Ensiling conditions strongly influence fermentation characteristics, yeast count, and aerobic stability. Numerous volatile organic compounds including esters are produced, which may negatively affect feed intake and animal performance and air quality. In addition to a farm survey, 3 laboratory experiments were carried out to study the effects of air (by delayed sealing or by air infiltration during anaerobic storage), temperature (20 and 35°C), and various types of additives [blends of either sodium benzoate and sodium propionate (SBSP) or of sodium benzoate and potassium sorbate (SBPS); buffered mixture of formic and propionic acids (FAPA); homofermentative inoculant (LAB)]. After additive treatment, chopped whole corn plants were packed into 1.5-L glass jars and stored for several months. For treatments with air infiltration, glass jars with holes in the lid and body were used. The farm survey in 2009 revealed large variation in lactate, acetate, ethanol, n-propanol, and 1,2-propanediol concentrations. Whereas ethyl esters were detected in all silages, the mean ethyl lactate concentrations were higher than those for ethyl acetate (474 vs. 38mg/kg of dry matter). In the ensiling experiments, few unequivocal effects of the tested factors on the analyzed parameters were observed due to many interactions. Delayed ensiling without additives decreased lactic acid production but, in one trial, increased acetic acid and had no effect on ethanol. The effect of delayed sealing on yeast counts and aerobic stability differed widely among experiments. Air infiltration during fermentation tested in one trial did not alter lactic acid production, but resulted in more acetic acid in delayed and more ethanol than in promptly sealed untreated silages. Greater ethanol production was associated with increased yeast numbers. Storage at high temperature resulted in lower lactic acid and n-propanol, and a trend toward reduced ethanol production was observed. The additive FAPA consistently caused increased ethanol and reduced n-propanol levels with no effect on yeast counts and aerobic stability. When the additives SBSP and SBPS decreased n-propanol and ethanol, reduced yeast counts were also found. Ethyl ester formation was strongly correlated with those of ethanol and to a lesser degree with those of the respective acid.

The probability of detecting treatment differences can often be increased by using geostatistical instead of classical statistical models. Geostatistical approaches require the selection of the best fitted model from a set of alternative models. This additional analysis effort could be reduced if the same model shows consistently the best fit for a given field or crop. To prove whether this reduction can be expected for designed on‐station trials, we analyzed five uniformity trials conducted on the same field. We studied whether different layouts of randomized complete block designs, the positions on the field, and the randomized plans influenced the model decision and analyzed the precision achieved. For this, the designs were shifted across the field, and 1000 randomized plans were projected onto each position. The model fit was evaluated using the corrected Akaike information criterion (AICC). The ranked AICC values were used for assessing model preference. In the means of all crops, designs, and models, the variation of the ranks depended on an individual decision for the combination of position and randomized plan by 62.6%. Therefore, the best fitted model was not predictable for a single experiment. As in the classical approach, the proper layout of a trial determines precision and unbiasedness of treatment differences. Randomization and blocking still should be the basic principles of experiment planning; however, their roles have partially changed. The detected bias of the Type I errors, both of the t‐test and F test, needs further investigation. Basic findings are also valid for on‐farm trials.

The highly infectious Tomato brown rugose fruit virus (ToBRFV) is a new viral threat to tomato production worldwide. In production, the very easy mechanical transmissibility combined with the high resistance in vitro is of great concern. We tested: (i) whether household cleaning products, commercial agricultural detergents, and an authorized plant protectant are suitable for cleaning contaminated clothing, and (ii) whether infectious viruses remain in the resulting cleaning water. The evaluation of the sanitation effect was performed using bioassays, by counting ToBRFV-associated necrotic local lesions on Nicotiana tabacum cv. Xanthi NN. For this purpose, leaves were mechanically inoculated with treated fabrics and cleaning solutions which would normally be discharged to the sewer system. The detergents Fadex H+ (FH) and Menno Hortisept Clean Plus, as well as the disinfectant Menno Florades (MF), led to an almost complete removal of ToBRFV from contaminated fabrics, corresponding to a reduction in local lesions by 99.94–99.96%. In contrast, common household cleaning products (Spee ActivGel (SAG), Vanish Oxi Action Gel (VO) did not effectively remove the pathogen from the fabric, where the reduction was 45.1% and 89.7%, respectively. In particular, cleaning solutions after the use of household cleaners were highly contaminated with ToBRFV. After a 16-h treatment with the disinfectant MF, infectious ToBRFV was no longer present in VO, FH, and MF cleaning solutions, as demonstrated by extensive bioassays.

Earthworm activity is observed at long‐term monitoring sites as an indicator of soil function to assess changes resulting from environmental and management conditions. In order to assess changes, characteristic values of earthworm populations under different site conditions have to be known. Therefore, a classification scheme for site‐specific earthworm populations was developed for soil in agricultural use, taking interactions between earthworm populations and soil properties into account. Characteristics of sites grouped by means of a cluster analysis after principal‐component analysis served as a basis for the derivation of the classification scheme. Soil variables found to characterize site differences with respect to earthworm populations were the texture of the topsoil, the texture of the subsoil, and the soil organic‐matter (SOM) content. The textural classes of the topsoil were divided into five groups comprising sandy soils (Ss), silty sand soils (Su), slightly loamy sand soils (Sl2), medium to strongly loamy sand soils (Sl3/Sl4), and loam and clay soils. Soil organic matter was divided into grades of equal size in a range from <1%, 1%–2% up to >6%. The variables “earthworm abundance” and “earthworm species” were selected to represent earthworm populations and were divided into six groups ranging from very low to extremely high. Defined groups of earthworm populations showed a clear structure in relation to soil textural groups and the content of SOM. From this distribution, a classification scheme was derived as basis for prognostic values of site‐specific earthworm populations, thus enabling the interpretation of changes over time. For some soil textural groups, selected variables appeared to enable the derivations of expected earthworm densities and species composition outside the range of the given database, but for some soil textural groups, broader databases will be needed to specify these derivations.