Air Quality and Comfort Characterisation within an Electric Vehicle Cabin in Heating and Cooling Operations.

This work is aimed at the experimental characterisation of air quality and thermal profile within an electric vehicle cabin, measuring at the same time the HVAC system energy consumption. Pollutant concentrations in the vehicle cabin are measured by means of a low-cost system of sensors. The effects of the HVAC system configuration, such as fresh-air and recirculation mode, on cabin air quality, are discussed. It is shown that the PM concentrations observed in recirculation mode are lower than those in fresh-air mode, while VOC concentrations are generally higher in recirculation than in fresh-air mode. The energy consumption is compared in different configurations of the HVAC system. The novelty of this work is the combined measurement of important comfort parameters such as air temperature distribution and air quality within the vehicle, together with the real time energy consumption of the HVAC system. A wider concept of comfort is enabled, based on the use of low-cost sensors in the automotive field.

Pea Grain Protein Content Across Italian Environments: Genetic Relationship With Grain Yield, and Opportunities for Genome-Enabled Selection for Protein Yield.

Wider pea (Pisum sativum L.) cultivation has great interest for European agriculture, owing to its favorable environmental impact and provision of high-protein feedstuff. This work aimed to investigate the extent of genotype × environment interaction (GEI), genetically based trade-offs and polygenic control for crude protein content and grain yield of pea targeted to Italian environments, and to assess the efficiency of genomic selection (GS) as an alternative to phenotypic selection (PS) to increase protein yield per unit area. Some 306 genotypes belonging to three connected recombinant inbred line (RIL) populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield and protein content on a dry matter basis in three autumn-sown environments of northern or central Italy. Line variation for mean protein content ranged from 21.7 to 26.6%. Purely genetic effects, compared with GEI effects, were over two-fold larger for protein content, and over 2-fold smaller for grain and protein yield per unit area. Grain yield and protein content exhibited no inverse genetic correlation. A genome-wide association study revealed a definite polygenic control not only for grain yield but also for protein content, with small amounts of trait variation accounted for by individual loci. On average, the GS predictive ability for individual RIL populations based on the rrBLUP model (which was selected out of four tested models) using by turns two environments for selection and one for validation was moderately high for protein content (0.53) and moderate for grain yield (0.40) and protein yield (0.41). These values were about halved for inter-environment, inter-population predictions using one RIL population for model construction to predict data of the other populations. The comparison between GS and PS for protein yield based on predicted gains per unit time and similar evaluation costs indicated an advantage of GS for model construction including the target RIL population and, in case of multi-year PS, even for model training based on data of a non-target population. In conclusion, protein content is less challenging than grain yield for phenotypic or genome-enabled improvement, and GS is promising for the simultaneous improvement of both traits.

Linear models for diallel crosses: a review with R functions.

KEY MESSAGE: A new R-software procedure for fixed/random Diallel models was developed. We eased the diallel schemes approach by considering them as specific cases with different parameterisations of a general linear model. Diallel experiments are based on a set of possible crosses between some homozygous (inbred) lines. For these experiments, six main diallel models are available in literature, to quantify genetic effects, such as general combining ability (GCA), specific combining ability (SCA), reciprocal (maternal) effects and heterosis. Those models tend to be presented as separate entities, to be fitted by using specialised software. In this manuscript, we reinforce the idea that diallel models should be better regarded as specific cases (different parameterisations) of a general linear model and might be fitted with general purpose software facilities, as used for all other types of linear models. We start from the estimation of fixed genetical effects within the R environment and try to bridge the gap between diallel models, linear models and ordinary least squares estimation (OLS). First, we review the main diallel models in literature. Second, we build a set of tools to enable geneticists, plant/animal breeders and students to fit diallel models by using the most widely known R functions for OLS fitting, i.e. the 'lm()' function and related methods. Here, we give three examples to show how diallel models can be built by using the typical process of GLMs and fitted, inspected and processed as all other types of linear models in R. Finally, we give a fourth example to show how our tools can be also used to fit random/mixed effect diallel models in the Bayesian framework.

Exploring Heterosis in Melon (Cucumis melo L.).

Heterosis is the superiority of an F1 hybrid over its parents. Since this phenomenon is still unclear in melon, a half diallel experiment based on eight genetically distant breeding lines was conducted in six environments of Central Italy, assessing commercially important traits: yield, total soluble solids (TSS), and days to ripening (DTR). To estimate the additive (general combining ability; GCA) and the non-additive gene effects (specific combining ability; SCA), yield was analyzed by Griffing's methods two and four, and the results were compared to the GGE (Genotype plus Genotype by Environment interaction) biplot methodology; TSS and earliness were evaluated only by Griffing's method four. Overall, GCAs were significantly more relevant than SCAs for all examined traits. Least square means (LsM), mid-parent heterosis (MPH), best-parent heterosis (BPH), as well as Euclidean and Mahalanobis' distances were calculated and compared with the genetic distance (GD). As a few correlations were found statistically significant (only for TSS), it was difficult to predict the value of a hybrid combination only by knowing the genetic distance of its parents. Despite this, heterosis was observed, indicating either the presence of epistatic effects (additive × additive interactions) and/or an underestimate of SCAs embedded within Griffing's method. The significant Env × Entries source of variation suggests development of hybrids in specific environments. The results are discussed with a breeding perspective.

