Identification of potato varieties suitable for cold storage and reconditioning: A safer alternative to anti-sprouting chemicals for potato sprouting control.

Low temperature storage as an alternative to anti-sprouting chemicals in potato storage may induce reducing sugars (RS) accumulation (i.e. glucose and fructose) in potato tubers. This phenomenon is called "cold induced sweetening" (CIS) and occurs in certain varieties. CIS leads to a decrease in the organoleptic qualities and darkening of processed potato and the accumulation of toxic molecules such as acrylamide. To identify potato varieties suitable for storage at low temperatures, we screened six commercial processing varieties: Lady Claire (LC), Verdi, Kiebitz (KB), Pirol, Agria and Markies for their CIS characteristics and sprout-forming potential after storage at 4 °C and 8 °C. Our findings reveal that 4 °C storage allows for efficient sprout reduction in all six tested varieties for up to 4.5 months of storage. Three CIS-resistant varieties, namely Verdi, Lady Claire and Kiebitz, were identified as able to be stored for up to four months at 4 °C with limited increase in glucose content. Conversely, Pirol, Agria and Markies showed an increase in glucose content with a decrease in storage temperature and can be considered as CIS-susceptible varieties. After processing into crisps, the CIS-susceptible varieties displayed poor crisp color quality (brown to black color crisps) after storage for two months at 4 °C compared to the storage at 8 °C, whereas the CIS-resistant varieties had good crisp color quality (pale yellow color crisps) after storage at both 4 and 8 °C. Interestingly, the trends of total RS and/or glucose content in the CIS-resistant and in the CIS-susceptible varieties were correlated with the trends in Vacuolar Invertase (VInv) gene expression for most varieties, as well as with the trends in acrylamide content after processing. In addition, reconditioning of Markies variety after storage at 4 °C by gradually increasing the temperature to 15 °C resulted in a significant decrease of VInv transcript levels (reduction of 80 %), acrylamide content (reduction of 75 %) and glucose content when compared to a storage at 4 °C without reconditioning. Those results demonstrate that the reconditioning technique is a key factor for a sustainable potato storage and for improving the quality of processed potatoes.

Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies.

Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.

Can sensory boar taint levels be explained by fatty acid composition and emitted volatile organic compounds in addition to androstenone and skatole content?

This study aimed at understanding which molecules were responsible for the differences existing in boar taint sensory evaluation. The latter was therefore linked to the results of skatole and androstenone chemical analyses, fatty acid composition and VOC profiles of heated backfat. This study confirmed that some discrepancy exists between chemical analysis and sensory evaluation of tainted backfats. Significant correlations between human nose scores and fatty acid composition were not revealed. Strong correlations between emissions and contents in skatole and androstenone were found. Oxidation products of polyunsaturated fatty acids, with fatty odor descriptors, were found to be more present in the VOC profiles of boar fat considered untainted through the human nose methodology. Weak coefficient of determination for partial least square regression indicates that other factors, yet unknown, are responsible for sensory evaluation outcomes. These findings hence support the idea that high human nose score is mainly due to boar taint compounds rather than general differences in VOC profiles.

Risk factors associated with cassava brown streak disease dissemination through seed pathways in Eastern D.R. Congo.

Vegetatively propagated crops are particularly prone to disease dissemination through their seed systems. Strict phytosanitary measures are important to limit the impact of diseases as illustrated by the potato seed system in Europe. Cassava brown streak disease (CBSD) is a devastating disease caused by two viral species collectively named cassava brown streak viruses (CBSVs). CBSD can cause substantial root yield losses of up to 100% in the worst affected areas and is easily transmitted through stem cuttings. In Eastern and Central Africa, the epidemiology of CBSVs in the local socio-economical context of production remains poorly known while a better understanding would be an asset to properly manage the disease. This lack of information explains partially the limited efficiency of current regulatory schemes in increasing the availability of quality seed to smallholders and mitigating the spread of pests and diseases. This study surveyed the epidemiology of CBSVs in Uvira territory, Eastern D.R. Congo, and its drivers using a multivariate approach combining farmer's interview, field observation, sampling and molecular detection of CBSVs. Investigation on the epidemiology of CBSD revealed that three clusters in the study area could be identified using five most significant factors: (i) symptoms incidence, (ii) number of whiteflies, (iii) types of foliar symptoms, (iv) cutting's pathways and (v) plant age. Among the three clusters identified, one proved to be potentially interesting for seed multiplication activities since the disease pressure was the lowest. Through risk assessment, we also identified several key socio-economic determinants on disease epidemy: (i) factors related to farmer's knowledge and awareness (knowledge of cassava pests and diseases, knowledge of management practices, support from extension services and management strategies applied), (ii) factors related to the geographical location of farmer's fields (proximity to borders, proximity to town, distance to acquire cuttings), as well as (iii) the pathways used to acquire cuttings.

Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium).

Managers need to know how to mitigate rising stream water temperature (WT) due to climate change. This requires identifying the environmental drivers that influence thermal regime and determining the spatial area where interventions are most effective. We hypothesized that (i) extreme thermal events can be influenced by a set of environmental factors that reduce thermal sensitivity and (ii) the role played by those factors varies spatially. To test these hypotheses, we (i) determined which of the environmental variables reported to be the most influential affected WT and (ii)identified the spatial scales over which those environmental variables influenced WT. To this end, the influence of multi-scale environmental variables, namely land cover, topography (channel slope, elevation), hydromorphology (channel sinuosity, water level, watershed area, baseflow index) and shade conditions, was analyzed on the three model variables (day thermal sensitivity, night thermal sensitivity, and non-convective thermal flux) in the model developed by Georges et al. (2021) of the temporal thermal dynamics of daily maximum WT during extreme events. Values were calculated on six spatial scales (the entire upstream catchment and the associated 1 km and 2 km circular buffer, and 50 m wide corridors on each side of the stream with the associated 1 km and 2 km circular buffer). The period considered was 17 extreme days during the summer identified by Georges et al. (2021) based on WT data measured every 10 min for 7 years (2012-2018) at 92 measurement sites. Sites were located evenly throughout the Wallonia (southern Belgium) hydrological network. Results showed that shade, baseflow index (a proxy of the influence of groundwater), water level and watershed area were the most significant variables influencing thermal sensitivity. Since managers with finite financial and human resources can act on only a few environmental variables, we advocate restoring and preserving the vegetation cover that limits solar radiation on the watercourse as a cost-effective solution to reduce thermal sensitivity. Moreover, management at small spatial scale (50 m riparian buffer) should be strategically promoted (for finance and staffing) as our results show that a larger management scale is not more effective in reducing thermal sensitivity to extreme events.

Validation of Dairy Cow Bodyweight Prediction Using Traits Easily Recorded by Dairy Herd Improvement Organizations and Its Potential Improvement Using Feature Selection Algorithms.

Knowing the body weight (BW) of a cow at a specific moment or measuring its changes through time is of interest for management purposes. The current work aimed to validate the feasibility of predicting BW using the day in milk, parity, milk yield, and milk mid-infrared (MIR) spectrum from a multiple-country dataset and reduce the number of predictors to limit the risk of over-fitting and potentially improve its accuracy. The BW modeling procedure involved feature selections and herd-independent validation in identifying the most interesting subsets of predictors and then external validation of the models. From 1849 records collected in 9 herds from 360 Holstein cows, the best performing models achieved a root mean square error (RMSE) for the herd-independent validation between 52 ± 2.34 kg to 56 ± 3.16 kg, including from 5 to 62 predictors. Among these models, three performed remarkably well in external validation using an independent dataset (N = 4067), resulting in RMSE ranging from 52 to 56 kg. The results suggest that multiple optimal BW predictive models coexist due to the high correlations between adjacent spectral points.

Appropriate Data Quality Checks Improve the Reliability of Values Predicted from Milk Mid-Infrared Spectra.

