The INCREASE project: Intelligent Collections of food-legume genetic resources for European agrofood systems.

Food legumes are crucial for all agriculture-related societal challenges, including climate change mitigation, agrobiodiversity conservation, sustainable agriculture, food security and human health. The transition to plant-based diets, largely based on food legumes, could present major opportunities for adaptation and mitigation, generating significant co-benefits for human health. The characterization, maintenance and exploitation of food-legume genetic resources, to date largely unexploited, form the core development of both sustainable agriculture and a healthy food system. INCREASE will implement, on chickpea (Cicer arietinum), common bean (Phaseolus vulgaris), lentil (Lens culinaris) and lupin (Lupinus albus and L. mutabilis), a new approach to conserve, manage and characterize genetic resources. Intelligent Collections, consisting of nested core collections composed of single-seed descent-purified accessions (i.e., inbred lines), will be developed, exploiting germplasm available both from genebanks and on-farm and subjected to different levels of genotypic and phenotypic characterization. Phenotyping and gene discovery activities will meet, via a participatory approach, the needs of various actors, including breeders, scientists, farmers and agri-food and non-food industries, exploiting also the power of massive metabolomics and transcriptomics and of artificial intelligence and smart tools. Moreover, INCREASE will test, with a citizen science experiment, an innovative system of conservation and use of genetic resources based on a decentralized approach for data management and dynamic conservation. By promoting the use of food legumes, improving their quality, adaptation and yield and boosting the competitiveness of the agriculture and food sector, the INCREASE strategy will have a major impact on economy and society and represents a case study of integrative and participatory approaches towards conservation and exploitation of crop genetic resources.

New biomolecular tools for aerobiological monitoring: Identification of major allergenic Poaceae species through fast real-time PCR.

Grasses (Poaceae) are very common plants, which are widespread in all environments and urban areas. Despite their economical importance, they can represent a problem to humans due to their abundant production of allergenic pollen. Detailed information about the pollen season for these species is needed in order to plan adequate therapies and to warn allergic people about the risks they take in certain areas at certain moments. Moreover, precise identification of the causative species and their allergens is necessary when the patient is treated with allergen-specific immunotherapy. The intrafamily morphological similarity of grass pollen grains makes it impossible to distinguish which particular species is present in the atmosphere at a given moment. This study aimed at developing new biomolecular tools to analyze aerobiological samples and identifying major allergenic Poaceae taxa at subfamily or species level, exploiting fast real-time PCR. Protocols were tested for DNA extraction from pollen sampled with volumetric and gravimetric methods. A fragment of the matK plastidial gene was amplified and sequenced in Poaceae species known to have high allergological impact. Species- and subfamily-specific primer-probe systems were designed and tested in fast real-time PCRs to evaluate the presence of these taxa in aerobiological pollen samples. Species-specific systems were obtained for four of five studied species. A primer-probe set was also proposed for the detection of Pooideae (a grass subfamily that includes also major cereal grains) in aerobiological samples, as this subfamily includes species carrying both grass allergens from groups 1 and 5. These, among the 11 groups in which grass pollen allergens are classified, are considered responsible for the most frequent and severe symptoms.

Time linkages between pollination onsets of different taxa in Perugia, Central Italy--an update.

INTRODUCTION AND OBJECTIVE: In the last decades, increasing attention has been paid to pollinosis. Numerous studies have been carried out concerning the pollination timing of allergenic plant species and the possibility to forecast its beginning and intensity using several statistical methods and models. This study proposes a simple and fast method to identify in advance the time lapse in which the pollination of some allergenic taxa should start. MATERIALS AND METHODS: The times of pollination of 14 taxa were recorded in the area of Perugia (Central Italy) by means of a 7-volumetric Hirst-Type pollen trap. For a 30-year period (1984-2013), annual starting dates were calculated for each taxa, using the 5% method (Lejoly-Gabriel). The time linkages between these starting dates were then estimated, considering them in pairs and calculating linear regression coefficients. RESULTS: For the significantly linked species, forecasting models were obtained by means of linear regression analysis. To apply these models to the ongoing pollen season, pollination beginning of the earlier species has to be calculated using a sum-based method. From this date, through the obtained equations, it is possible to predict the approximate period in which the pollination of the second linked taxa should start. CONCLUSIONS: The possibility to predict the start of the pollen season of these taxa could be of great importance from the allergological point of view. In fact, an early or delayed flowering can have considerable effects in the prophylaxis programming and efficacy.