Evaluation of Cross-Species Transferability of SSR Markers in Foeniculum vulgare.

Fennel (Foeniculum vulgare) is a species belonging to the Apiaceae family, well known for its nutritional and pharmacological properties. Despite the economic and agricultural relevance, its genomic and transcriptomic data remain poor. Microsatellites-also known as simple sequence repeats (SSRs)-are codominant markers widely used to perform cross-amplification tests starting from markers developed in related species. SSRs represent a powerful tool, especially for those species lacking genomic information. In this study, a set of primers previously designed in Daucus carota for polymorphic SSR loci was tested in commercial varieties and breeding lines of fennel in order to: (i) test their cross-genera transferability, (ii) look at their efficiency in assessing genetic diversity, and (iii) identify their usefulness for marker-assisted selection (MAS) in breeding programs. Thirty-nine SSR markers from carrot were selected and tested for their transferability score, and only 23% of them resulted suitable for fennel. The low rate of SSR transferability between the two species evidences the difficulties of the use of genomic SSR in cross-genera transferability.

Pea genomic selection for Italian environments.

BACKGROUND: A thorough verification of the ability of genomic selection (GS) to predict estimated breeding values for pea (Pisum sativum L.) grain yield is pending. Prediction for different environments (inter-environment prediction) has key importance when breeding for target environments featuring high genotype × environment interaction (GEI). The interest of GS would increase if it could display acceptable prediction accuracies in different environments also for germplasm that was not used in model training (inter-population prediction). RESULTS: Some 306 genotypes belonging to three connected RIL populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield, onset of flowering, lodging susceptibility, seed weight and winter plant survival in three autumn-sown environments of northern or central Italy. The large GEI for grain yield and its pattern (implying larger variation across years than sites mainly due to year-to-year variability for low winter temperatures) encouraged the breeding for wide adaptation. Wider within-population than between-population variation was observed for nearly all traits, supporting GS application to many lines of relatively few elite RIL populations. Bayesian Lasso without structure imputation and 1% maximum genotype missing rate (including 6058 polymorphic SNP markers) was selected for GS modelling after assessing different GS models and data configurations. On average, inter-environment predictive ability using intra-population predictions reached 0.30 for yield, 0.65 for onset of flowering, 0.64 for seed weight, and 0.28 for lodging susceptibility. Using inter-population instead of intra-population predictions reduced the inter-environment predictive ability to 0.19 for grain yield, 0.40 for onset of flowering, 0.28 for seed weight, and 0.22 for lodging susceptibility. A comparison of GS vs phenotypic selection (PS) based on predicted genetic gains per unit time for same selection costs suggested greater efficiency of GS for all traits under various selection scenarios. For yield, the advantage in predicted efficiency of GS over PS was at least 80% using intra-population predictions and 20% using inter-population predictions. A genome-wide association study confirmed the highly polygenic control of most traits. CONCLUSIONS: Genome-enabled predictions can increase the efficiency of pea line selection for wide adaptation to Italian environments relative to phenotypic selection.

Genetic Characterization of the Apple Germplasm Collection in Central Italy: The Value of Local Varieties.

In the last 50 years, intensive farming systems have been boosted by modern agricultural techniques and newly bred cultivars. The massive use of few and related cultivars has dramatically reduced the apple genetic diversity of local varieties, confined to marginal areas. In Central Italy a limited spread of intensive fruit orchards has made it possible to preserve much of the local genetic diversity, but at the same time the coexistence of both modern and ancient varieties has generated some confusion. The characterization and clarification of possible synonyms, homonyms, and/or labeling errors in old local genetic resources is an issue in the conservation and management of living collections. 175 accessions provided by 10 apple collections, mainly local varieties, some of unknown origin, and well-known modern and ancient varieties, were studied by using 19 SSRs, analyzed by STRUCTURE, Ward's clustering and parentage analysis. We were able to identify 25 duplicates, 9 synonyms, and 9 homonyms. As many as 37 unknown accession were assigned to well known local or commercial varieties. Polyploids made up 20%. Some markers were found to be significantly correlated with morphological traits and the loci associated with the fruit over color were related to QTLs for resistance to biotic stresses, aroma compounds, stiffness, and acidity. In conclusion the gene pool of Central Italy seems to be rather consistent and highly differentiated compared with other European studies (F ST = 0.147). The importance of safeguarding this diversity and the impact on the management of the germplasm living collection is discussed.

