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Saudi mango farm cuts irrigation by 50 percent with AI tech | Arab News PK

A Saudi mango farm in Rijal Almaa deployed AI-driven soil moisture sensors and leaf image analysis to cut irrigation by 50% whilst boosting flowering rates to 98% and production by 40%. The system uses automated thresholds (50-60% optimal soil moisture, <850ppm salinity) to schedule watering every 2-5 days, with supplementary apps (Plantix, Agrio, PictureThis) for pest and disease detection.

This Wire brief sits within Fusion42's coverage of Climate Tech. Wire is Fusion42's founder-focused intelligence feed: each story is connected to the funds and startups it names — every one with a live profile on Raise or Scout — so founders can follow the capital and the momentum behind the headline rather than just the headline itself. Wire analysis is one of the live surfaces Arthur, Fusion42's AI co-founder, reasons over.

The Wire takeaway

If you're building agricultural sensors or plant-health imaging software, Saudi Arabia's water scarcity has just created a proven buyer willing to cut irrigation by half and accept 40% yield gains as proof. The farm's homegrown AI application shows the next move: bundled farm-management SaaS, not point sensors.

Read the full story at arabnews.pk

Topics: Climate Tech · agricultural-ai · water-efficiency · soil-sensors · precision-farming · middle-east-agri

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Verified 16 July 2026 · Sources: Fusion42 review