Identification of the contaminating psychrotrophic bacteria in refrigerated bulked raw milk and the assessment of their deteriorating potential

This work aimed to characterize, identify, and determine the deteriorating potential of the contaminating psychrotrophic bacteria in refrigerated raw milk. Samples were submitted to serial dilutions and plated in specific culture media to form a bacterial culture collection. The isolates were characterized for their morphology and biochemical characteristics. The deteriorating potential of the isolates was determined according to the proteolytic, lipolytic and lecithinase activities at 4.0 ºC, 6.5 ºC, and 25.0 ºC. The results obtained for deterioration potential were assessed by the multivariate statistical method and by the principal components analysis (PCA). A total of 159 isolates were characterized, and of these, 46 strongly proteolytic Gram-negative isolates were selected for identification using the API 20 NE kit. The predominant bacteria were Gram-negative and oxidase and catalase positive, with a predominance of bacteria of the genus Pseudomonas. Using PCA, it was shown that the bacteria with the greatest deterioration potential were lecithinase producers, and that, in the autumn, proteolytic bacteria predominated at 4.0 ºC. Of the 46 isolates identified, more than 80% belonged to the species Pseudomonas fluorescens. Thus, attention should be given to the importance of implementing microbial contamination prevention measures in the bulking process, since, even under refrigeration, psychrotrophic bacteria multiply and produce enzymes that deteriorate lipids and proteins, with consequent quality losses of the milk and its derivatives, yield losses in the production of dairy products, and economic losses.

Along the Rivers and into the Plain: Early Crop Diversity in the Central and Western Balkans and Its Relationship with Environmental and Cultural Variables

Agriculture is a complex and dynamic socio-ecological system shaped by environmental, economic, and social factors. The crop resource pool is its key component and one that best reflects environmental limitations and socio-economic concerns of the farmers. This pertains in particular to small-scale subsistence production, as was practised by Neolithic farmers. We investigated if and how the environment and cultural complexes shaped the spectrum and diversity of crops cultivated by Neolithic farmers in the central-western Balkans and on the Hungarian Plain. We did so by exploring patterns in crop diversity between biogeographical regions and cultural complexes using multivariate statistical analyses. We also examined the spectrum of wild-gathered plant resources in the same way. We found that the number of species in Neolithic plant assemblages is correlated with sampling intensity (the number and volume of samples), but that this applies to all archaeological cultures. Late Neolithic communities of the central and western Balkans exploited a large pool of plant resources, whose spectrum was somewhat different between archaeological cultures. By comparison, the earliest Neolithic tradition in the region, the Starčevo-Körös-Criş phenomenon, seems to have used a comparatively narrower range of crops and wild plants, as did the Linearbandkeramik culture on the Hungarian Plain.

Mesoscale geomorphic change on barrier estuarine regime at the tropical coast of Chandipur, India: Evidence from assessment of grain-size distribution

It is crucial for policy makers and environmental managers to determine the future dynamics of coastal wetlands, especially the existence of their response, disruption, and recovery regimes. Reconstruction of meso-scale evolution in coastal ecosystems can help to adapt coastal resource management techniques to the natural scales of system activity, thereby encouraging true biodiversity. This research provides an overview of decadal (mesoscale) geomorphic transition by high-resolution grain size analysis of a sediment deposit from a barrier estuary regime on the Chandipur coast, India. Coastal marshland’s grain size distribution (GSD) has generally been analyzed using End Member Mixing Models (EMMA) and Probability Density Function (PDF) methods (e.g. log-normal, log skew-Laplace). Although these techniques do not consider the compositional nature of the records, which can undermine the outcomes of the interpretation of sedimentary deposits. The approach to reliable granulometric analysis of lithostratigraphic sequences aims at establishing direct links between fluid dynamics and subsequent shifts in the texture of sediments. In this study, GSD analysis of marsh sediment is represented by compositional data analysis (CoDa) and a multivariate statistical framework. Barrier estuary evolution, presented by time lapses of satellite maps coupled with grain size and carbon content of marsh sediment, primarily reflects the evolving hydrodynamics of the back barrier area. These findings will provide a statistically robust analysis of the depositional system in coastal marshland. Multiannual environmental variations in the back barrier configuration illustrate the importance of this applied approach with respect to bridging the basis of estuarine evolution and process information.

Synchronization-Free Multivariate Statistical Process Control for Online Monitoring of Batch Process Evolution

Synchronization of variable trajectories from batch process data is a delicate operation that can induce artifacts in the definition of multivariate statistical process control (MSPC) models for real-time monitoring of batch processes. The current paper introduces a new synchronization-free approach for online batch MSPC. This approach is based on the use of local MSPC models that cover a normal operating conditions (NOC) trajectory defined from principal component analysis (PCA) modeling of non-synchronized historical batches. The rationale behind is that, although non-synchronized NOC batches are used, an overall NOC trajectory with a consistent evolution pattern can be described, even if batch-to-batch natural delays and differences between process starting and end points exist. Afterwards, the local MSPC models are used to monitor the evolution of new batches and derive the related MSPC chart. During the real-time monitoring of a new batch, this strategy allows testing whether every new observation is following or not the NOC trajectory. For a NOC observation, an additional indication of the batch process progress is provided based on the identification of the local MSPC model that provides the lowest residuals. When an observation deviates from the NOC behavior, contribution plots based on the projection of the observation to the best local MSPC model identified in the last NOC observation are used to diagnose the variables related to the fault. This methodology is illustrated using two real examples of NIR-monitored batch processes: a fluidized bed drying process and a batch distillation of gasoline blends with ethanol.

