Colonization of potato plants by soilborne, green fluorescent protein (GFP)-tagged Dickeya sp. IPO2254 was investigated by selective plating, epifluorescence stereo microscopy (ESM), and confocal laser scanning microscopy (CLSM). Replicated experiments were carried out in a greenhouse using plants with an intact root system and plants from which ca. 30% of the lateral roots was removed. One day after soil inoculation, adherence of the pathogen on the roots and the internal colonization of the plants were detected using ESM and CLSM of plant parts embedded in an agar medium. Fifteen days post-soil inoculation, Dickeya sp. was found on average inside 42% of the roots, 13% of the stems, and 13% of the stolons in plants with undamaged roots. At the same time-point, in plants with damaged roots, Dickeya sp. was found inside 50% of the roots, 25% of the stems, and 25% of the stolons. Thirty days postinoculation, some plants showed true blackleg symptoms. In roots, Dickeya sp. was detected in parenchyma cells of the cortex, both inter- and intracellularly. In stems, bacteria were found in xylem vessels and in protoxylem cells. Microscopical observations were confirmed by dilution spread-plating the plant extracts onto agar medium directly after harvest. The implications of infection from soilborne inoculum are discussed.

Possibilities for biocontrol of biovar 3 Dickeya sp. in potato were investigated, using bacteria from rotting potato tissue isolated by dilution plating on nonselective agar media. In a plate assay, 649 isolates were screened for antibiosis against Dickeya sp. IPO2222 and for the production of siderophores. Forty-one isolates (6AE4%) produced antibiotics and 112 isolates (17AE3%) produced siderophores. A selection of 41 antibiotic-producing isolates and 41 siderophore-producing isolates were tested in a potato slice assay for control of the Dickeya sp. Isolates able to reduce rotting of potato tuber tissue by at least 50% of the control were selected. Isolates were characterized by 16S rDNA analysis as Bacillus, Pseudomonas, Rhodococcus, Serratia, Obesumbacterium and Lysinibacillus genera. Twenty-three isolates belonging to different species and genera, 13 producing antibiotics and 10 producing siderophores, were further characterized by testing acyl-homoserine lactone (AHL) production, quorum quenching, motility, biosurfactant production, growth at low (4AE0) and high (10AE0) pH, growth at 10°C under aerobic and anaerobic conditions and auxin production. In replicated greenhouse experiments, four selected antagonists based on the in vitro tests were tested in planta using wounded or intact minitubers of cv. Kondor subsequently inoculated by vacuum infiltration with an antagonist and a GFP (green fluorescent protein)-tagged biovar 3 Dickeya sp. strain. A potato endophyte A30, characterized as S. plymuthica, protected potato plants by reducing blackleg development by 100% and colonization of stems by Dickeya sp. by 97%. The potential use of S. plymuthica A30 for the biocontrol of Dickeya sp. is discussed.

Various models exist for estimating the usual intake distribution from dietary intake data. In this paper, we compare two of these models, the Iowa State University Foods (ISUF) model and the betabinomial-normal (BBN) model and apply them to three different datasets. Intake data are obtained by aggregating over multiple food products and are often non-normal. The ISUF and BBN model both address non-normality. While the two models have similar structures, they show some differences. The ISUF model includes an additional spline transformation for improving the normality of the intake amount distribution, while the BBN model includes the possibility of addressing covariates, such as age or sex. Our analyses showed that for two of the example datasets both models produced similar estimates of the higher percentiles of the usual intake distribution. However, for the third dataset, where the intake amount distribution appear to be multimodal, both models produced different percentile estimates.

In the context of the second framework partnership agreement between the National Institute for Public Health and the Environment of the Netherlands (RIVM) and the European Food Safety Authority (EFSA) acute cumulative dietary exposure assessments were performed for two cumulative assessment groups (CAGs) of pesticides that affect the nervous system: pesticides associated with brain and/or erythrocyte AChE inhibition (CAG-NAN, 47 pesticides) and pesticides associated with functional alterations of the motor division (CAG-NAM, 100 pesticides). The exposure assessments used pesticide monitoring data collected by Member States under their official monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Exposure estimates were obtained for each group of pesticides by means of a 2-dimensional Monte Carlo simulation, which was implemented in the Monte Carlo Risk Assessment (MCRA) software. The scope of the assessment and the parameters to be used for cumulative exposure assessment were discussed and agreed by the Standing Committee on Plants, Animals, Food and Feed (SC PAFF). Based on those discussions, a very conservative tier I modelling approach and a refined, but still conservative tier II modelling approach were used. In these assessments, common risk assessment practice was followed and the cumulative exposure was calculated as total margin of exposure (MOET) at the 50 th , 90 th , 95 th , 99 th and 99.9 th percentiles of the exposure distribution. Five sensitivity analyses aiming to address major uncertainties were performed. The exposure estimates obtained in this report are used in EFSA's scientific report on the cumulative dietary risk characterisation of pesticides that have acute effects on the nervous system.

Recent and systematic evidence on the magnitude of post-harvest losses in sub-Saharan Africa is scarce, hindering the identification of interventions to reduce losses. Here, we unlock standardized and systematically collected information on post-harvest management and farmer-reported post-harvest loss estimates from the Living Standards Measurement Study -Integrated Surveys in Agriculture. Using the data from Ethiopia, the objective is to disentangle factors that induce or relate to post-harvest losses in cereals. The data of approximately 2500 households and 5500 cereal records were analysed. Cereal post-harvest loss was reported by only 10% of these households. The average self-reported post-harvest loss was 24%. Rodents and other pests were most frequently reported to cause these losses. Adoption of improved storage methods was limited and most cereals were stored inside the house in bags. Random Forests (RF) was applied to gain insight into factors and conditions favouring post-harvest losses. Application of RF explained 31% of the variation in postharvest losses reported by farmers. Three major factors associated with post-harvest losses were the distance of the household dwelling to the nearest market, the distance of the household dwelling to the main road, and average annual rainfall. Losses increased the further households were located from a market or main road, and losses also tended to decrease with higher rainfall. The standardized and nationally representative survey data from Ethiopia used were a good starting point for modelling post-harvest losses but the finally available information appeared to be partial. Therefore, this paper calls for better data collection, which could help to better target interventions needed to reduce post-harvest losses.