The use of abnormal milk mid-infrared (MIR) spectrum strongly affects prediction quality, even if the prediction equations used are accurate. So, this record must be detected after or before the prediction process to avoid erroneous spectral extrapolation or the use of poor-quality spectral data by dairy herd improvement (DHI) organizations. For financial or practical reasons, adapting the quality protocol currently used to improve the accuracy of fat and protein contents is unfeasible. This study proposed three different statistical methods that would be easy to implement by DHI organizations to solve this issue: the deletion of 1% of the extreme high and low predictive values (M1), the deletion of records based on the Global-H (GH) distance (M2), and the deletion of records based on the absolute fat residual value (M3). Additionally, the combinations of these three methods were investigated. A total of 346,818 milk samples were analyzed by MIR spectrometry to predict the contents of fat, protein, and fatty acids. Then, the same traits were also predicted externally using their corresponded standardized MIR spectra. The interest in cleaning procedures was assessed by estimating the root mean square differences (RMSDs) between those internal and external predicted phenotypes. All methods allowed for a decrease in the RMSD, with a gain ranging from 0.32% to 41.39%. Based on the obtained results, the "M1 and M2" combination should be preferred to be more parsimonious in the data loss, as it had the higher ratio of RMSD gain to data loss. This method deleted the records based on the 2% extreme predictions and a GH threshold set at 5. However, to ensure the lowest RMSD, the "M2 or M3" combination, considering a GH threshold of 5 and an absolute fat residual difference set at 0.30 g/dL of milk, was the most relevant. Both combinations involved M2 confirming the high interest of calculating the GH distance for all samples to predict. However, if it is impossible to estimate the GH distance due to a lack of relevant information to compute this statistical parameter, the obtained results recommended the use of M1 combined with M3. The limitation used in M3 must be adapted by the DHI, as this will depend on the spectral data and the equation used. The methodology proposed in this study can be generalized for other MIR-based phenotypes.

Use of New Glycerol-Based Dendrimers for Essential Oils Encapsulation: Optimization of Stirring Time and Rate Using a Plackett-Burman Design and a Surface Response Methodology.

Essential oils are used in an increasing number of applications including biopesticides. Their volatility minimizes the risk of residue but can also be a constraint if the release is rapid and uncontrolled. Solutions allowing the encapsulation of essential oils are therefore strongly researched. In this study, essential oils encapsulation was carried out within dendrimers to control their volatility. Indeed, a spontaneous complexation occurs in a solution of dendrimers with essential oils which maintains it longer. Six parameters (temperature, stirring rate, relative concentration, solvent volume, stirring time, and pH) of this reaction has been optimized by two steps: first a screening of the parameters that influence the encapsulation with a Plackett-Burmann design the most followed by an optimization of those ones by a surface response methodology. In this study, two essential oils with herbicide properties were used: the essential oils of Cinnamomum zeylanicum Blume and Cymbopogon winterianus Jowitt; and four biosourced dendrimers: glycerodendrimers derived from polypropylenimine and polyamidoamine, a glyceroclikdendrimer, and a glyceroladendrimer. Meta-analysis of all Plackett-Burman assays determined that rate and stirring time were effective on the retention rate thereby these parameters were used for the surface response methodology part. Each combination gives a different optimum depending on the structure of these molecules.

Identifying key pathways in manure and sewage management of dairy farming based on a quantitative typology: A case study in China.

With the greatly increased demand for animal products, the global dairy sector has experienced rapid expansion and intensification. The correspondingly increasing manure and sewage produced has been the major contributor to environmental burden and human health, especially in developing countries like China. Both worldwide environmental concerns and growing awareness of the circular economy have focused the governments' attention on environmental policies related to sustainable manure and sewage management (MSM). However, inherently dynamic decision-making processes of individual farms result in a great diversity of MSM practices, which leads to enormous difficulties and complexity in further sustainability and policy evaluation. Hence, it is essential to explore the key MSM pathways to represent diversity at a scientific and statistic view. While it is rarely practiced, particularly in China's dairy farming. We used China as a case study to develop the key MSM pathways using data from the nationwide survey of 306 scale dairy farms via a quantitative typology methodology. The results by optimal clustering solution revealed four key pathways based on the individual practices which are associated with the collection, storage, and processing and utilization stages. Furthermore, general characteristics were compared to identify potential determinant factors. It revealed that the major indicators such as resource endowments, milk productivity and quality, and revenues and expenditure showed a consistently increasing trend among pathways. The results indicated resource availability and intensive degree, to a certain extent, affected the farmers' selection. The possibilities of performing sustainability and policy evaluation at a higher scale were also demonstrated. Overall, the identified key pathways can help to know regional waste utilization and economic potential to evolve their MSM strategies. They are especially critical for developing countries to obtain typical MSM profiles and formulate targeted policies more effectively, aiming to promote dairy sustainable development and achieve the circular economy globally.

