Diving Deeper: Grid Sampling vs. Management Zones Sampling

Unlocking higher agricultural productivity and sustainable practices has become a focal point for modern farmers. In the realm of precision agriculture, the method through which soil sampling is conducted plays a pivotal role in shaping decision-making processes in the field, in order to optimize yields while minimizing resource use. Each approach offers distinct advantages, but […]

CLIP for computer vision in agriculture: How powerful is it?

Foundation models refer to a class of large-scale machine learning models that are trained on a broad range of data sources to acquire a wide set of capabilities. These models can be adapted or fine-tuned for various specific tasks and applications. Some examples are CLIP or GPT-4 by OpenAI. An important feature of these models […]

Agriculture’s environmental footprint and Precision agriculture

Nowadays, agriculture is identified as one of the major culprits for environmental degradation for several reasons. Firstly, it significantly contributes to greenhouse gas emissions, primarily methane from livestock and nitrous oxide from fertilizer use, exacerbating global warming and climate change. Additionally, runoff from agricultural fields contributes to water pollution, with synthetic fertilizers and pesticides being [...]

Elevating Agriculture: The Power of Innovation in Maximizing Biopesticide Effectiveness

As we stand at the crossroads of environmental stewardship and agricultural productivity, the role of innovation in shaping the future of agriculture has never been more critical. One such innovation that holds immense promise is the integration of cutting-edge technology to enhance the efficiency of biopesticides. The damage caused by pests in fruit trees, grapevines, […]

Harnessing Precise Localization in AgTech: An Agronomist’s Guide to the Future

In the evolving landscape of agronomy, integrating technology with traditional practices offers unprecedented benefits. Precision agriculture, especially, is transforming the meticulous care of vines and orchards, allowing for smarter, more sustainable interventions. Georeferencing: More than Just a Location Marker Georeferencing does more than just pinpoint locations—it meticulously logs actions and quantities. – For example, in […]

Soil Survey Techniques for Enhanced Precision Farming

Modern soil survey tools and techniques are now widely available to farmers and consultants due to precision agriculture’s data requirements. The cost and speed of data collection are frequently more important than the precision and reliability of the information. Recently, a number of methods have been used to give soil data for site-specific nutrient management. […]

The architecture of the future? Let’s talk about Transformers

Are Convolutional Neural Networks (CNNs) still the most suitable solution for agricultural computer vision tasks such as plant species classification or disease detection? We could debate it since the technology revolutionizing natural language processing also makes waves in computer vision. Let’s talk about Transformers, which have achieved remarkable success in various computer vision tasks, competing […]

Ensuring crop health: Pest detection in arable lands

Arable crops are, undoubtedly, of great economic and social importance for the EU, as half of the total area is used for cereal cultivation. Interestingly, in 2017 the EU produced 309.9 million tonnes of cereals (which is almost 11.9 % of the global harvest) like wheat, maize, barley, rye, and oats, but also rice. However, […]

The Significance of Mid-Season Shoot Thinning

Shoot thinning, or removal, is an essential practice in vineyard management. This process involves selectively removing some of the new growth (shoots) during the growing season. This is typically done in late spring or early summer, once the shoots have begun to grow but before they’ve become woody canes. BenefitsThe reasons for shoot thinning in […]

How Management Zones are Revolutionizing Precision Agriculture

In today’s agriculture, nature protection, and cost efficiency are the two most important aspects. By applying precision farming methods, it is possible to implement the mentioned features. In addition to the production of high-quality and high-quantity crops, the rate of return can also be improved by reducing expenses. Seed, fertilizer, and plant protection agents applied […]

Digital agriculture data interoperability problems, causes and what the future holds

Data interoperability refers to the capacity of different devices and systems to communicate and effectively exchange data with each other. In other words, it is the ability of data to be shared and used across different platforms or systems without any loss of information or functionality. By facilitating interoperability, we ensure that farmers, agronomists, and […]

Efficient Transfer Learning: Fine-tuning or Top-Tuning?

