A Hungarian survey of Tokaj-Mád vineyards was conducted. Shotgun metabarcoding was applied to decipher the microbial-terroir. The results of 60 soil samples showed that there were three dominant fungal phyla, Ascomycota 66.36% ± 15.26%, Basidiomycota 18.78% ± 14.90%, Mucoromycota 11.89% ± 8.99%, representing 97% of operational taxonomic units (OTUs). Mutual interactions between microbiota diversity and soil physicochemical parameters were revealed. Principal component analysis showed descriptive clustering patterns of microbial taxonomy and resistance gene profiles in the case of the four historic vineyards (Szent Tamás, Király, Betsek, Nyúlászó). Linear discriminant analysis effect size was performed, revealing pronounced shifts in community taxonomy based on soil physicochemical properties. Twelve clades exhibited the most significant shifts (LDA > 4.0), including the phyla Verrucomicrobia, Bacteroidetes, Chloroflexi, and Rokubacteria, the classes Acidobacteria, Deltaproteobacteria, Gemmatimonadetes, and Betaproteobacteria, the order Sphingomonadales, Hypomicrobiales, as well as the family Sphingomonadaceae and the genus Sphingomonas. Three out of the four historic vineyards exhibited the highest occurrences of the bacterial genus Bradyrhizobium, known for its positive influence on plant development and physiology through the secretion of steroid phytohormones. During ripening, the taxonomical composition of the soil fungal microbiota clustered into distinct groups depending on altitude, differences that were not reflected in bacteriomes. Network analyses were performed to unravel changes in fungal interactiomes when comparing postveraison and preharvest samples. In addition to the arbuscular mycorrhiza Glomeraceae, the families Mycosphaerellacae and Rhyzopodaceae and the class Agaricomycetes were found to have important roles in maintaining soil microbial community resilience. Functional metagenomics showed that the soil Na content stimulated several of the microbiota-related agrobiogeochemical cycles, such as nitrogen and sulphur metabolism; steroid, bisphenol, toluene, dioxin and atrazine degradation and the synthesis of folate.

AbstractA Hungarian survey of Tokaj-Mád vineyards was conducted. Shot-gun metabarcoding was applied to decipher the microbial-terroir. The results of 60 soil samples showed that there were three dominant fungal phyla,Ascomycota66.36% ± 15.26,Basidiomycota18.78% ± 14.90,Mucoromycota11.89% ± 8.99, representing 97% operational taxonomic units (OTUs). Mutual interactions between microbiota diversity and soil physicochemical parameters were revealed. Principal component analysis showed descriptive clustering patterns of microbial taxonomy and resistance gene profiles in the case of the four historic vineyards (Szent Tamás, Király, Betsek, Nyúlászó). Soil seed bacteria changed markedly due to ripening. Network analyses were performed to unravel changes in fungal interactions when comparing postveraison and preharvest samples. In addition to the arbuscular mycorrhizaGlomeraceae, the familiesMycosphaerellacaeandRhyzopodaceaeand the classAgaricomyceteswere found to have important roles in maintaining soil microbial community resilience. By investigating the possible connections between the soil fungal community and the associated must samples, it was found that the species of theDiversisporagenus and the familyCordycipitaceaewere shown to be good soil indicator microorganisms of a high must polyphenol content. Functional metagenomics showed that the soil Na content stimulated several of the microbiota-related agrobiogeochemical cycles, such as nitrogen and sulphur metabolism; steroid, bisphenol, toluene, dioxin and atrazine degradation and the synthesis of folate.

The study presents a systematic review of published scientific articles investigating the effects of interventions aiming at aflatoxin reduction at the feed production and animal feeding phases of the milk value chain in order to identify the recent scientific trends and summarize the main findings available in the literature. The review strategy was designed based on the guidance of the systematic review and knowledge synthesis methodology that is applicable in the field of food safety. The Web of Science and EBSCOhost online databases were searched with predefined algorithms. After title and abstract relevance screening and relevance confirmation with full-text screening, 67 studies remained for data extraction, which were included in the review. The most important identified groups of interventions based on their mode of action and place in the technological process are as follows: low-moisture production using preservatives, acidity regulators, adsorbents and various microbiological additives. The results of the listed publications are summarized and compared for all the identified intervention groups. The paper aimed to help feed producers, farmers and relevant stakeholders to get an overview of the most suitable aflatoxin mitigation options, which is extremely important in the near future as climate change will likely be accompanied by elevated mycotoxin levels.