The Walloon farmers position differently their ideal dairy production system between a global-based intensive and a local-based extensive model of farm.

Dairy farming systems are evolving. This study presents dairy producers' perceptions of their ideal future farm (IFF) to ensure revenue, and attempts to determine the reasons for this choice, the environmental aspects related to this choice, the proximity between the current farm and the IFF and the requirements for reaching this IFF. Just before the end of the European milk quota, a total of 245 Walloon dairy producers answered a survey about the characteristics of their IFF and other socio-environmental-economic information. A multiple correspondence analysis (MCA) was carried out using seven characteristics of the IFF (intensive vs. extensive, specialised vs. diversified, strongly vs. weakly based on new technologies, managed by a group of managers vs. an independent farmer, employed vs. familial workforce, local vs. global market, standard vs. quality-differentiated production) to observe the relationships between them. Based on the main contributors to the second dimension of the MCA, this axis was defined as an IFF gradient between the local-based extensive (LBE) producers (26%) and the global-based intensive (GBI) producers (46%). The differences of IFF gradient between modalities of categorical variables were estimated using generalised linear models. Pearson correlations were calculated between the scores on the IFF gradient and quantitative variables. Finally, frequencies of IFF characteristics and the corresponding characteristic for the current situation were calculated to determine the percentages of "unhappy" producers. Some reasons for the choice of IFF by the producers have been highlighted in this study. Environmental initiatives were more valued by LBE than GBI producers. Low similarity was observed between the current farm situation of the respondents and their IFF choice. LBE and GBI producers differed significantly regarding domains of formation (technical and bureaucratic vs. transformation and diversification respectively) and paths of formation (non-market vs. market respectively). Two kinds of farming systems were considered by dairy producers and some socioeconomic and environmental components differed between them.

Quantitative Structure-Activity Relationship of Humic-Like Biostimulants Derived From Agro-Industrial Byproducts and Energy Crops.

Humic-like substances (HLSs) isolated by alkaline oxidative hydrolysis from lignin-rich agro-industrial residues have been shown to exert biostimulant activity toward maize (Zea mays L.) germination and early growth. The definition of a quantitative structure-activity relationship (QSAR) between HLS and their bioactivity could be useful to predict their biological properties and tailor plant biostimulants for specific agronomic and industrial uses. Here, we created several projection on latent structure (PLS) regression by using published analytical data on the molecular composition of lignin-derived HLS obtained by both 13C-CPMAS-NMR spectra directly on samples and 31P-NMR spectra after derivatization of hydroxyl functions with a P-containing reagent (2-chloro-4,4,5,5-tetramethyl-1,3,2-dioxaphospholane). These spectral data were used to model the effect of HLS on the elongation of primary root, lateral seminal roots, total root apparatus, and coleoptile of maize. The 13C-CPMAS-NMR data suggested that methoxyl and aromatic moieties positively affected plant growth, while the carboxyl/esterified functions showed a negative impact on the overall seedling development. Alkyl C seems to promote Col elongation while concomitantly reducing that of the root system. Additionally, 31P-NMR-derived spectra revealed that the elongation of roots and Col were enhanced by the occurrence of aliphatic hydroxyl groups, and guaiacyl and p-Hydroxyphenyl lignin monomers. The PLS models based on raw dataset from 13C-CPMAS-NMR spectra explained more than 74% of the variance for the length of lateral seminal roots, total root system and coleoptile, while other parameters derived from 13C-CPMAS-NMR spectra, namely the Hydrophobicity and Hydrophilicity of materials were necessary to explain 83% of the variance of the primary root length. The results from 31P-NMR spectra explained the observed biological variance by 90, 96, 96, and 93% for the length of primary root, lateral seminal roots, total root system and coleoptile, respectively. This work shows that different NMR spectroscopy techniques can be used to build up PLS models which can predict the bioactivity of lignin-derived HLS toward early growth of maize plants. The established QSAR may also be exploited to enhance by chemical techniques the bioactive properties of HLS and enhance their plant stimulation capacity.