Often fine-tuning a deep neural network is more art than science/engineering. Which is the most optimal learning rate? How many layers shall we freeze? Should we use different learning rates depending on the layer? Most of the time, many of these questions are solved by trial and error (and some AutoML). Would it be a […]

Supervised Contrastive Learning

During the last years, the tendency for applying transfer learning was to directly fine-tune the ImageNet weights in the new domain problem where (usually) there was a lack of images available for training. However, a new trend has arisen recently; in this case, before fine-tuning, there is a previous step called pre-training where the neural […]

AI: a weapon against food waste

The world is currently struggling with a severe food crisis and millions of people around the globe are suffering from malnutrition. As a matter of fact, world hunger affects nearly 10% of people globally, not to mention that from 2019 to 2022 the number of people that are considered to be undernourished increased by 150 […]

Chemical thinning in apple trees using innovative means

Apple tree is one of the most important crops due to the high nutritional value of the apples intended for human consumption. The apple tree cultivation is of high importance for farmers and especially for those who are in areas with very low temperatures, as in order to create apples of excellent quality it needs […]

Applications of Precision Agriculture

Precision agriculture (PA) is not a new trend. As we can observe from many cultivation systems around the world, a lot of producers have adopted precision agriculture technologies on a high scale and are familiar with them. Many technologies have been developed and are already mature to solve crucial matters that concern many producers and […]

ChatGPT: Understanding its Imagination and Creativity

The webs have been buzzing with the new shiny technology, ChatGPT – it managed to create even more noise than its previous version, GPT-3. Both are large language models (Generative Pre-trained Transformers) developed by OpenAI and have been trained on massive text datasets, which allows them to generate human-like text in a wide range of […]

Can agtech solve labor shortage in agriculture?

The agri-food industry is currently facing a severe shortage of labor resources. This is a significant challenge as manual labor is crucial for crop protection and harvesting. In the past 15 years, there has been a 30% decrease in the agricultural workforce which is expected to continue to decline at a rate of 2% per […]

Introduction to knowledge distillation

Imagine that you have trained several models to find the most suitable one for your application and the one that obtained the best performance is also the largest. And, additionally, the slowest one at inference time. This problem is rather common. Very large models that fit the training objectives, but often fail to meet latency, […]

Problems for AI

Artificial Intelligence, Machine Learning, Computer Vision: all of these sound like cool buzzwords, but what kind of problems can they help us with? Here we will try to present some classes of tasks that the aforementioned fields of study can help us tackle, both in the field and anywhere else. Image classificationYou give us a […]

Computer vision for tree crops yield estimation

In any crop, the total production is definitely the most important criterion that shows the agricultural business’s success in revenue in relation to the expenses and simultaneously indicates if the producers achieved their targeted goals. Tree crops put some challenges in counting the fruits and as a consequence making a yield prediction or estimation. However, […]

Spectral imaging for plant health

Over the past decades, agricultural sciences relied principally on reflectance (in the visible, VIS, 0.4–0.7 μm, near-infrared, NIR, 0.7–1.3 μm and short wave-infrared, SWIR, 1.3–2.5 μm regions), thermal (in the thermal infrared, TIR 7.0–20.0 μm region) and fluorescence (at 0.68 and 0.74 μm wavelengths) sensors.  Depending on the application, these sensors can be used for […]

Image annotation for spot spraying

Spot spraying is a new method. It is based on a concept that only the infected areas of the crop should be sprayed and not the whole field. This novelty can be implemented by having a modern sprayer, electronics and the target to spray in the crop. This last requirement is provided by the image […]

The hyper-parameter that makes the difference: The Learning Rate

Some posts ago, we were discussing that AutoML is the best way to avoid the overwhelming process of tuning all the hyper-parameters that modify the behavior of a neural network. However, in AutoML you can also choose which hyper-parameters should be the most relevant ones to explore. So the question is: which hyper-parameter should we […]

Assessment of Different Object Detectors for the Maturity Level Classification of Broccoli Crops Using UAV Imagery

One high-value crop that needs careful handling both throughout the growing season and during post-harvest care is broccoli. Broccoli heads are still plucked by hand since they are easily damaged. Moreover, to harvest broccoli plants when they are in their best condition, human scouting is also needed to initially locate the field segments where multiple […]