Aflatoxins (AFs) are harmful secondary metabolites produced by various moulds, among which Aspergillus flavus is the major AF-producer fungus. These mycotoxins have carcinogenic or acute toxigenic effects on both humans and food producing animals and, therefore, the health risks and also the potential economic damages mounted by them have led to legal restrictions, and several countries have set maximum allowable limits for AF contaminations in food and feed. While colonization of food and feed and AF production by A. flavus are highly supported by the climatic conditions in tropical and subtropical geographic regions, countries in the temperate climate zones are also increasingly exposed to AF-derived health risks due to climate change. In the present study, we have reviewed the available mathematical models as risk assessment tools to predict the possibility of A. flavus infection and levels of AF contaminations in maize in a changing climatic environment. After highlighting the benefits and possible future improvements of these models, we summarize the current agricultural practices used to prevent or, at least, mitigate the deleterious consequences of AF contaminations

Three super-sweet corn hybrids (Zea mays L. convar. saccharata) with different ripening characteristics were grown in three water supplies (regularly irrigated, deficit-irrigated, and unirrigated) to examine the spectral reflectance at leaf and canopy levels, leaf area index (LAI) during the stage of development and their relationship with the yield and nutritional quality. Under unirrigated conditions, the plant’s height, diameter, and weight of ears per plants, as well as total carotenoid content of kernels, decreased, SPAD values of leaves, normalized vegetation differential index (NDVI) and LAI were low. The difference in SPAD and LAI was higher between the hybrids during the silking than the tasseling period under water deficiency. Under unirrigated dry conditions, no correlation was found between SPAD, NDVI, and yield. Using deficit irrigation, SPAD measured during tasseling correlated closely with the individual husked ear and the final yields as well as the sugar and carotene contents of kernels. Under this condition, NDVI did not correlate with the yield, but LAI was correlated with the yield and its carotene content. Under deficit irrigated conditions, the 46 to 49 range of SPAD measured during tasseling predicted 23.5 to 26.7 t ha−1 depending on the hybrid, but this range predicted a yield lower by 6.4 to 10.1% during silking.

Abstract The knowledge of the evapotranspiration of natural ecosystems and plant populations is of fundamental importance in several branches of science, research and practical uses. Nevertheless, the harmonisation of the large number of methods and user needs often causes problems. The objective of the analyses was to explore the output range and sensitivity of models of different physical approaches under local conditions. We performed descriptive statistical and sensitivity analysis of 10 commonly used estimation models - one of them with two variants. Correlation between modelled and measured evapotranspiration data series was assessed. The magnitude of the model outputs, their variability and responses to the changes of selected atmospheric parameters were evaluated. Priestley-Taylor, Penman-Monteith-FAO-56, Shuttleworth-Wallace (parameterized with alternative radiation balance), Szász and Makkink proved to be the most sensitive methods. As regards the systematic error, Makkink and Shuttleworth-Wallace showed the best agreement with pan evaporation, while Shuttleworth-Wallace, Blaney-Criddle and Makkink models were found to be the closest to the Penman-Monteith-FAO-56 method as a reference value.

The fact and volume of global warming in Hungary is proven by accurate meteorological measurements from the previous century. In agriculture and cultivation one should count with frequent changes of weather conditions due to climate change. Although the tendency of 0.6 degrees C raise in the annual average of temperature in the past one hundred years does not risk our cultivation so far, the high fluctuation of temperature, the winters, and the shorter transition seasons cause real problems. Similar potential threads are the decreasing trend of precipitation volume, the longer drought periods, and more frequent sudden heavy rainfalls. To provide a safe and well scheduled production, it is essential to maintain a decision support monitoring system based on up-to-date and accurate weather data. It is extraordinary needed in site-specific precision farming systems, where the aim is to produce goods of the highest quality. Nowadays, remote sensing is one of the basic instruments of continuous monitoring. Processing the collected data provides information for many fields of cultivation from technological parts to decision support processes.The survey the vegetation state of plants, a measure can be calculated from remote sensing data, the so-called normalized vegetation index (NDVI). The aim of our research is to prove that satellite records can be a useful tool for maize seed production in two aspects: first, to find correlation between the NDVI and the weather conditions of a given year, and second, to find the optimal time interval for NDVI based crop estimation method.