Discovery of Kerivoula kachinensis and a validity of K. titania (Chiroptera: Vespertilionidae) in China

In April 2019, 15 (10♂, 5♀) Kerivoula bats were collected by harp traps from Xishuangbanna, Yunnan Province, China. External and craniodental examination, multivariate statistical analyses and molecular phylogenetic inference (CoI, Cytb and Rag2 gene markers) indicated they are Kerivoula kachinensis and Kerivoula titania, respectively. Former represents a new chiropteran record from China, while the latter is a valid occurrence of K. titania in this region because recent study indicate a misidentification of “K. titania” in Guangdong, Guangxi and Hainan, China. All specimens are presently preserved at Key Laboratory of Conservation and Application in Biodiversity of South China in Guangzhou University, Guangzhou, China. Nowadays, four woolly bats occur in China including, Kerivoula furva, K. kachinensis, Kerivoula picta and K. titania, whilst there is a risk of underestimation the actual species diversity in China region when comparing those of neighboring region such as Vietnam. Supports for field survey need to be continued in future.

Food Purchase Behavior during The First Wave of COVID-19: The Case of Hungary

Coronavirus disease (SARSCoV-2) appeared in 2019 was confirmed as pandemic by the WHO on 11 March 2020. Stay-at-home order had an impact on consumers’ food purchase habits, as people around the world were able to leave their homes solely in extremely severe or urgent cases. In our research, we delve into the impact of COVID-19 pandemic on consumers’ food purchase habits. The research involved 3000 consumers during the first wave of coronavirus. The sample represents the Hungarian population by gender and age. To achieve the research goals, we applied multivariate statistical tools. The findings suggest that the pandemic could not change consumer attitude significantly, but the order of factors influencing purchases changed. Consumer motivation factors were organized into four well-distinguished factors: Healthy, domestic, and environmentally friendly choice; Usual taste and quality; Reasonable price; Shelf life. Due to the lack of outstanding data during segmentation, we developed four segments by hierarchical cluster analysis: Health- and environment-conscious women; Price sensitive young people; Taste-oriented men; Quality-oriented intellectuals. The results confirm that food manufacturers and traders need to be prepared for further restrictions in the future.

The Effect of Organizational Climate and Job Satisfaction on the Formation of OCB in Marketing Staff of Pt Ajmi Pontianak Branch

This research was conducted in Pontianak, involving marketing employees at PT AJMI Pontianak Branch. Respondents of this research consisted of 35 men and 84 women with an age range between 24 s.d. 62 years old, with take home pay based on commission from their sales. This research data processing uses Multivariate Statistical Method, Structural Equation Modeling (SEM), WarpPLS6 Approach. Research findings state that organizational climate is a positive and significant builder for job satisfaction and OCB, job satisfaction is also a positive and significant shaper for OCB and job satisfaction is a significant mediation between organizational climate and OCB in marketing employees of PT AJMI Pontianak Branch.

Quality Assessment of Goldenrod, Milkweed and Multifloral Honeys Based on Botanical Origin, Antioxidant Capacity and Mineral Content

The goal of the study was to evaluate the pollen spectrum, antioxidant capacity and mineral content of four Hungarian honey types, using multivariate statistical analysis. The light colored honeys were represented by milkweed honey and a multifloral (MF) honey with dominant pollen frequency of linden (MF-Tilia); the darker ones were goldenrod honey and a multifloral honey with Lamiaceae pollen majority (MF-Lamiaceae). The pollen spectrum of the samples was established with melissopalynological analysis. The absorbance of the honeys positively correlated with the antioxidant capacity determined with three of the used methods (TRC, TEAC, DPPH), but not with ORAC. The latter method correlated negatively also with other antioxidant methods and with most of the mineral values. MF-Tilia had high ORAC value, K and Na content. The MF-Lamiaceae had the highest K, Mg, P, S, Cu and Zn content, the last five elements showing strict correlation with the TRC method. The darker goldenrod honey had higher SET values and total mineral content, than the milkweed honey. The above character-sets facilitate identification of each honey type and serve as indicators of variety. The antioxidant levels and mineral content of honeys allowed their clear separation by principal component analysis (PCA).

NMR-Based Metabolomic Analysis of Sera in Mouse Models of CVB3-Induced Viral Myocarditis and Dilated Cardiomyopathy

Viral myocarditis (VMC) is an inflammatory heart condition which can induce dilated cardiomyopathy (DCM). However, molecular mechanisms underlying the progression of VMC into DCM remain exclusive. Here, we established mouse models of VMC and DCM by infecting male BALB/c mice with Coxsackievirus B3 (CVB3), and performed NMR-based metabonomic analyses of mouse sera. The mouse models covered three pathological stages including: acute VMC (aVMC), chronic VMC (cVMC) and DCM. We recorded 1D 1H-NMR spectra on serum samples and conducted multivariate statistical analysis on the NMR data. We found that metabolic profiles of these three pathological stages were distinct from their normal controls (CON), and identified significant metabolites primarily responsible for the metabolic distinctions. We identified significantly disturbed metabolic pathways in the aVMC, cVMC and DCM stages relative to CON, including: taurine and hypotaurine metabolism; pyruvate metabolism; glycine, serine and threonine metabolism; glycerolipid metabolism. Additionally, we identified potential biomarkers for discriminating a VMC, cVMC and DCM from CON including: taurine, valine and acetate for aVMC; glycerol, valine and leucine for cVMC; citrate, glycine and isoleucine for DCM. This work lays the basis for mechanistically understanding the progression from acute VMC to DCM, and is beneficial to exploitation of potential biomarkers for prognosis and diagnosis of heart diseases.