Fátima Ezzahra, presentation at the Digital Enterprise Show
In an event that marked a milestone for Biyectiva Technology, our team had the honor of participating in the prestigious Digital Enterprise Show in Malaga. It was there, after a key presentation on July 11, that we won first prize on July 12 for a project as revolutionary as it was innovative: melon maturity detection using Artificial Intelligence (AI). This recognition is not just a technological triumph, but a testament to the effort, passion, and talent that define our team. We want to extend a special congratulations to our colleague Fátima Ezzahra, whose impeccable presentation captivated the jury, and to Sergio Moreno Lorente, who proudly represented Biyectiva Technology at this important event.
Innovation at the Service of the Agro Sector
At Biyectiva, we are a team of engineers with extensive experience in applying Artificial Intelligence techniques in the agro sector. Our track record of successes supports our trajectory, both in Computer Vision (especially in hyperspectral systems) and in Sound Analysis (such as hydrophones). We have AI Doctors, experts in deploying AI systems, and winners of renowned international challenges. We are proud to be one of the few national companies specialized in applying AI to this key sector.
A Market with Great Potential
Our project focuses on a product with two main use cases, each with a significant target market:
- In the field: Helping the farmer decide when to harvest. The portable device allows determining the optimal harvesting time, eliminating the need for specialized personnel, which represents considerable economic savings for individual farmers. In Castilla-La Mancha (CLM) alone, we are talking about more than 4,000 individual melon farmers.
- In the plant: Helps generate ranges and packaging. This system allows separating melon ranges according to their maturity level, opening the door to the creation of premium lines. For processing centers, we estimate a market of around 200 centers in CLM alone, a number that would multiply by 5 or 10 nationwide.
Furthermore, the versatility of this device's hardware means it could be adapted to other fruits (such as watermelon), significantly expanding our potential market in future phases.
A Multimodal and Precise Approach
Unlike traditional maturity detection techniques based on superficial color changes (ineffective in melon), our solution combines two innovative approaches:
- Hyperspectral Vision: We are not limited to the visible spectrum. We use components beyond the visible (ultraviolet and infrared) and AI models to correlate the physical appearance of the melon (netting, patterns, geometry of spots) with its internal maturity.
- Acoustic Analysis: We leverage the variation in density in high-water content fruits as they mature. Using ultrasound waves, we measure the melon's resonance profile, a proven technique for evaluating its internal state.
The combination of these visual and acoustic techniques, along with powerful Machine Learning models, results in the first multimodal mechanism based on AI in the market with these capabilities, capable of accurately estimating the average Brix degrees and, therefore, the internal maturity level of the melon.
Our Roadmap: From Research to Market
Although this project starts from a low technological readiness level (TRL), its innovative and differential nature guarantees a significant impact on the sector and society. Our previous experience with vision and acoustic models in the agro sector allows us to understand the risks well and has led us to plan the project in three key phases:
- Phase A - Hypothesis validation in melon: Based on the validation of physical principles in similar crops (such as watermelon), we will confirm that melon has sufficiently similar characteristics for our hypotheses to be valid. Additionally, our techniques (vision and sound) are an automated improvement of what humans already do intuitively.
- Phase B - Dataset generation for training: We will collect data from between 500 and 600 melons, measuring Brix degrees, applying sound pulses, and performing visual analyses. A Biyectiva team will travel on-site to ensure the quality of these samples.
- Phase C - Model validation and productization analysis phase: This phase will focus on validating the accuracy of our model and charting the path to bring this design and product to market, raising its TRL and transforming this innovation into a commercializable solution.
The Impact in Castilla-La Mancha and Beyond
Castilla-La Mancha is the main melon producer in Spain, with 35% of national production and over 5,400 cultivated hectares. However, much of the cultivation process still relies on traditional methods that introduce inefficiencies. Our multimodal AI system will allow:
- More informed harvesting decisions: Without human intervention and consistently.
- Optimization of triage: Facilitating the creation of different melon quality grades, including premium ranges.
We are convinced that this technology will revolutionize the way melons are cultivated and processed, generating efficiency, reducing costs, and guaranteeing higher final product quality.
This award is an immense boost! to continue developing solutions that make a difference. Thanks to everyone who makes it possible.
Best Startup 2025 Award at Digital Enterprise Show
