We provide Remote Sensing and AI based reliable tools for trials monitoring

We are a Spanish SME aims at providing technical support for data acquisition, processing, and analysis in field trials (open fields and greenhouse) within Agriculture 4.0.
We operate a broad range of sensors and technologies for high precision data acquisition and analysis by applying scientifically robust methodologies:
• Hyperspectral, multispectral and thermal (high resolution) based remote sensing.
• LiDAR and Laser scanner (airborne and terrestrial)
• (Artificial Intelligent developments) - Computer Vision and Neural Network based applications.
Our team is permanently updating new technical adoptions to cover new cutting-edge requirements in order to provide our clients with turnkey solutions specifically adapted to their needs.
Our expertise is based on more than 10 years successfully working in Plant Phenotyping, Plant Breeding and Bio-stimulants (Bio-solutions) trials in many different target crops (maize, wheat, soybean, cotton, oilseed rape, olives, vineyards, citrus, almonds, peach, tomato, pepper, cucumber, squash, melon, watermelon, okra, lettuce, pumpkin, strawberry, blueberry, blackberry and raspberry among others).

Our proposal would be focused on two different main applications:
• Monitoring your trials by Hyperspectral and thermal High resolution remote sensing:
o Hyperspectral data, allow the assessment of photosynthetic functioning which is a valuable tool to characterize the physiological status, nutritional stress and water stress of plants under different stress levels imposed while providing information potentially linked to yield or plant health.
o Thermal data, It is scientifically proven that the difference between crop temperature (Tc) and air temperature (Ta) is a RELIABLE INDICATOR OF THE WATER STRESS LEVEL. Therefore, it will be an useful tool to assess the behavior of the plants when trying to evaluate their tolerance to different water stress levels.
o LiDAR data will help to understand the behavior of the crops in terms of plant growth and dry/wet biomass.

• Using our Computer Vision and Neural Network based tool (EPYCApp) to automatically characterize the most relevant traits at fruit level (such size, weight, shape, color or diseases resistance among others) for a better understanding of your trials.
For example, in the case you would be interested on testing the behavior of different tomato cultivars to different water stress level or their resistance to a disease or the effect of a bio-stimulant, thanks to this tool you will be able automatically measure and characterize the most relevant traits from a video recorded with a smartphone:
o The yield of each cultivar under different water stress level.
o The yield and the number of fruits affected by a disease of each cultivar.
o The effect of the bio-stimulant at fruit level (size, weight, color, resistance to disease, tolerance to water stress,…) of each cultivar.
o And many other relevant aspects to improve decision making.

Open field and greenhouse trials, plant water stress, plant nutritional stress, early detection of diseases, yield, hyperspectral and thermal remote sensing, LiDAR, AI, Computer Vision, Neural Networks, Plant breeding, Plant phenotyping, Bio-stimulants.

Granted in 2020 by CDTI (a Business Public Entity under the Ministry of Science, Innovation and Universities of Spain that promotes innovation and technological development of Spanish companies) for developing EPYCApp.

Please, in the link below you will see a post of LinkedIn explaining how this tool works.

https://www.linkedin.com/posts/noel-vargas-velasco-5089605b_phenotyping-highthroughputphenotyping-plantbreeding-ugcPost-6993519903169236992-Hy2H?utm_source=share&utm_medium=member_desktop

Recently granted by the Spanish Ministry of Science and Innovation as innovative SME seal in recognition of our broad activity in Research and Development projects.