Report on quality characteristics of varieties to be used in organic farming

The key questions which will be addressed in this report are: • Which variety characteristics are important for organic farming and are they different from conventional farmers demand? • What is an “appropriate“ variety for organic farming? • Is the actual variety offer available to organic farmers satisfactory? Is it different per crops type and/or per geographic area? • How should variety trials be conducted in order to supply the information needed by organic operators? The main answers may be synthesized as follows: Characteristics of varieties to be used in organic farming are partly different from the ones requested in conventional farming. Main differences are related to yield stability, processing properties and root-system development; The definition of “appropriateness”, related to variety for organic farming, is not easy to state as it may involves different aspects, depending on perspective (producers, processor, trader etc.). A list of characters that should be considered within the “appropriateness” concept is presented in the report; Among involved Members States experts there is no common evaluation of the actual variety availability: in general if for cereals there is a reasonably good level of availability, for vegetables and fodder crops mixtures the situation is never very positive even if it varies greatly among Member States; Valuable guidelines for cereal variety testing in organic farming have been produced by the COST 860 action “SUSVAR” (Sustainable low-input cereal production: required variety characteristics and crop diversity) and they are summarized in the report; Guidelines for vegetable variety testing are difficult to identify as among vegetables species the characteristics and requirements are very different. In the report some indications are reported. Recommendation for variety evaluation and testing in organic farming Several recommendation result from the report. For clarity sake they have been grouped in 3 parts, depending on which institution they are aimed to: Recommendations to EU and international authorities: • To implement the possibility offered by EU directives on seed trading (EEC Dir. 66/4021; EEC Dir. 66/4012 and EC Dir. 2002/553) to run controls on seeds for organic farming additional to the routine controls. This possibility may be used to evaluate variety appropriateness to organic farming conditions and consequently orientate the choice of varieties that seed companies offer to the organic sector. • To consider specific variety traits requested by organic farming systems in the test for variety inclusion into the registers of varieties. Recommendations to Member States: • To keep record of the variety requested for derogation and make it public. It may be a useful instrument for seed producers’ orientation. • To include specific local (National/Regional) demands from organic farmers in the variety trials. It means to include varieties that are supposed as fit to organic conditions by farmers but also to include specific characteristics in the evaluation criteria. • To promote public breeding for organic farming and to support spin-off of seed companies dedicated to organic seed production. A low-cost option may be participatory breeding that combines the advantages of introducing variety traits asked for by organic producers and facilitate dissemination. Recommendations to other stakeholders: • To involve nurseries in the debate about organic variety choice as they result to be an important bottle-neck for the use of organic seeds in vegetable production. • To promote timely programming of variety used and amounts of seed needed among producers in order to facilitate seed producers and distributors but at the same time to grand producers the right variety choice

Italian networking of public experimental sites working on Organic Farming: an experience of networking in research

Research in organic farming, especially with an agro-ecological approach, is strictly linked to local conditions and interactions among several variables. The paper will present an example of a process developed in the Italian context to integrate and harmonize research in organic farming from different research stations, with different local conditions. Collecting similar and comparable data from different research stations participating in the network can have an interesting impact in results of organic farming experiments, due to high number and variability of data. ARSIA Toscana, with the aim of creating an Italian National Network of public experimental stations working in organic farming, involved FIRAB as a facilitator of the participatory process. The proposed process follows two parallel paths: individual questionnaire to single experimental sites to know the specific activities in place on organic farming and a series of meetings with direct involvement and exchange among researchers and policy makers from different regions to comment results of the questionnaire and future development of organic research in public experimental stations. The main outcome of the process has been the choice of a specific transversal topic to build the network: the development of synthetic agro-environmental indicators