Active Learning in Machine Learning: A brief intro

Any team that wants to implement AI methods in their pipeline to offer novel solutions to more complex tasks they are facing, will sooner or later have to deal with the necessity for plenty of relevant data. However, what constitutes plenty? Are 100 samples enough? 1000? 10000? Where does that stop? The lower limit should be […]

Computer vision to easily distinguish among different infestations and plant disorders

In agriculture, it is really difficult to precisely distinguish the diseases, the pests that have infected your crop, and also some nutrient deficiencies, because of the symptoms’ similarities, especially at the beginning of their emergence. This task, although it seems to be easy even for farmers and agronomists, has the possibility to cause serious problems […]

Grow more with less through Smart Farming

Smart Farming technologies hold the promise to bring on the next (fourth) agricultural revolution. The first agricultural revolution occurred roughly 12.000 years ago, with humans farming for the first time. The second revolution came with the reorganization of the farmland during the 17th century, while the third revolution, aka “The green revolution” or modern farming as […]

Data augmentation to overcome data scarcity in precision agriculture

We know deep learning is one of the main techniques to achieve state-of-the-art performances in computer vision methods applied to agriculture. However, this technique requires very large datasets (thousands of images) so that the automatic feature extraction can work accurately, generalize and not overfit. What can be done if we have a small dataset? There are […]

3 annotation rules for every agriculture AI project

Image labeling or annotation is fundamental for every Artificial Intelligent (AI) project. The performance of the trained model is highly dependent on the quality of annotations because this process transfers the human “wisdom” into the AI domain. Lack of clear project objectives, annotation rules, and annotator’s experience are the most common reasons many AI projects fail to achieve their goals. […]

Artificial Intelligence and Machine Learning made simple!

Artificial Intelligence is the field where we try to build systems that perform mental tasks just as we would ourselves, perhaps even in a better way. These could be simple tasks like finding a name in a list of guests, or something more complex like reasoning about the Nature of Man, and everything in between. […]

Yield estimation and maturity level using image annotation

Yield estimation and mapping in orchards are important for growers as it facilitates efficient utilization of resources and improves returns per unit area and time. With accurate knowledge of yield distribution and quantity, a grower can efficiently manage processes such as use of chemicals, fertilization, and thinning. Yield estimation also allows the grower to plan […]

AutoML or how to automatically fine-tune the hyper-parameters of your ML pipeline.

Which is the best learning rate for your ML pipeline? Do you need a high or a low dropout rate? How many convolutional layers do you need and how many filters? And the most important question: do we really care about these decisions? Most of the time, the answer is no. Although these hyper-parameters can […]

Weed detection for precision spraying

Weeds in the field are the enemy for any crop as they compete with the soil nutrients and can become a host for germs and insects threatening the crops. It is therefore essential to be combated effectively and with as little financial burden as possible for the producer and as little pollution for the environment […]

10 things to consider when preparing your agricultural training dataset

The first step toward building a computer vision solution is gathering the necessary images and preparing the training dataset. Something of extreme importance for agricultural environments as they are amongst the most challenging due to the constantly changing environmental conditions. Plant’s shape, size, characteristics, and color change throughout the growing season and are heavily dependent […]

Transfer learning for speeding up your computer vision pipelines

“A fertile soil alone does not carry agriculture to perfection” – E. H. DERBY  “A Defence of Agriculture”, Lessons in Modern Farming Will you learn to play the piano faster if you previously knew how to play the guitar? Probably, yes. At least some notions on music will boost your learning process with the new instrument. […]

Computer vision in citrus

Computer vision can be fundamental in agriculture. It plays a key role in crop resistance against pests, diseases and nutrient deficiencies and provides a method of early prediction and control of plant enemies. Accurate detection of plant enemies leads to increase of productivity, prevents quality loss and decreases the use of plant protection products (PPPs). […]

The hype is disease detection

Agriculture tech (AgTech) is one of the fastest-growing industries in the last five years, accumulating a 410% growth since 2017. Something that can be attributed to recent technological advancements as well as the constant pressure to produce more, with lower costs and in a sustainable way. More precisely, in 2020, AgTech companies received investments of  […]