Stable isotope (δ18O and δ13C) sclerochronology of Callovian (Middle Jurassic) bivalves (Gryphaea (Bilobissa) dilobotes) and belemnites (Cylindroteuthis puzosiana) from the Peterborough Member of the Oxford Clay Formation (Cambridgeshire, England): Evidence of palaeoclimate, water depth and belemnite behaviour

Incremental δ18O and δ13C signals were obtained from three well-preserved specimens of Cylindroteuthis puzosiana and from three well-preserved specimens of Gryphaea (Bilobissa) dilobotes from the Peterborough Member of the Oxford Clay Formation (Cambridgeshire, England). Through-ontogeny (sclerochronological) δ18O data from G. (B.) dilobotes appear to faithfully record seasonal temperature variations in benthic Callovian waters of the study area, which range from c. 14 °C to c. 17 °C (arithmetic mean temperature c. 15 °C). Water depth is estimated to have been in the region of c. 50 m, based upon comparisons between these data, previously published non-incremental sea surface δ18O values, and a modern analogue situation. Productivity in Callovian waters was comparable with that in modern seas, based upon δ13C data from G. (B.)dilobotes, with 13C depletion occurring during warmer periods, possibly related to an interaction between plankton blooms and intra-annual variations in mixing across a thermocline. Incremental δ18O data from C.puzosiana provide temperature minima of c.11 °C for all specimens but with maxima varying between c.14 °C and c.16 °C for different individuals (arithmetic mean values c. 13 °C). Temperatures for late ontogeny, when the C. puzosiana individuals must have been living close to the study site and hence the analysed specimens of G. (B.) dilobotes, are closely comparable to those indicated by the latter. However, for significant portions of ontogeny C. puzosiana experienced temperatures between c. 2 °C and c. 3 °C cooler than the winter minimum as recorded by co-occurring G. (B.) dilobotes. Comparisons with modern seas suggest that descent to a depth of c. 1000 m would be necessary to explain such cool minimum temperatures. This can be discounted due to the lack of deep waters locally and due to estimates of the depth tolerance of belemnites. The most likely cause of cool δ18O signals from C. puzosiana is a cosmopolitan lifestyle including migration to more northerly latitudes. Mean δ13C values from C. puzosiana are comparable with those from G.(B.)dilobotes. However, the incrementally acquired data are highly variable and probably influenced by metabolic effects.The probable identification of migratory behaviour in C. puzosiana calls into question the reliability of some belemnite species as place-specific palaeoenvironmental archives and highlights the benefits of adopting a sclerochronological approach

Experimentos em riticulado quadrado com alguns tratamentos comuns adicionados em cada bloco: análise intrablocos.

Apresentou-se um metodo geral de analise intrablocos para o caso de um ensaio em reticulado quadrado aumentado pela adicao de alguns tratamentos comuns a todos os blocos. Os tratamentos do delineamento inicial foram designados de tratamentos regulares, e os adicionados aos blocos, de tratamentos comuns. Os parametros do delineamento inicial foram definidos como: k (numero de parcelas por bloco), v = k2 (numero de tratamentos regulares), b (numero de blocos), i (numero de repeticoes ortogonais), n (numero de vezes que as repeticoes ortogonais sao repetidas) e r= ni (numero de repeticoes dos tratamentos). A inclusao de c tratamentos comuns em cada bloco do experimento resultou em um delineamento aumentado, com os seguintes parametros: v' = v +c (numero total de tratamentos), b (numero de blocos), k' = k + c (numero de parcelas por bloco), r' (numero de repeticoes de cada tratamento e uu'(numero de blocos onde os tratamentos u e u' ocorrem juntos). O modelo matematico adotado foi o seguinte y uh = m + tu + bh + euh e a observacao do u-esimo tratamento no h-esimo bloco; m e a media geral; tu e o efeito do u-esimo tratamento (u= 1,2,....v'); bh e o efeito do h-esimo bloco (h = 1, 2, ...., b) e euh e o erro experimental associado a yuh onde euh (0, o2). Foram determinadas as expressoes para as varias somas de quadrados na analise de variancia, as medias de tratamentos ajustadas para blocos e a variancia da estimativa de um contraste entre duas medias de tratamentos

PIT telemetry as a method to study the habitat requirements of fish populations: application to native and stocked trout movements