Ablation of non-coding RNAs affects bovine leukemia virus B lymphocyte proliferation and abrogates oncogenesis.

Viruses have developed different strategies to escape from immune response. Among these, viral non-coding RNAs are invisible to the immune system and may affect the fate of the host cell. Bovine leukemia virus (BLV) encodes both short (miRNAs) and long (antisense AS1 and AS2) non-coding RNAs. To elucidate the mechanisms associated with BLV non-coding RNAs, we performed phenotypic and transcriptomic analyzes in a reverse genetics system. RNA sequencing of B-lymphocytes revealed that cell proliferation is the most significant mechanism associated with ablation of the viral non-coding RNAs. To assess the biological relevance of this observation, we determined the cell kinetic parameters in vivo using intravenous injection of BrdU and CFSE. Fitting the data to a mathematical model provided the rates of cell proliferation and death. Our data show that deletion of miRNAs correlates with reduced proliferation of the infected cell and lack of pathogenesis.

Composition, Seasonal Variation, and Biological Activities of Lantana camara Essential Oils from Côte d'Ivoire.

This work aims to study the variations in the composition of Lantana camara leaf, flower, and stem essential oils over two years. L. camara organs were harvested in Bregbo (East Côte d'Ivoire) each month from June 2015 to June 2017. The essential oils were obtained by hydrodistillation and characterized by GC-MS and 13C NMR. Eighty-four compounds accounting for 84.4-99.1% of the essential oils have been identified. The essential oils hydrodistillated from L. camara are dominated by sesquiterpenes such as (E)-ß-caryophyllene and α-humulene, which were found in all samples. Some monoterpenes such as thymol, sabinene, and α-pinene were also present. Statistical analysis (principal component analysis and clustering) revealed a high variability in essential oil composition between the different organs and also within the studied periods, as the thymol proportion was higher during flowering and fruiting months. In addition, the stem, flower, and fruit essential oils were more concentrated in thymol than the leaf essential oils. The proportions of (E)-ß-caryophyllene and α-humulene were strictly inverted with the thymol proportion throughout the harvest period or vegetative cycle. The antioxidant, anti-inflammatory and insecticidal activities of leaves and flowers essential oils were also studied. Results showed that L. camara leaf and flower essential oils displayed high antioxidant, anti-inflammatory and insecticidal activities.

Virus Detection by High-Throughput Sequencing of Small RNAs: Large-Scale Performance Testing of Sequence Analysis Strategies.

Recent developments in high-throughput sequencing (HTS), also called next-generation sequencing (NGS), technologies and bioinformatics have drastically changed research on viral pathogens and spurred growing interest in the field of virus diagnostics. However, the reliability of HTS-based virus detection protocols must be evaluated before adopting them for diagnostics. Many different bioinformatics algorithms aimed at detecting viruses in HTS data have been reported but little attention has been paid thus far to their sensitivity and reliability for diagnostic purposes. Therefore, we compared the ability of 21 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 12 plant viruses through a double-blind large-scale performance test using 10 datasets of 21- to 24-nucleotide small RNA (sRNA) sequences from three different infected plants. The sensitivity of virus detection ranged between 35 and 100% among participants, with a marked negative effect when sequence depth decreased. The false-positive detection rate was very low and mainly related to the identification of host genome-integrated viral sequences or misinterpretation of the results. Reproducibility was high (91.6%). This work revealed the key influence of bioinformatics strategies for the sensitive detection of viruses in HTS sRNA datasets and, more specifically (i) the difficulty in detecting viral agents when they are novel or their sRNA abundance is low, (ii) the influence of key parameters at both assembly and annotation steps, (iii) the importance of completeness of reference sequence databases, and (iv) the significant level of scientific expertise needed when interpreting pipeline results. Overall, this work underlines key parameters and proposes recommendations for reliable sRNA-based detection of known and unknown viruses.

Evaluation of λ-Carrageenan, CpG-ODN, Glycine Betaine, Spirulina platensis, and Ergosterol as Elicitors for Control of Zymoseptoria tritici in Wheat.

