farmers’ livelihoods. Respondents reported higher crop yields, improved resource management, and increased financial stability due to modern agricultural innovations. However, the ability to fully transition to eco-friendly farming methods remained limited, as some farmers continued to rely on traditional chemical fertilizers due to cost and availability concerns.

While technology integration has improved productivity, environmental sustainability remains a concern. The continued use of chemical fertilizers and pesticides reflects limited access to organic alternatives and insufficient training on sustainable practices. Many farmers still rely on synthetic inputs because they are cheaper and more readily available in local markets. This reliance poses risks to soil health, biodiversity, and long-term ecological balance. Future programs should promote organic alternatives and offer training in integrated pest management to help farmers transition toward more environmentally friendly practices. This trend contradicts the goals of SDG 12: Responsible Consumption and Production, highlighting the need for targeted interventions that promote eco-friendly farming. Capacity-building, financial incentives and community-based demonstration farms could serve as effective strategies to reduce environmental impact and support long-term sustainability.

The analysis of technology adoption based on farming characteristics further reinforced that farm structure particularly in crop diversity and land size is more important than personal demographics in influencing adoption. Small-scale farmers, despite recognizing the benefits of modern tools, faced affordability barriers that limited their ability to integrate advanced technologies.

Overall, the regression analysis confirmed a strong positive relationship between technology adoption and agricultural sustainability. The hypothesis stating that technology integration does not influence agricultural sustainability (Ho₂) was rejected, affirming that modern innovations significantly enhance resource efficiency, environmental responsibility, and financial stability. However, the model explained only 24% of the variance in sustainability outcomes, suggesting that other influential factors were not captured in this study. These may include access to extension services, peer influence, government subsidies, market conditions, and farmers’ personal attitudes toward innovation. Future research should explore these dimensions to build a more comprehensive understanding of what drives sustainable practices among farmers. These findings underscore the transformative potential of technology in rural agricultural systems and call for inclusive strategies that address both economic and environmental dimensions of sustainability.

CONCLUSION

This study affirms that technology integration is very important in enhancing agricultural sustainability among farmers in Kadingilan, Bukidnon. The adoption of modern tools, such as automated machinery, mobile farm management systems, and drip irrigation led to improved productivity, resource efficiency, and financial stability. However, the full potential of these innovations remains constrained by financial and infrastructural barriers, particularly for small-scale farmers.

The findings reinforce the Diffusion of Innovations Theory, showing that farmers are more likely to adopt technologies when they perceive clear advantages. Yet, adoption is shaped more by structural farming characteristics, such as crop diversity and land size, than by personal demographics like income or years in farming. This suggests that practical farming needs drive decision-making more than individual attributes.

Environmental sustainability, while improved in some areas, remains a concern. Continued reliance on chemical inputs and limited access to organic alternatives highlight the need for targeted interventions that promote eco-friendly practices. Moreover, the regression model explained only 24% of the variance in sustainability outcomes, suggesting that other influential factors, such as access to extension services, peer networks, and market conditions may also shape adoption behaviour. To ensure inclusive and sustainable technology integration, coordinated efforts from policymakers, agricultural institutions, and community stakeholders are essential.

RECOMMENDATIONS 

To promote equitable and sustainable agricultural development in Kadingilan, Bukidnon, the following recommendations are proposed:

1. Expand Financial Support for Technology Adoption

• Provide targeted subsidies, low-interest loans, and grant programs to help smallholder farmers acquire modern technologies.
• Prioritize support for cost-intensive tools like drip irrigation and automated machinery.

2. Strengthen Training and Capacity-Building Programs

• Conduct regular workshops, field demonstrations, and hands-on training tailored to local farming contexts.
• Collaborate with universities, agricultural agencies, and technology developers to ensure farmers receive up-to-date, practical knowledge.

3. Improve Infrastructure and Digital Connectivity

• Invest in rural internet access and mobile network expansion to enable real-time access to weather updates, market prices, and digital advisory tools.
• Upgrade irrigation systems, storage facilities, and farm roads to improve resource management and reduce post-harvest losses.

4. Promote Sustainable Farming Practices

• Encourage the use of organic fertilizers, integrated pest management, and climate-smart techniques through financial incentives and awareness campaigns.
• Support precision agriculture and environmentally responsible technologies aligned with SDG 12: Responsible Consumption and Production.

5. Enhance Market Linkages and Policy Support

• Develop structured market access programs to help farmers sell their produce at fair prices and connect with larger distribution networks.
• Formulate inclusive policies that address financial, technical, and environmental barriers to technology adoption.

6. Support Further Research and Monitoring

• Encourage longitudinal studies to explore additional factors influencing sustainability, such as farmer attitudes, peer influence, and access to advisory services.
• Establish local monitoring systems to track technology adoption trends and environmental outcomes over time.

ACKNOWLEDGEMENTS

The researchers would like to express their sincere gratitude to all the individuals who supported and contributed to the success of this research study. First, they extend their heartfelt appreciation to the supportive and dedicated Campus In-Charge and Chairperson of the Board, Ma’am Nina Marie G. Jamisolamin, for her invaluable assistance.

They are also deeply thankful to their research adviser, Ms. Charelle P. Tecson, for her continuous guidance, patience, and encouragement throughout the research process.

Special thanks are extended to the panel examiners, Dr. Jason B. Montecanas and Dr. Jahzeel M. Candilasa, for dedicating their time to review the paper and for sharing valuable feedback that significantly improved the quality of the work:

The researchers also wish to acknowledge Dr. Jahzeel M. Candilasa, their passionate editor for her constructive comments and ideas from the early stages of the research. Her suggestions contributed greatly to the clarity and refinement of the final manuscript.

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