Characterization and Phylogenetic Analysis of Ancient Italian Landraces of Pear.

Pear is one of the oldest fruit tree crops and the third most important temperate fruit species. Its domestication took place independently in the Far East (China) and in the Caucasus region. While the origin of Eastern Asian cultivars is clear, that of European cultivars is still in doubt. Italy has a wealth of local varieties and genetic resources safeguarded by several public and private collections to face the erosion caused by the introduction of improved varieties in specialized orchards. The objectives of the present study were: (i) to characterize the existing germplasm through nuclear (SSR) and (ii) to clarify the genetic divergence between local and cultivated populations through chloroplast DNA (cpDNA) markers in order to provide insights into phylogenetic relationships of Pyrus spp. For this reason, 95 entries from five different germplasm collections, including nine European, Mediterranean and Eastern Asian species, were analyzed, and the intergenic accD-psaI sequences were compared to the worldwide distributed dataset encompassing a total of 298 sequences from 26 different Pyrus species. The nine nuclear SSRs were able to identify a total of 179 alleles, with a loci polymorphism P = 0.89. Most of the variation (97%) was found within groups. Five accessions from different sources were confirmed to be the same. Eight out of 20 accessions of unknown origin were identified, and six synonyms were detected. Locus NH030a was found to be monomorphic in all the cultivated accessions and in reference species interfertile with P. communis, leading to hypothesize selection pressures for adaptation to cultivation. The cpDNA sequences of the 95 accessions were represented by 14 haplotypes, six of which (derived from P. communis, P. cossonii and P. ussuriensis) are recorded here for the first time and may suggest the ancient origin of some local varieties. The network analysis of the 298 cpDNA sequences allowed two different haplogroups, Eastern and Western Eurasia, to be defined, supporting recent views of a clear division between Occidental and Oriental species. By combining the results from nuclear and uniparental markers, it was possible to better define many unknown accessions.

Understanding Genetic Diversity and Population Structure of a Poa pratensis Worldwide Collection through Morphological, Nuclear and Chloroplast Diversity Analysis.

Poa pratensis L. is a forage and turf grass species well adapted to a wide range of mesic to moist habitats. Due to its genome complexity little is known regarding evolution, genome composition and intraspecific phylogenetic relationships of this species. In the present study we investigated the morphological and genetic diversity of 33 P. pratensis accessions from 23 different countries using both nuclear and chloroplast molecular markers as well as flow cytometry of somatic tissues. This with the aim of shedding light on the genetic diversity and phylogenetic relationships of the collection that includes both cultivated and wild materials. Morphological characterization showed that the most relevant traits able to distinguish cultivated from wild forms were spring growth habit and leaf colour. The genome size analysis revealed high variability both within and between accessions in both wild and cultivated materials. The sequence analysis of the trnL-F chloroplast region revealed a low polymorphism level that could be the result of the complex mode of reproduction of this species. In addition, a strong reduction of chloroplast SSR variability was detected in cultivated materials, where only two alleles were conserved out of the four present in wild accessions. Contrarily, at nuclear level, high variability exist in the collection where the analysis of 11 SSR loci allowed the detection of a total of 91 different alleles. A Bayesian analysis performed on nuclear SSR data revealed that studied materials belong to two main clusters. While wild materials are equally represented in both clusters, the domesticated forms are mostly belonging to cluster P2 which is characterized by lower genetic diversity compared to the cluster P1. In the Neighbour Joining tree no clear distinction was found between accessions with the exception of those from China and Mongolia that were clearly separated from all the others.

Identifying commercially relevant Echinacea species by AFLP molecular markers.

The rising interest in medicinal plants has brought several species of the genus Echinacea to the attention of many scientists. Echinacea angustifolia, E. pallida, and E. purpurea are the most important for their immunological properties, well known and widely used by the native Americans. The three species are easily distinguishable on the basis of their morphological characteristics, but it would be difficult, if not impossible, to distinguish them in commercial preparations of ground, dry plant parts of E. purpurea (the most valuable species for chemotherapeutic properties) mixed with the other two species. Species-specific molecular markers could be useful to address this issue. In the present work, using fresh material collected from cultivated Echinacea spp., AFLP analysis was used to discriminate the three species and to detect species-specific DNA fragments. By using 14 primer combinations it was possible to detect a total of 994 fragments, of which 565 were polymorphic. Overall, 89 fragments were unique to E. purpurea, 32 to E. angustifolia, and 26 to E. pallida. E+CAC/M+AAT or E+CAC/M+AGC alone provided 13, 9, and 4 or 7, 5, and 5 specific fragments for E. purpurea, E. angustifolia, and E. pallida, respectively. A validation trial to confirm the results was carried out on bulked samples of 23 accessions covering most of the genetic diversity of the three species. The results are discussed in terms of practical applications in the field of popular medicine, detecting frauds, and implications for the genus Echinacea.