Wheat crops are constantly challenged by the pathogen Zymoseptoria tritici, responsible for Septoria tritici Blotch (STB) disease. The present study reports the evaluation of five elicitor compounds (λ-carrageenan, cytosine-phosphate-guanine oligodesoxynucleotide motifs [CpG ODN], glycine betaine, Spirulina platensis, and ergosterol) for the protection of wheat against STB in order to offer new alternative tools to farmers for sustainable crop protection. Screening of elicitors of wheat defenses was carried out through a succession of experiments: biocidal in vitro tests enabled checking for any fungicidal activities, glasshouse experiments allowed determination of the efficacy of a given compound in protecting wheat against STB, and quantitative reverse-transcription polymerase chain reaction biomolecular tests investigated the relative expression of 23 defense genes in treated versus untreated plants. Therefore, we demonstrated that λ-carrageenan, CpG-ODN, glycine betaine, S. platensis, and ergosterol are potential elicitors of wheat defenses. Foliar treatment with these compounds conferred protection of wheat by up to approximately 70% against Z. tritici under semicontrolled conditions and induced both salicylic acid- and jasmonic acid-dependent signaling pathways in the plant. These findings contribute to extending the narrow list of potential elicitors of wheat defenses against Z. tritici.

The limited contribution of large trees to annual biomass production in an old-growth tropical forest.

Although the importance of large trees regarding biodiversity and carbon stock in old-growth forests is undeniable, their annual contribution to biomass production and carbon uptake remains poorly studied at the stand level. To clarify the role of large trees in biomass production, we used data of tree growth, mortality, and recruitment monitored during 20 yr in 10 4-ha plots in a species-rich tropical forest (Central African Republic). Using a random block design, three different silvicultural treatments, control, logged, and logged + thinned, were applied in the 10 plots. Annual biomass gains and losses were analyzed in relation to the relative biomass abundance of large trees and by tree size classes using a spatial bootstrap procedure. Although large trees had high individual growth rates and constituted a substantial amount of biomass, stand-level biomass production decreased with the abundance of large trees in all treatments and plots. The contribution of large trees to annual stand-level biomass production appeared limited in comparison to that of small trees. This pattern did not only originate from differences in abundance of small vs. large trees or differences in initial biomass stocks among tree size classes, but also from a reduced relative growth rate of large trees and a relatively constant mortality rate among tree size classes. In a context in which large trees are increasingly gaining attention as being a valuable and a key structural characteristic of natural forests, the present study brought key insights to better gauge the relatively limited role of large trees in annual stand-level biomass production. In terms of carbon uptake, these results suggest, as already demonstrated, a low net carbon uptake of old-growth forests in comparison to that of logged forests. Tropical forests that reach a successional stage with relatively high density of large trees progressively cease to be carbon sinks as large trees contribute sparsely or even negatively to the carbon uptake at the stand level.

Meat retail conditions within the establishments of Kigali city (Rwanda): bacteriological quality and risk factors for Salmonella occurrence.

Meat constitutes one of the major vehicles for human foodborne infections. This study aimed to assess the retail conditions and to determine the microbiological quality and safety of meat retailed within the establishments of Kigali (Rwanda). A questionnaire survey was carried out in 150 retail outlets to characterise meat retail conditions. Additionally, 270 retail meat samples were analysed for the enumeration of hygiene indicator bacteria (total mesophilic bacteria and Escherichia coli) and for the qualitative detection of Salmonella, using conventional culture methods. The results revealed that beef was the predominant meat sold within the retail premises of Kigali city, while meat from non-bovine animal species was mainly sold in large establishments. Salmonella was detected in 19.6% of all the retailed meat samples evaluated, whereas the mean loads for total mesophilic bacteria and E. coli were 7.3 and 3.5 log cfu/g, respectively. Three factors, namely the temperature conditions of the meat under retail, the cleanability of the used meat cutting boards, and the training of personnel in hygienic meat handling practices, were found to be significantly (p ≤ 0.05) associated with the risk of Salmonella occurrence in the retailed meat. The findings from this study highlight the need for improvements in hygienic meat handling practices, particularly, in small and medium meat retail establishments in Kigali.

Influence of rhizobacterial volatiles on the root system architecture and the production and allocation of biomass in the model grass Brachypodium distachyon (L.) P. Beauv.

