Annals of Agriculture and Life Sciences Journal (AALSJ)

Impact of Sulfur on Sunflower Growth and Yield

Islam Nabi — Sat, 16 May 2026 12:20:38 +0000

The use of Sulphur (S) is known to have a significant effect on the growth and yield components of Sunflower (‘Helianthus annuus’ L.). From March to May, the Kharif season from 2022 was conducted at Amir Muhammad Khan Campus, The University of Agriculture, Peshawar in order to analyses S’s effects on sunflower with varying levels of Sulphur 0, 10, 20, 30 kg ha⁻¹. A randomized complete block design was followed with three replicates of sunflower crops across the region. Results showcased the best growth parameters with 30kg S ha⁻¹, early emergence on day 10 and oil content of 45.38%, seed weight oil content of 60.39g, plant height of 156.66cm. Furthermore, all 30 ha were the optimal yielding conditions with Michigan S K Port received values of grain yield and biological yield peaking at 1076 alongside 4310 Kg ha⁻¹ becoming the new regional record. Overall, S was showcased with the fullest potential regarding the sunflower yield, with 30 kg S has recommended for the Mardan region.

Artificial Intelligence-Based Precision Agriculture and Crop Yield Optimization: The Mediating Role of Data-Driven Decision Making and Farmer Digital Literacy

Muhammad Islam Khan — Sat, 16 May 2026 12:21:22 +0000

Artificial Intelligence (AI) is revolutionizing modern agriculture by enabling precision farming techniques that optimize crop yield, resource utilization, and environmental sustainability. AI-based precision agriculture systems leverage machine learning algorithms, predictive analytics, and remote sensing data to provide actionable insights for irrigation, fertilization, pest management, and harvesting. However, the effectiveness of these technologies depends not only on technological adoption but also on farmers’ ability to interpret and apply data-driven insights and their level of digital literacy. This study investigates the impact of AI-based precision agriculture on crop yield optimization, with a focus on the mediating roles of data-driven decision making and farmer digital literacy. Data-driven decision making refers to farmers’ capacity to interpret AI-generated recommendations and implement evidence-based interventions effectively. Digital literacy reflects farmers’ technical skills, familiarity with digital tools, and confidence in utilizing AI platforms for agricultural management. A quantitative research design was employed, targeting farmers, agronomists, and agricultural extension specialists in regions practicing precision agriculture. Structured questionnaires were used to collect data, which were analyzed using Smart PLS structural equation modeling to assess both direct effects of AI-based precision agriculture and the mediating effects of decision making and digital literacy. Results indicate that AI-based precision agriculture positively impacts crop yield optimization. Data-driven decision making and farmer digital literacy both mediate this relationship, emphasizing the importance of human capability in translating AI insights into practical actions. These findings highlight the necessity of combining technological innovation with capacity-building programs and digital skill development to maximize the benefits of AI-based precision agriculture. The study offers critical insights for policymakers, agricultural extension services, and technology developers seeking to promote sustainable and high-yield farming practices.

Nanotechnology-Based Fertilizers and Sustainable Crop Productivity: The Mediating Role of Nutrient Use Efficiency and Soil Fertility

Mutabir Shah — Sat, 16 May 2026 12:23:11 +0000

Sustainable agriculture is increasingly challenged by declining soil fertility, inefficient nutrient utilization, and the growing demand for high crop yields. Nanotechnology-based fertilizers (NBFs), which involve nano-sized nutrient particles or encapsulated delivery systems, offer a promising solution by improving nutrient availability, reducing losses, and enhancing plant uptake. These fertilizers have the potential to optimize crop productivity while minimizing environmental impact. This study investigates the impact of nanotechnology-based fertilizers on sustainable crop productivity, focusing on the mediating roles of nutrient use efficiency and soil fertility. Nutrient use efficiency refers to the proportion of applied nutrients effectively absorbed and utilized by crops, while soil fertility encompasses physical, chemical, and biological properties that support plant growth. Both factors are hypothesized to mediate the relationship between NBF application and crop productivity. A quantitative research design was adopted, with data collected from farmers, agronomists, and soil scientists across regions using NBFs. Structured questionnaires measured NBF adoption, nutrient use efficiency, soil fertility, and crop productivity. Data were analyzed using Smart PLS structural equation modeling to evaluate direct and mediated effects. Results indicate that nanotechnology-based fertilizers positively influence sustainable crop productivity. Nutrient use efficiency and soil fertility both significantly mediate this relationship, emphasizing the role of soil health and optimal nutrient management in achieving productivity gains. The findings highlight the importance of integrating advanced fertilizer technologies with soil management strategies to ensure sustainable and high-yield agriculture. These insights are valuable for policymakers, agricultural planners, and technology developers aiming to promote precision nutrient management and sustainable crop production.

