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IntroductionTomato is a high economic value crop worldwide with recognized nutritional properties and diverse postharvest potential. Nowadays, there is an emerging awareness about the exploitation and utilization of underutilized traditional germplasm in modern breeding programs. In this context, the existing diversity among Greek accessions in terms of their postharvest life and nutritional value remains largely unexplored.MethodsHerein, a detailed evaluation of 130 tomato Greek accessions for postharvest and nutritional characteristics was performed, using metabolomics and transcriptomics, leading to the selection of accessions with these interesting traits. ResultsThe results showed remarkable differences among tomato Greek accessions for overall ripening parameters (color, firmness) and weight loss. On the basis of their postharvest performance, a balance between short shelf life (SSL) and long shelf life (LSL) accessions was revealed. Metabolome analysis performed on 14 selected accessions with contrasting shelf-life potential identified a total of 206 phytonutrients and volatile compounds. In turn, transcriptome analysis in fruits from the best SSL and the best LSL accessions revealed remarkable differences in the expression profiles of transcripts involved in key metabolic pathways related to fruit quality and postharvest potential. DiscussionThe pathways towards cell wall synthesis, polyamine synthesis, ABA catabolism, and steroidal alkaloids synthesis were mostly induced in the LSL accession, whereas those related to ethylene biosynthesis, cell wall degradation, isoprenoids, phenylpropanoids, ascorbic acid and aroma (TomloxC) were stimulated in the SSL accession. Overall, these data would provide valuable insights into the molecular mechanism towards enhancing shelf-life and improving flavor and aroma of modern tomato cultivars.

AbstractBackgroundAlpaca (Vicugna pacos), llama (Lama glama), vicugna (Vicugna vicugna) and guanaco (Lama guanicoe), are the camelid species distributed over the Andean high-altitude grasslands, the Altiplano, and the Patagonian arid steppes. Despite the wide interest on these animals, most of the loci under selection are still unknown. Using whole-genome sequencing (WGS) data we investigated the occurrence and the distribution of Runs Of Homozygosity (ROHs) across the South American Camelids (SACs) genome to identify the genetic relationship between the four species and the potential signatures of selection.ResultsA total of 37 WGS samples covering the four species was included in the final analysis. The multi-dimensional scaling approach showed a clear separation between the four species; however, admixture analysis suggested a strong genetic introgression from vicugna and llama to alpaca. Conversely, very low genetic admixture of the guanaco with the other SACs was found. The four species did not show significant differences in the number, length of ROHs (100-500 kb) and genomic inbreeding values. Longer ROHs (> 500 kb) were found almost exclusively in alpaca. Seven overlapping ROHs were shared by alpacas, encompassing nine loci (FGF5, LOC107034918, PRDM8, ANTXR2, LOC102534792, BSN, LOC116284892, DAG1andRIC8B) while nine overlapping ROHs were found in llama with twenty-five loci annotated (ERC2, FZD9, BAZ1B, BCL7B, LOC116284208, TBL2, MLXIPL, PHF20, TRNAD-AUC, LOC116284365, RBM39, ARFGEF2, DCAF5, EXD2, HSPB11, LRRC42, LDLRAD1, TMEM59, LOC107033213, TCEANC2, LOC102545169, LOC116278408, SMIM15, NDUFAF2andRCOR1). Four overlapping ROHs, with three annotated loci (DLG1, KAT6BandPDE4D) and three overlapping ROHs, with seven annotated genes (ATP6V1E1, BCL2L13, LOC116276952, BID, KAT6B, LOC116282667andLOC107034552), were detected for vicugna and guanaco, respectively.ConclusionsThe signatures of selection revealed genomic areas potentially selected for production traits as well as for natural adaptation to harsh environment. Alpaca and llama hint a selection driven by environment as well as by farming purpose while vicugna and guanaco showed selection signals for adaptation to harsh environment. Interesting, signatures of selection onKAT6Bgene were identified for both vicugna and guanaco, suggesting a positive effect on wild populations fitness. Such information may be of interest to further ecological and animal production studies.

Abstract Eggplant (Solanum melongena) is a major vegetable crop with great potential for genetic improvement owing to its large and mostly untapped genetic diversity. It is closely related to over 500 species of Solanum subgenus Leptostemonum that belong to its primary, secondary, and tertiary genepools and exhibit a wide range of characteristics useful for eggplant breeding, including traits adaptive to climate change. Germplasm banks worldwide hold more than 19 000 accessions of eggplant and related species, most of which have yet to be evaluated. Nonetheless, eggplant breeding using the cultivated S. melongena genepool has yielded significantly improved varieties. To overcome current breeding challenges and for adaptation to climate change, a qualitative leap forward in eggplant breeding is necessary. The initial findings from introgression breeding in eggplant indicate that unleashing the diversity present in its relatives can greatly contribute to eggplant breeding. The recent creation of new genetic resources such as mutant libraries, core collections, recombinant inbred lines, and sets of introgression lines will be another crucial element and will require the support of new genomics tools and biotechnological developments. The systematic utilization of eggplant genetic resources supported by international initiatives will be critical for a much-needed eggplant breeding revolution to address the challenges posed by climate change.

This study analyzes, through remote sensing techniques and innovative clouding services, the recent land use dynamics in the North-Roman littoral zone, an area where the latest development has witnessed an important reconversion of purely rural areas to new residential and commercial services. The survey area includes five municipalities and encompasses important infrastructure, such as the “Leonardo Da Vinci” Airport and the harbor of Civitavecchia. The proximity to the metropolis, supported by an efficient network of connections, has modified the urban and peri-urban structure of these areas, which were formerly exclusively agricultural. Hereby, urban expansion has been quantified by classifying Landsat satellite images using the cloud computing platform “Google Earth Engine” (GEE). Landsat multispectral images from 1985 up to 2020 were used for the diachronic analysis, with a five-yearly interval. In order to achieve a high accuracy of the final result, work was carried out along the temporal dimension of the images, selecting specific time windows for the creation of datasets, which were adjusted by the information related to the NDVI index variation through time. This implementation showed interesting improvements in the model performance for each year, suggesting the importance of the NDVI standard deviation parameter. The results showed an increase in the overall accuracy, being from 90 to 97%, with improvements in distinguishing urban surfaces from impervious surfaces. The final results highlighted a significant increase in the study area of the “Urban” and “Woodland” classes over the 35-year time span that was considered, being 67.4 km2 and 70.4 km2, respectively. The accurate obtained results have allowed us to quantify and understand the landscape transformations in the area of interest, with particular reference to the dynamics of urban development.

Nuclear magnetic resonance (NMR) profiling, sample georeferentiaton, and geostatistics are applied to evaluate the spatial variability of metabolic expression of durum wheat in fields managed by precision agriculture. Durum wheat at three different vegetation stages, grown in two different places of the Basilicata region, in Italy, is analyzed by NMR. The spatial variability, within each field, of metabolites, quantified by NMR, is evidenced by appropriate geostatistic tools through the definition of a suitable metabolic index. Metabolic maps are compared to highlight the effects of soil and farming strategies.