BACKGROUND: Plant growth-promoting rhizobacteria are increasingly being seen as a way of complementing conventional inputs in agricultural systems. The effects on their host plants are diverse and include volatile-mediated growth enhancement. This study sought to assess the effects of bacterial volatiles on the biomass production and root system architecture of the model grass Brachypodium distachyon (L.) Beauv. RESULTS: An in vitro experiment allowing plant-bacteria interaction throughout the gaseous phase without any physical contact was used to screen 19 bacterial strains for their growth-promotion ability over a 10-day co-cultivation period. Five groups of bacteria were defined and characterised based on their combined influence on biomass production and root system architecture. The observed effects ranged from unchanged to greatly increased biomass production coupled with increased root length and branching. Primary root length was increased only by the volatile compounds emitted by Enterobacter cloacae JM22 and Bacillus pumilus T4. Overall, the most significant results were obtained with Bacillus subtilis GB03, which induced an 81 % increase in total biomass, as well as enhancing total root length, total secondary root length and total adventitious root length by 88.5, 201.5 and 474.5 %, respectively. CONCLUSIONS: This study is the first report on bacterial volatile-mediated growth promotion of a grass plant. Contrasting modulations of biomass production coupled with changes in root system architecture were observed. Most of the strains that increased total plant biomass also modulated adventitious root growth. Under our screening conditions, total biomass production was strongly correlated with the length and branching of the root system components, except for primary root length. An analysis of the emission kinetics of the bacterial volatile compounds is being undertaken and should lead to the identification of the compounds responsible for the observed growth-promotion effects. Within the context of the inherent characteristics of our in vitro system, this paper identifies the next critical experimental steps and discusses them from both a fundamental and an applied perspective.

Aggregation behavior of Harmonia axyridis under non-wintering conditions.

The invasive multicolored Asian ladybeetle, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), aggregates inside dwellings during winter to avoid cold weather. This adaptive behavior disturbs homeowners, because of the large numbers of individuals that aggregate, which induces allergic reactions. The migratory flight patterns of this species have been well documented, with individuals preferentially moving toward prominent and high color contrast elements. However, the factors involved in the selection of aggregation sites by this species have yet to be elucidated. Here, we evaluated the influence of (i) the density of individuals and (ii) the type of available shelters on decisions by H. axyridis to settle and aggregate under shelters. A dual choice bioassay conducted in the laboratory demonstrated the presence of mutual attraction to conspecifics. We also found that individuals preferentially settled under red covered shelters compared to transparent shelters, and that the type of shelter outweighed the effect of social interactions among conspecifics. Moreover, this experiment was performed under non-wintering conditions, providing the first evidence that aggregative behavior in this species can also occur under those specific conditions.

Plutella xylostella (L.) infestations at varying temperatures induce the emission of specific volatile blends by Arabidopsis thaliana (L.) Heynh.

The effect of combined abiotic and biotic factors on plant volatile organic compound (VOC) emissions is poorly understood. This study evaluated the VOC emissions produced by Arabidopsis thaliana (L.) Col-0 subjected to 3 temperature regimes (17, 22, and 27°C) in the presence and absence of Plutella xylostella larvae over 2 time intervals (0-4 and 4-8 h), in comparison to control plants. The analyses of VOCs emitted by Arabidopsis plants were made by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). It was found that certain volatile groups (e.g., alcohols, ketones, aldehydes, and terpenes) are induced by both single factors (temperature or larval infestation) and combined factors (temperature and larvae interactions), whereas other volatile groups (e.g., isothiocyanates [ITCs] and nitrile) were specific to the experimental conditions. ITCs (mainly 4-methylpentyl isothiocyanate) were emitted from plants subjected to larval infestation at 17 and 27°C after the 2 time intervals. The proportions of sulfides (mainly dimethyl disulfide) and 4-(methylthio) butanenitrile were significantly higher on herbivore-infested plants at 22°C compared to the other treatments. Overall, our findings indicate that changes in all experimental conditions caused significant changes to the VOC emissions of Arabidopsis plants. Therefore, the interaction between temperature and larval feeding may represent an important factor determining the variability of volatile emissions by plants subjected to multiple simultaneous factors.