1,720,996 research outputs found
Use of Probes and Sensors in Agriculture—Current Trends and Future Prospects on Intelligent Monitoring of Soil Moisture and Nutrients
Full text linkSoil monitoring is essential for promoting sustainability in agriculture, as it helps prevent degradation and optimize the use of natural resources. The introduction of innovative technologies, such as low-cost sensors and intelligent systems, enables the acquisition of real-time data on soil health, increasing productivity and product quality while reducing waste and environmental impact. This study examines various agricultural monitoring technologies, focusing on soil moisture sensors and nutrient detection, along with examples of IoT-based systems. The main characteristics of these technologies are analyzed, providing an overview of their effectiveness and the key differences among various tools for optimizing agricultural management. The aim of the review is to support an informed choice of the most appropriate sensors and technologies, thus contributing to the promotion of sustainable agricultural practices
A comparison among innovative plants for high quality extra-virgin olive oil production
No full textThe cleaning operation of extra-virgin olive oil, subsequent to its extraction, is generally performed by means of a vertical disc stack centrifuge separator causing qualitative damage due to increased oxidative alterations. However, previous works have demonstrated the great opportunity that settling represents in order to improve the EVOO quality performing the separation operation with minimal qualitative damage
Models for the rapid assessment of water and oil content in olive pomace by near-infrared spectrometry
No full textBACKGROUND
Measurement of water and oil content in olive pomace is crucial in order to control the olive oil extraction process; the use of near‐infrared spectra could allow the measurement of the oil and water content in the olive pomace.
RESULTS
Partial least squares for pomace oil content on dry basis reached an error of 2.5% (+/− 0.5), principal component regression for pomace oil content on wet basis reached an error of 3.7% (+/− 0.5), both suitable for quantitative analysis. Principal component regression for pomace water content reached an error of 6.0% (+/− 2.3), suitable for process control. The relationship between ‘ratio of standard deviation of calibration data to standard error of prediction data’ and ‘range of confident prediction error percent’ was investigated resulting hyperbolic through a constant depending on the product under analysis: for the olive pomace this constant is equal to 45.60 (+/− 1.78).
CONCLUSION
As the measure of the content of water and oil still contained in pomace must be considered of strategic importance to control the olive oil extraction process, the NIR analysis has confirmed the possibility of determining the oil and water content in the olive pomace. A new algorithm has been used, jointly with standard statistical algorithms, in order to identify and remove from the models the less useful wavelengths improving the overall prediction performance. A new parameter (the ‘range of confident prediction error percent’) has been proposed to estimate the model prediction error in an objective way
The microbiota of high-moisture mozzarella cheese produced with different acidification methods
No full textThe microbiota of high-moisture Mozzarella cheese made from cow's milk and produced with different acidification methods was evaluated at the end of refrigerated storage by pyrosequencing of the 16S rRNA gene. The cheeses were clearly separated on the basis of the acidification methods. Cheeses produced with the addition of starters were dominated by Streptococcus thermophilus, but a variety of lactic acid bacteria and spoilage microorganisms appeared at low levels (0.01-1%). Cheeses produced by direct addition of citric acid were dominated by a diverse microbiota, including both lactic acid bacteria and psychrotrophic γ-proteobacteria. For five brands the acidification system was not declared on the label: the microbiota was dominated by thermophilic lactic acid bacteria (S. thermophilus, Lactobacillus delbrueckii, Lactobacillus helveticus) but a variety of other subdominant lactic acid bacteria, psychrotrophs and Enterobacteriaceae were present, with a diversity comparable or higher to cheeses produced by direct acid addition. This led to the conclusion that undefined starters were used for acidification. Both ordination methods and network analysis were used for the representation of beta-diversity: matrix cluster analysis, principal coordinate analysis and OTU networks uncovered different aspects of the microbial community structure. For three cheese brands both biological replicates (cheeses from different lots) and technical replicates (replicate cheeses from the same lot) were analyzed. Repeatability was acceptable for OTUs appearing at frequencies >1%, but was low otherwise. A linear mixed model showed that the starter system was responsible for most differences related to dairies, while difference due to psychrotrophic contaminants was more related to lot-to-lot variability
Use of wavelength interaction terms to improve near infrared spectroscopy models of donkey’s milk properties
No full textRanchers are continuously searching for suitable tools to rapidly and inexpensively assess the characteristics of donkey milk and because spectroscopic models are useful to assess the composition of many foods, an attempt to further improve the prediction performance of donkey milk protein, lactose and dry-matter content has been made using three widely used spectroscopic models by adding some interaction terms, namely product, ratio, sum and difference of absorbances for each couple of wavelengths. Principal component regression using product terms showed an improvement in prediction error achieving 1.8%, 1.7% and 0.9% for protein, lactose and dry-matter content respectively. Furthermore, the added ratio terms showed a very great improvement in the predictive overall performance achieving 0.3%, 0.4% and 0.2%. A coefficient has been found relating the widely used RPD, a standard index of prediction performance, to the new proposed “range of confident prediction error percent” being a more understandable parameter to assess the goodness of the prediction model
Evolution of microbial counts and chemical and physico-chemical parameters in high-moisture Mozzarella cheese during refrigerated storage
No full textThe microbiological quality, pH, colour, proteolysis and head space composition (using an electronic
nose) of several commercial brands of high-moisture Mozzarella cheese produced in Italy were evaluated
at the beginning and at the end (5 days) of refrigerated storage in order to evaluate the effect of the
acidification system (direct acid addition or use of starter cultures) and storage on the quality of the
cheese. A high variability was found for most parameters. At the end of storage all parameters were
affected by the mode of acidification and cheese produced by direct acid addition had a significantly
lower microbiological quality; counts of psychrotrophs exceeded 107 cfu/g for most samples and microbial
counts showed a significant correlation with the residual shelf life. Multivariate analysis
confirmed that samples at the beginning and at the end of storage were clearly separated but no
grouping based on the mode of acidification was found. The electronic nose was only partially successful
(80% correct classification) in classifying the cheeses on the basis of storage time or of microbial counts.