A robust feature tracker for active surveillance of outdoor scenes

In this paper, we propose a robust real-time object detection system for outdoor image sequences acquired by an active camera. The system is able to compensate background changes due to the camera motion and to detect mobile objects in the scene. Background compensation is performed by assuming a simple translation (displacement vector) of the background from the previous to the current frame and by applying the well-known tracker proposed by Lucas and Kanade. A reference map containing all well trackable features is maintained and updated by the system at each frame by introducing new good features related to new regions that appear in the current image. A new method is applied to reject badly tracked features. The current frame and the background after compensation are processed by a change detection method in order to locate mobile objects. Results are presented in the contest of a visual-based surveillance system for monitoring outdoor enviroments

Deep generative adversarial residual convolutional networks for real-world super-resolution

Most current deep learning based single image super-resolution (SISR) methods focus on designing deeper / wider models to learn the non-linear mapping between low-resolution (LR) inputs and the high-resolution (HR) outputs from a large number of paired (LR/HR) training data. They usually take as assumption that the LR image is a bicubic down-sampled version of the HR image. However, such degradation process is not available in real-world settings i.e. inherent sensor noise, stochastic noise, compression artifacts, possible mismatch between image degradation process and camera device. It reduces significantly the performance of current SISR methods due to real-world image corruptions. To address these problems, we propose a deep Super-Resolution Residual Convolutional Generative Adversarial Network (SRResCGAN1) to follow the real-world degradation settings by adversarial training the model with pixel-wise supervision in the HR domain from its generated LR counterpart. The proposed network exploits the residual learning by minimizing the energy-based objective function with powerful image regularization and convex optimization techniques. We demonstrate our proposed approach in quantitative and qualitative experiments that generalize robustly to real input and it is easy to deploy for other downscaling operators and mobile/embedded devices

Visual Object Tracking in First Person Vision

The understanding of human-object interactions is fundamental in First Person Vision (FPV). Visual tracking algorithms which follow the objects manipulated by the camera wearer can provide useful information to effectively model such interactions. In the last years, the computer vision community has significantly improved the performance of tracking algorithms for a large variety of target objects and scenarios. Despite a few previous attempts to exploit trackers in the FPV domain, a methodical analysis of the performance of state-of-the-art trackers is still missing. This research gap raises the question of whether current solutions can be used “off-the-shelf” or more domain-specific investigations should be carried out. This paper aims to provide answers to such questions. We present the first systematic investigation of single object tracking in FPV. Our study extensively analyses the performance of 42 algorithms including generic object trackers and baseline FPV-specific trackers. The analysis is carried out by focusing on different aspects of the FPV setting, introducing new performance measures, and in relation to FPV-specific tasks. The study is made possible through the introduction of TREK-150, a novel benchmark dataset composed of 150 densely annotated video sequences. Our results show that object tracking in FPV poses new challenges to current visual trackers. We highlight the factors causing such behavior and point out possible research directions. Despite their difficulties, we prove that trackers bring benefits to FPV downstream tasks requiring short-term object tracking. We expect that generic object tracking will gain popularity in FPV as new and FPV-specific methodologies are investigated

Young drivers’ pedestrian anti-collision braking operation data modelling for ADAS development

Smart cities and smart mobility come from intelligent systems designed by humans. Artificial Intelligence (AI) is contributing significantly to the development of these systems, and the automotive industry is the most prominent example of "smart" technology entering the market: there are Advanced Driver Assistance System (ADAS), Radar/LIDAR detection units and camera-based Computer Vision systems that can assess driving conditions. Actually, these technologies have become consumer goods and services in mass-produced vehicles to provide human drivers with tools for a more comfortable and safer driving. Nevertheless, they need to be further improved for progress in the transition to fully automated driving or simply to increase vehicle automation levels. To this end, it becomes imperative to accurately predict driver’s decisions, model human driving behaviors, and introduce more accurate risk assessment metrics. This paper presents a system that can learn to predict the future braking behavior of a driver in a typically urban vehicle-pedestrian conflict, i.e., when a pedestrian enters a zebra crossing from the curb and a vehicle is approaching. The algorithm proposes a sequential prediction of relevant operational indicators that continuously describe the encounter process. A car driving simulator was used to collect reliable data on braking behaviours of a cohort of 68 licensed university students, who faced the same urban scenario. The vehicle speed, steering wheel angle, and pedal activity were recorded as the participants approached the crosswalk, along with the azimuth angle of the pedestrian and the relative longitudinal distance between the vehicle and the pedestrian: the proposed system employs the vehicle information as human driving decisions and the pedestrian information as explanatory variables of the environmental state. In fact, the pedestrian’s polar coordinates are usually calculated by an on-board millimeter-wave radar which is typically used to perceive the environment around a vehicle. All mentioned information is represented in the form of time series data and is used to train a recurrent neural network in a supervised machine learning process. The main purpose of this research is to define a system of behavioral profiles in non-collision conditions that could be used for enhancing the existing intelligent driving systems, e.g., to reduce the number of warnings when the driver is not on a collision course with a pedestrian. Preliminary experiments reveal the feasibility of the proposed system

