In the March issue of Fruits, vegetables and flowers you will find the opinion article entitled “The role of InnovPlantProtect in Organic Farming: Paths to sustainable and efficient solutions”, in which the executive director of InnovPlantProtect (InPP), António Saraiva, reveals how our CoLAB is contributing to the success of organic farming.
“By boosting research, collaboration and knowledge sharing, InPP is helping to solve the central challenges of this practice [organic farming], allowing it to expand and enhancing the supply of agricultural products to consumers. The solutions developed by InPP make organic farming a more viable option for producers,” says the executive director.
Read the full article and find out how we are shaping the future of agriculture.
We thank Frutas, legumes e flores magazine for its recognition and reiterate our commitment to the agriculture of the future.
Imagine a future where drones and artificial intelligence work together to protect your vineyards. That's what the AI4Leafhopper project is making a reality!
Manisha Sirsat, a researcher on the AI4Leafhopper team, has developed two artificial intelligence models that analyze the aerial images captured by our latest generation drone... and these models make it possible:
geolocation of each vine
to know if there are vine failures
quickly identify “sick” vines”
optimize the application of treatments
The result? Growers can have a detailed view of the health of their vineyards, detect problems early and make more informed decisions.
AI4Leafhopper is a project led by InPP and funded by the ICAERUS Horizon Europe program, which began in April 2024 and ended on April 30 with a final meeting involving the six European projects approved in the 1st edition of the ICAERUS program's PULL applications. The project team presented the AI-based models for detecting and monitoring the impact of the green leafhopper on vineyards.
The AI4Leafhopper project, InnovPlantProtect used a state-of-the-art drone to monitor the impact of the green leafhopper in the vineyards of our partners Reynolds Wine Growers and João Portugal Ramos. Although the results show that this advanced technology is more effective at detecting attacks at advanced stages, we are excited about the potential of this tool to provide valuable data for the management of this harmful insect.
We believe that with more research, we can refine our solution to detect early attacks and prevent significant damage to vineyards. Transforming the monitoring of this pest is where we want to go, always with the aim of protecting vineyards and guaranteeing the quality of production for winegrowers.
Over the next few days we'll be revealing everything that the AI4Leafhopper project is making a reality and how drones and artificial intelligence are working together to create a more sustainable future for viticulture. Stay tuned!
AI4Leafhopper, funded by the ICAERUS Horizon Europe program, which began in April 2024, is now in its final stages. The development phase of the project, which took place in the field, is now over and the final stage is to present the solutions developed by our team on Portuguese soil to the market.
Nature Plants highlights the advantages of new genome editing techniques but warns of three crucial aspects that still need to be addressed.
“The rapid development of plant biotechnologies is profoundly shaping crop improvement and catalyzing the next revolution in agriculture,” writes an editorial recently published by Nature Plants, entitled Next-generation crop engineering (Next-generation crop engineering).
Crop improvement no longer has to depend on naturally occurring mutations and artificially generated variations can be the raw material for further improvement, the text argues. “A much broader spectrum of phenotypic space is ready for exploration, allowing the development of ideal phenotypes adapted to the heterogeneous environments of Earth, or even Space,” argue the authors of the paper. article, He concluded that “a new agricultural revolution driven by biotechnology could be just around the corner”.
Image: Francesco Gallarotti/ Unsplash
The editorial refers to the promise and advantages of the new genome editing techniques, particularly compared to classical breeding, but not only. And it warns of three crucial factors that are still missing in order to achieve high levels of variation through gene editing: 1) a better understanding of the key regulators for genes that are important from an evolutionary or developmental point of view; 2) being able to dissect networks of genes that control phenotypes of interest and regulatory networks in cis that affect gene expression; 3) to establish stable and efficient transformation and regeneration procedures for most species.
Unless genetic editing in planta is developed quickly, breeding based on gene editing will be unable to benefit recalcitrant species. It is also recalled that there are alternative strategies for engineering new generation crops, such as the transfection of viral RNA in sprays, which allows for the temporary adjustment of agronomic characteristics without modifying the genetic material.
The DGAV has announced new requirements for citrus production and marketing, due to the African citrus psyllid plague.
The technical requirements for the production and marketing of citrus fruits and other rutaceous plants in a place free from Trioza erytreae, the insect vector of the disease citrus greening, were recently updated and published by the Directorate-General for Food and Veterinary (DGAV).
The rutaceae are a family of trees in which the genus Citrus is imperative from the point of view of economic value. O citrus greening, greening citrus greening, Huanglongbing disease or citrus greening is caused by the African citrus psyllid (Trioza erytreae), an insect vector that also causes direct damage to citrus fruits.
“In view of the detection of Trioza erytreae in some regions of the country and given the expansion that has already occurred in the area infested by this insect, we have tried to ensure a set of conditions to ensure the continuity of production and marketing of citrus propagating material in regions where the pest is present,” explain the DGAV officials in a press release. document. The update was motivated by “experience gained in the meantime” and by the new legislation in force: Annex VIII of Implementing Regulation (EU) 2019/2072 and Ordinance no. 142/2020.
A Trioza erytreae is a quarantine pest on national territory.
In the T. erytreae, In addition to the obligatory declaration of mother or nursery plants, citrus and other rutaceous plants must be produced “in a place with complete physical protection against this insect” and have been subject to two official inspections in the last growing season without showing any symptoms of the pest.
For marketing, the plants must also be kept in a place with complete physical protection against this insect “and come from exempt areas (outside infested zones and buffer zones) or from nurseries located in demarcated zones”, among other requirements, which aim to guarantee that no infestation occurs.
InPP has a cooperation project with the DGAV to take part in the task force phytosanitary measures and to support the biological control plan with a view to controlling the Trioza erytreae.
Researchers at InPP are developing machine learning methods for predicting phenotypic traits from genetic information of key crops. The project is led by Manisha Sirsat, from the Data Management and Risk Analysis Department, which is headed by Ricardo Ramiro, in collaboration with the Protection of Specific Crops Department, headed by Paula Oblessuc.
Over the last decade, machine learning has become part of our everyday lives, when it suggests the next song you should listen to or the restaurant you should go to. This branch of artificial intelligence is focused on building models and applications that can learn from data, in order to predict a particular outcome. For this to be possible, large amounts of data are necessary which, until recently, would preclude its application in most fields of biology. However, in the last 20 years, biology has become a data-intensive discipline, due to the revolution brought by high-throughput systems for fields as disparate as genomics and microscopy. Thus, machine learning methods are now being applied to a wide range of biological questions.
At InPP, the team is taking advantage of the availability of high-throughput genomic and phenotypic data for key phenotypes of important crops (e.g. wheat genomes and yield) and using this data to develop machine learning models that can predict the phenotype from the genotype. This approach is termed Genomic Prediction. “The aim is to develop an advanced genomic prediction tool which uses genome-wide genetic markers to predict complex traits,” states Manisha Sirsat. “This will allow us to identify genetic markers that can increase agricultural productivity and that can accelerate plant breeding programs,” adds Ricardo Ramiro.
Image by congerdesign/ Pixabay
Image by annawaldl/ Pixabay
An advanced genomic prediction tool can help accelerate plant breeding programs and increase agricultural productivity.
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