Precision Agriculture for Smallholder Farmers

Introduction

This document provides an overview of digital technologies driving precision agriculture for smallholder farmers, focusing on challenges and opportunities in developing countries. It outlines key technologies such as mobile phones, satellites, unmanned aerial vehicles (UAVs), and sensors/Internet of Things (IoT), and provides recommendations for project managers and policymakers. The practical value lies in its guidance on implementing technology-enabled programs to improve productivity, reduce waste, and protect the environment while promoting gender inclusion and making farming more profitable for smallholders.

Key Insights

Technologies Driving Precision Agriculture

Mobile Phones

Mobile phones are the most transformative technology, enabling two-way communication, real-time monitoring, and easy data collection. They can overcome limitations of agricultural extension workers (AEWs) by providing customized and localized advice on what, when, and how to grow, as well as alerts on weather, pests, and diseases. A study suggested a benefit-cost ratio of up to 10:1 from farmers applying lime to their crops following SMS-based advisories (Fabregas et al., 2019).

Satellites

Remote sensing using satellites supports precision agriculture by providing high-resolution imagery for nutrient status, crop health monitoring, and yield estimation. This imagery can be analyzed using machine learning algorithms for applications like nutrient status and crop health monitoring for individual farms. “Satellite imagery provides a snapshot of a large area of farmland in a single image” (UNDP, 2021, p.8).

Unmanned Aerial Vehicles (UAVs)

UAVs offer remote sensing capabilities and high resolutions for weed and pest detection, enabling variable rate maps specifying the amounts of inputs required in different parts of the farm. They can also be used for precise application of these inputs, substantially reducing the amount of physical labor required.

Sensors and Internet of Things (IoT)

Onsite sensors collect accurate farm-level data (e.g., soil moisture and pH, temperature, humidity) to help farmers make decisions related to sowing, irrigation, fertilizer application, and harvesting. Wireless networking technologies like Low-Power Wide Area Network (LPWAN) and cloud computing enable data transmission.

Key Applications of Precision Agriculture

Weather Monitoring

Weather monitoring involves the continuous study and analysis of key weather parameters (temperature, moisture, pressure, wind velocity) to inform planting, harvesting, and irrigation decisions. aWhere’s platform uses 1.9 million virtual weather stations to put farmers within 6.4 km of a local weather station.

Soil Monitoring

Soil monitoring is the measurement and monitoring of soil’s physical and biochemical attributes such as nutrients, microbes, and water. This allows farmers to tailor fertilizer application to the needs of their farms. Soil testing is usually done using on-site sensors.

Pest Surveillance and Disease Monitoring

Pest and disease monitoring solutions employ simple hand-held devices, remote sensing, and on-site sensors to provide timely and reliable advice for integrated pest management. PlantVillage has aggregated over 50,000 infected plant images and become the world’s largest open-access library of crop health knowledge.

Yield Monitoring

Yield monitoring and mapping uses GPS technology and on-site sensors to track crop yields, enabling farmers to compare performance across different test plots or crop varieties. Yield maps display the spatial and temporal variability in crop yields.

Smart Irrigation

Smart irrigation systems use technology to assess and cater to the needs of the farm, either through soil sensors or weather-based systems measuring evapotranspiration. These systems help to improve water-use efficiency. In Vietnam, farmers using smart irrigation practices were able to save 13–20 percent of the irrigation water compared to conventional AWD.

Precision Spraying

Precision spraying ensures the application of an optimum amount of crop protection chemical. In fact, the use of drones for cotton spraying in China by the company DJI is reported to be 40 times more efficient than manual spraying (Trendov et al., 2019).

Key Statistics & Data

• World population is estimated to increase to almost 10 billion by 2050 (Elferink & Schierhorn, 2016).
• Agriculture accounts for more than 70% of global freshwater use.
• Smallholder farmers constitute about 90% of all farmers worldwide.
• Digital extension has a benefit-cost ratio of up to 10:1 from farmers applying lime after SMS advisories (Fabregas et al., 2019).
• Fall armyworm infestations destroyed 20-30% of the crop.
• The soil health card scheme has reduced the use of chemical fertilisers by 8-10% (Tiwari, 2020).

Methodology

The paper’s methodology includes a literature review of existing research and reports, as well as case studies and examples to illustrate the application of various technologies. Specific methodologies for data collection and analysis within the cited studies vary, including surveys, remote sensing analysis, and econometric modeling.

Implications and Conclusions

Digital technologies hold immense potential for transforming agriculture and improving the livelihoods of smallholder farmers. However, realizing this potential requires addressing challenges such as digital infrastructure gaps, lack of awareness and skills, and societal barriers like gender inequality. Key implications include the need for cross-sector collaboration, user-centered design, and enabling policies to support the adoption and scalability of digital agriculture solutions. Furthermore, ensuring data privacy and security is crucial to fostering trust and encouraging greater adoption among farmers. Future research should focus on developing sustainable business models, promoting interoperability and open standards, and ensuring gender inclusivity in the design and implementation of digital agriculture interventions.