Amaia Maria Ortiz Barredo

Title: Amaia Maria Ortiz Barredo: Applying Artificial Intelligence to Plant Health

Introduction

Amaia Maria Ortiz Barredo is an inventor based in Vitoria-Gasteiz, Spain. Her patent work focuses on applying computer vision and neural networks to plant health, including disease detection and the measurement of biological objects on plants. She is associated with BASF SE and holds 2 patents.

Latest Patents

One of Ortiz Barredo’s patents, “System and Method for Plant Disease Detection Support,” describes a computer-implemented approach for identifying plant diseases from images. It uses a convolutional neural network trained on a multi-crop dataset. The network combines image classification with crop identification, allowing the system to use information about the plant species when classifying visible disease symptoms. The system receives a plant image and its crop identifier, then produces a result indicating the diseases associated with the symptoms.

Her other patent, “Quantifying Objects on Plants by Estimating the Number of Objects on Plant Parts Such as Leaves, by Convolutional Neural Networks That Provide Density Maps,” addresses the estimation of biological objects on plant parts. A computer processes an image of a plant, identifies a part such as a leaf, divides that part’s image into tiles, and uses a neural network to generate density maps. By combining the maps and integrating their pixel values, the system estimates the number of objects. The method can distinguish object classes to support more targeted countermeasures.

Career Highlights

Ortiz Barredo’s disclosed inventions apply machine-learning techniques to practical agricultural challenges. Her work covers both the classification of plant disease symptoms and the quantitative assessment of biological objects, supporting data-driven plant monitoring.

Collaborations

Ortiz Barredo is associated with BASF SE. Her listed coworkers include Till Eggers and Jone Echazarra Huguet.

Conclusion

Amaia Maria Ortiz Barredo’s patents demonstrate how neural networks and image analysis can support plant disease identification and infestation measurement, connecting artificial intelligence with agricultural monitoring.