Precision Irrigation Technologies and Sustainable Crop Yield: The Moderating Role of Water Scarcity Adaptation Strategies

Fawad Iqbal — Sat, 16 May 2026 12:23:54 +0000

Agricultural water management is a critical challenge in the context of climate change, population growth, and increasing water scarcity. Precision irrigation technologies, including drip irrigation, automated sprinklers, soil moisture sensors, and remote sensing-based irrigation scheduling, have emerged as transformative tools for enhancing crop productivity and promoting sustainable water use. By optimizing water application according to crop needs and environmental conditions, these technologies can improve water use efficiency, minimize wastage, and support sustainable agriculture. This study investigates the impact of precision irrigation technologies on sustainable crop yield and examines the moderating role of water scarcity adaptation strategies, such as drought-resistant crop varieties, soil moisture conservation techniques, and integrated water management practices. Water scarcity adaptation strategies are posited to strengthen the relationship between precision irrigation adoption and crop yield outcomes by enhancing resilience to water limitations. A quantitative research design was employed, with structured questionnaires administered to farmers, agronomists, and agricultural extension specialists across regions facing varying degrees of water scarcity. Data were analyzed using Smart PLS structural equation modeling to evaluate the direct effect of precision irrigation technologies on crop yield and the moderating effect of adaptation strategies. Findings indicate that precision irrigation technologies significantly enhance sustainable crop yield. The presence of water scarcity adaptation strategies moderates this relationship, amplifying the positive impact of precision irrigation in water-limited environments. The study highlights the importance of integrating technological innovation with adaptive water management practices to ensure resilient, high-yield agricultural systems. These insights inform policymakers, agricultural planners, and extension services in designing interventions for sustainable crop production under water scarcity.

Climate Change Adaptation in Agriculture: The Impact of Farmer Resilience and Digital Advisory Services on Sustainable Crop Management

Robeena Tesori — Sat, 16 May 2026 12:24:49 +0000

Climate change poses a significant threat to agricultural productivity and food security worldwide. Increasing frequency of extreme weather events, rising temperatures, and shifting rainfall patterns challenge conventional farming practices and necessitate adaptive strategies to ensure sustainable crop management. Farmers’ resilience—their capacity to anticipate, respond, and recover from climate-related shocks and digital advisory services, including mobile apps, remote sensing platforms, and online extension services, are critical in facilitating climate-smart agricultural practices. This study investigates the impact of farmer resilience and digital advisory services on sustainable crop management. Farmer resilience is conceptualized as adaptive capacity, knowledge, and coping strategies that mitigate climate risks, while digital advisory services provide timely, data-driven guidance on crop planning, irrigation, pest management, and weather adaptation. A quantitative research design was employed, using structured questionnaires distributed to farmers, agronomists, and agricultural extension specialists across regions affected by climate variability. Data were analyzed using Smart PLS structural equation modeling to examine the direct and interaction effects of farmer resilience and digital advisory services on sustainable crop management outcomes. Results indicate that both farmer resilience and access to digital advisory services significantly enhance sustainable crop management practices. Digital advisory services amplify the positive effects of farmer resilience by providing timely information, predictive analytics, and evidence-based recommendations, enabling proactive adaptation to climate challenges. The findings highlight the importance of integrating human adaptive capacity with digital technologies to achieve resilient, high-performing agricultural systems. These insights inform policymakers, agricultural planners, and extension services in designing interventions to support climate-smart agriculture.