In the mountainous southern Saudi Arabia region, Haswa Mango Farm leverages artificial intelligence and smart farming technologies to enhance fruit quality, reduce water usage, and boost output.

This initiative supports Saudi Arabia’s broader efforts to promote sustainability, innovation, and food security in agriculture.

The farm sits in Hiswah village, roughly 80 minutes by car from Rijal Almaa governorate, spanning about 20,000 square meters with approximately 150 mango trees.

The project, also known as Abdullah Saad Al-Zalfi Farm, was established in early 2019 following studies of the area’s soil and water sources to determine their suitability for mango cultivation.

Jamal Al-Zalfi, whose family has farmed in Rijal Almaa for generations, brings eight years of mango farming expertise.

He has worked to develop the farm by incorporating modern technology and AI, in line with national efforts to promote sustainability, innovation and food security in the agricultural sector.

“The main motivation for introducing AI technologies was to obtain accurate agricultural information to support decision-making, particularly in irrigation scheduling, detecting nutrient deficiencies, and the early identification of insect and fungal pests,” Al-Zalfi told Arab News.

“One of the biggest challenges we faced was determining the correct irrigation schedule, as it directly affects early flowering and production levels.” He added. “Smart technologies have helped improve irrigation management and enhance both the efficiency and quality of the crop.”

The farm’s AI-supported system collects readings from soil-moisture sensors and analyzes magnified images of mango leaves taken with a specialized inspection lens.

The system uses the moisture readings to determine whether irrigation is required after two, three or five days, while image analysis helps to identify nutrient deficiencies, insect infestations and fungal diseases. This allows agricultural decisions to be made earlier and more accurately.

Equipment used at the farm includes an intelligent soil detector, a plant inspection magnifier, a total dissolved solids meter to measure water salinity, and an anemometer to monitor wind speed.

“We continuously monitor soil moisture, irrigation water salinity and nutrient levels,” Al-Zalfi said. “The ideal moisture range around mango trees is between 50 and 60 percent, while irrigation water salinity should preferably not exceed 850 parts per million.”

If soil moisture rises above 70 percent, the farm extends the interval between irrigation cycles. If it falls below 30 percent, the interval is shortened. When salinity levels increase, rainwater is used to help flush accumulated salts from around the roots.

Organic fertilizer is also added every January to support growth and productivity throughout the season.

The irrigation schedule changes according to seasonal conditions as the governorate has a tropical-like climate, moderate temperatures, rainfall during much of the year, nutrient-rich clay soil and fresh water flowing through its valleys.

During the rainy season in Rijal Almaa, from August to October, the trees depend largely on rainfall and often require no additional irrigation.

During the cooler months from November to February, watering is limited to once or twice a month.

In the drier period from March to July, irrigation is scheduled every three to five days according to soil-moisture readings, helping meet the trees’ needs without wasting water or causing stress.

The farm also uses applications including Plantix, Agrio and PictureThis to help diagnose plant diseases and pests, analyze agricultural images and data, review farming practices and prepare technical reports.

Al-Zalfi said that important decisions were verified through official agricultural guidance and field experience.

The farm has also begun developing its own AI-powered application to monitor operations, analyze data and provide agricultural recommendations on a continuous basis.

According to Al-Zalfi, AI-supported irrigation management helped the farm to achieve a flowering rate of more than 98 percent during the 2026 season.

“Flowering began in mid-December 2025, compared with February in previous seasons, when higher soil moisture and prolonged irrigation delayed the process.” He said that the more precise irrigation schedule helped to encourage earlier flowering and increased production.

“Scheduling irrigation based on soil-moisture sensor readings reduced irrigation water consumption by around 50 percent compared with previous seasons, without affecting tree health,” he said.

“The smart magnifier and AI-powered image analysis also enabled the early detection of insect pests and diseases and provided accurate control recommendations.”

The measures contributed to healthier fruit, reduced losses and an increase in production of at least 40 percent compared with previous seasons, he added.

The farm’s 2026 production has so far reached about five tonnes, with about one month of the season remaining.

Its average annual production is about four tonnes. “The farm grows several mango varieties, including Tommy Atkins, Angra, Sindri and Glen. Tommy Atkins accounts for about 70 percent of its trees.

“This confirms the success of the project and the region’s strong potential for producing high-quality mangoes.”

Since its establishment, the farm has reached commercial production, maintained a high seedling survival rate and adopted organic fertilization to reduce costs and protect soil fertility.

It has also made seasonal rainwater its main irrigation source and developed into a model of smart agriculture that could help to promote modern farming practices elsewhere in the Kingdom.

Al-Zalfi explained that the irrigation system was supplemented by well water during dry periods after quality testing.

“Tests showed that water from a nearby well has a salinity level of about 800 ppm, within the suitable range for irrigating mango trees.”

He also said that Rijal Almaa’s natural conditions made it well suited to mango cultivation.

Water scarcity is a critical issue in Saudi Arabia, making efficient irrigation essential. AI-driven systems like those at Haswa Farm can help farmers optimize water use and detect problems early, potentially boosting long-term productivity and sustainability.