Passive integrated transponder (PIT) technology was used to study the behaviour of fishes during the summer season in two headwater streams of northeastern Portugal. A total of 71 PIT tags (12 mm long x 2.1 mm diameter) were surgically implanted in 1+ stocked (39) and native (32) brown trout of two size classes (< 20.0 and ≥ 20.0 cm). Eight independent antennae, connected to a multi-point decoder (MPD reader) unit, were placed in different microhabitats, selected randomly every three days during the observation period (29 August to 9 September in Baceiro stream and 19 September to 4 October in Sabor stream). The results confirmed this method as a suitable labour efficient tool to assess the movement and habitat use of sympatric stocked and native trout populations. About 76.9% of stocked and 59.4% of native PIT tagged trouts were detected. Multivariate techniques (CCA, DFA and classification tree) showed a separation in habitat use between the two sympatric populations. Stocked trout mainly used the microhabitats located in the middle of the channel with higher depths and without cover. Furthermore, these fishes displayed a greater mobility and a diel activity pattern different to native trout populations

Ionoluminescence: A New Tool for Nuclear Microprobes in Geology

When an ion beam in the energy range of a few MeV/amu impacts on a mineral, visible light can often be observed. This light, induced by energetic ions, is termed ionoluminescence (IL). The intensity and wavelength of the ionoluminescent light provide information concerning the nature of luminescence centers, such as trace substituents and structural defects, found in the mineral. This makes IL a useful complement to other methods of ion beam analysis (IBA), such as particle induced X-ray emission (PIXE) and Rutherford backscattering (RBS), in characterizing geological samples. In the present study, a proton or alpha particle beam was used for the IL excitation and IBA with a nuclear microprobe. The results obtained with IL were compared with those of cathodoluminescence (CL) and photoluminescence (PL)

Impact of volatile phenols and their precursors on wine quality and control measures of Brettanomyces/Dekkera yeasts

Volatile phenols are aromatic compounds and one of the key molecules responsible for olfactory defects in wine. The yeast genus Brettanomyces is the only major microorganism that has the ability to covert hydroxycinnamic acids into important levels of these compounds, especially 4-ethylphenol and 4-ethylguaiacol, in red wine. When 4-ethylphenols reach concentrations greater than the sensory threshold, all wine’s organoleptic characteristics might be influenced or damaged. The aim of this literature review is to provide a better understanding of the physicochemical, biochemical, and metabolic factors that are related to the levels of p-coumaric acid and volatile phenols in wine. Then, this work summarizes the different methods used for controlling the presence of Brettanomyces in wine and the production of ethylphenols

Multi-target prediction of wheat flour quality parameters with near infrared spectroscopy

Near Infrared (NIR) spectroscopy is an analytical technology widely used for the non-destructive characterisation of organic samples, considering both qualitative and quantitative attributes. In the present study, the combination of Multi-target (MT) prediction approaches and Machine Learning algorithms has been evaluated as an effective strategy to improve prediction performances of NIR data from wheat flour samples. Three different Multi-target approaches have been tested: Multi-target Regressor Stacking (MTRS), Ensemble of Regressor Chains (ERC) and Deep Structure for Tracking Asynchronous Regressor Stack (DSTARS). Each one of these techniques has been tested with different regression methods: Support Vector Machine (SVM), Random Forest (RF) and Linear Regression (LR), on a dataset composed of NIR spectra of bread wheat flours for the prediction of quality-related parameters. By combining all MT techniques and predictors, we obtained an improvement up to 7% in predictive performance, compared with the corresponding Single-target (ST) approaches. The results support the potential advantage of MT techniques over ST techniques for analysing NIR spectra

Hyperspectral Imaging and Deep Learning for Quality and Safety Inspection of Fruits and Vegetables: A Review

Quality inspection of fruits and vegetables linked to food safety monitoring and quality control. Traditional chemical analysis and physical measurement techniques are reliable, they are also time-consuming, costly, and susceptible to environmental and sample changes. Hyperspectral imaging technology combined with deep learning methods can effectively overcome these problems. Compared with human evaluation, automated inspection improves inspection efficiency, reduces subjective error, and promotes the intelligent and precise fruit and vegetable quality inspection. This paper reviews reports on the application of hyperspectral imaging technology combined to deep learning methods in various aspects of fruits and vegetables quality assessment. In addition, the latest applications of these technologies in the fields of fruit and vegetable safety, internal quality, and external quality inspection are reviewed, and the challenges and future development directions of hyperspectral imaging technology combined with deep learning in this field are prospected. Hyperspectral imaging combined with deep learning has shown significant advantages in fruit and vegetable quality inspection, especially in improving inspection accuracy and efficiency. Future research should focus on reducing costs, optimizing equipment, personalizing feature extraction, and model generalizability. In addition, the development of lightweight models and the balance of accuracy, the enhancement of the database and the importance of quantitative research should also be brought to attention. These efforts will promote the wide application of hyperspectral imaging technology in fruit and vegetable inspection, improve its practicability in the actual production environment, and bring important progress for food safety and quality management