This is likely to be due to the variety of brands used in the analysis and to differences in the starter
systems or acidification mode used
Microbial community dynamics in thermophilic undefined milk starter cultures
No full textModel undefined thermophilic starter cultures were produced from raw milk of nine pasta-filata cheesemaking plants using a selective procedure based on pasteurization and incubation at high temperature with the objective of studying the microbial community dynamics and the variability in performances under repeated (7-13) reproduction cycles with backslopping. The traditional culture-dependent approach, based on random isolation and molecular characterization of isolates was coupled to the determination of pH and the evaluation of the ability to produce acid and fermentation metabolites. Moreover, a culture-independent approach based on amplicon-targeted next-generation sequencing was employed. The microbial diversity was evaluated by 16S rRNA gene sequencing (V1-V3 regions), while the microdiversity of Streptococcus thermophilus populations was explored by using novel approach based on sequencing of partial amplicons of the phosphoserine phosphatase gene (serB). In addition, the occurrence of bacteriophages was evaluated by qPCR and by multiplex PCR. Although it was relatively easy to select for a community dominated by thermophilic lactic acid bacteria (LAB) within a single reproduction cycle, final pH, LAB populations and acid production activity fluctuated over reproduction cycles. Both culture-dependent and -independent methods showed that the cultures were dominated by either S. thermophilus or Lactobacillus delbrueckii subsp. lactis or by both species. Nevertheless, subdominant mesophilic species, including lactococci and spoilage organisms, persisted at low levels. A limited number of serB sequence types (ST) were present in S. thermophilus populations. L. delbrueckii and Lactococcus lactis bacteriophages were below the detection limit of the method used and high titres of cos type S. thermophilus bacteriophages were detected in only two cases. In one case a high titre of bacteriophages was concurrent with a S. thermophilus biotype shift in the culture. This study largely confirms previous data on the composition of undefined thermophilic starters used for the production of traditional cheeses in Italy but it is the first one to systematically address the dynamics of the cultures under a repeated reproduction regime with backslopping
Sensory properties of mozzarella cheese as affected by starter cultures and preservation liquid
No full textIndustrial manufacturing of pasta filata cheeses with commercial starter cultures, despite a qualitative standardisation, may cause flavour flattening. In order to improve the sensory profile of mozzarella cheese, we used two starters: ST051 (commercial) vs CL13A (natural milk culture) and two preservation liquids: TL (0.4% NaCl brine) vs IL (0.4% NaCl, 0.67% CaCl2, 0.51% lactose, 1% Lact. lactis + Leuc. mesenteroides). Sensory analyses were performed on four products (two starters x two liquids) by a 10- member panel (7 females and 3 males) in triplicate, whereas 82 consumers evaluated product acceptability. ST051 products had higher brightness, colour uniformity, eye number (P<0.001) and buttermilk release (P<0.05). CL13A cheeses showed higher milk flavour, and higher tenderness (P<0.05) and grainy (P<0.001) mouth feel intensities, whereas sourness (P<0.01), bitterness (P<0.05) flavours and mouth feel of residual (P<0.01) were lower. IL products had a lower eye number (P<0.001), buttermilk release (P<0.05) in terms of aspect, lower fruity and bitterness flavours (P<0.001), increased butter flavour (P<0.05), and increased shear strength (P<0.01), moisture (P<0.05) and grainy (P<0.001) mouth feel. Consumers expressed higher overall and taste/flavour liking for CL13A (P<0.01), whereas IL products were preferred in terms of taste/flavour liking (P<0.05). The PLS regression of 82 judges on 23 sensory variables (38% and 33% of Y variance explained by the first and second component, respectively) allowed to cluster four groups representing 5, 28, 37 and 21% of the consumers, respectively (Fig. 1). Group I preferred ST051 cheese preserved in IL liquid, with high surface uniformity, shear strength and butter flavour. Group II preferred both CL13A products with high milk and sweetness taste/flavour and grainy and tenderness textural attributes. Group III did not express a preference for a particular product, albeit showing a preference for attributes such as fruity flavour and colour intensity, while Cluster IV favoured ST051TL cheeses, characterized by brightness, eye number, and uniformity, in terms of aspect, bitterness, sourness and yogurt taste/flavour, and residual and oily mouth feel. The identification and selection of suitable cheese making technologies, involving the use of adjunct cultures or flavouring preservation liquid may be useful to the industry for product differentiation
Recovery of agricultural and food waste for compost production and agricultural reuse
No full textAgricultural and food waste from farms and agro-food industries could be reused in order to improve food production systems. In fact, organic waste produced by the agricultural sector is rich in nutrients that can be recovered and used as fertilizers. Among the various organic wastes for nutrient recovery, the primary interest is towards livestock effluents both for the abundance of annual production and for the physical and chemical characteristics that make them suitable for the agricultural reuse. The process currently used for the treatment of organic waste is the AD process (anaerobic digestion), which converts organic waste into biogas (source of alternative energy) and digestate; biogas can be used as a while the digestate (soil fertilizer after composting). The objective of this work was to analyse three different livestock manure mixtures for biogas production by means of a laboratory-scale demonstration prototype of a plant for the anaerobic digestion of agro-food biomass, as well as to reuse the residual by-product of anaerobic digestion (AD effluent) for the preparation of compost on a laboratory-scale
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