Report on seed born diseases in organic seed and propagation material

The key questions which will be addressed in this report are: • Are seed born diseases an important factor that prevents seed companies from producing organic seeds and organic farmers from using them? • Which seed treatments are available in organic farming? Which treatments are or will be acceptable? To which degree are they effective? • Are the thresholds for seed born diseases different among Member States? Can this cause unfair competition among farmers and seed producers? • How did the health status of organic seed change in the last years? The main answers may be synthesized as follows: • Seed born diseases are an important factor influencing seed production and seed use in organic agriculture, but they are not the only obstacle that exists at the moment. • Awareness on the importance of seed health has increased considerably; “conventional” organizations such as ISF (International Seed Federation) or ISTA (International Seed Testing Association) give statements on seed health and seed treatments for organic agriculture. • In the last 5 to 10 years several methods and products of non-synthetic seed treatments (physical, microbiological, plant-based etc.) have been successfully tested on different host-parasite combinations and are potentially available for use in organic farming. However, there are no general treatments available that are effective for all host-pathogen combinations. • Due to the importance of seed health in organic agriculture, it is important that organically acceptable seed treatments are identified and authorized in organic seed production. This would assure organic producers reliable seeds for their farming operations. • Besides legal restrictions for quarantine diseases on seeds, most of the Member States have legal thresholds for seed born diseases, which however apply almost exclusively to cereals. For vegetables and legumes, Member States only have general statements on seed health. • Thresholds for seed born diseases in cereals vary between Member States. This may cause distortion in seed trade and use as one country may allow the import (from another MS) of seeds that do not fulfill certification limits in the importing country, but that are fully certifiable in the MS where they are produced. • Data on the status of organic seed health is available in few countries only. It would be very helpful if the MS kept annual records of the organic seed-lots’ health status as it would allow to monitor the presence of seed born diseases and risks and act consequently on the seeds and the crops. In general, available data for cereals does not show a clear trend of seed health development but rather highlights the influence of climatic condition. There also appears to be a general spreading of Tilletia caries, which may increase with lower control levels, especially with of-farm seed production. Spreading of seed-born diseases is greater in organic farming since few control measures are available. Recommendations for development of the legal basis for organic seed production: • Seed quality refers not only to purity and germination parameters but also to aspects of seed health. • Seed health in organic production is of crucial importance as healthy seeds are the basis for successful production, especially in organic farming systems, where less efficient plant protection agents are available for managing plant diseases and prevention is the main key of success. • There is a need to define and regulate which seed treatments can be permitted in organic farming (methods and products should be listed in the revised EU Reg. 2092/91 in annex II B) • In order to increase the availability of organic seeds and their assortment in terms of varieties, seed treatments (accepted in organic agriculture) should be made possible. • It would be advisable that all treatments which the seeds are subjected to are declared on the label. • Thresholds for seed born diseases in organic seeds must be strict and harmonized among Member States in order to avoid the spread of seed born diseases, difficult to manage in organic farming. Such thresholds must be based on sound scientific basis. • Organic seed-lots’ health status should be monitored on a yearly basis by seed health authorities