The use of a portable X-ray fluorescence spectrometer for measuring nickel in plants: sample preparation and validation.

X-ray fluorescence is a fast, cost-effective, and eco-friendly method for elemental analyses. Portable X-ray fluorescence spectrometers (pXRF) have proven instrumental in detecting metals across diverse matrices, including plants. However, sample preparation and measurement procedures need to be standardized for each instrument. This study examined sample preparation methods and predictive capabilities for nickel (Ni) concentrations in various plants using pXRF, employing empirical calibration based on inductively coupled plasma optical emission spectroscopy (ICP-OES) Ni data. The evaluation involved 300 plant samples of 14 species with variable of Ni accumulation. Various dwell times (30, 60, 90, 120, 300 s) and sample masses (0.5, 1.0, 1.5, 2.0 g) were tested. Calibration models were developed through empirical and correction factor approaches. The results showed that the use of 1.0 g of sample (0.14 g cm-2) and a dwell time of 60 s for the study conditions were appropriate for detection by pXRF. Ni concentrations determined by ICP-OES were highly correlated (R2 = 0.94) with those measured by the pXRF instrument. Therefore, pXRF can provide reliable detection of Ni in plant samples, avoiding the digestion of samples and reducing the decision-making time in environmental management.

The Magnitude and Impact of Food Allergens and the Potential of AI-Based Non-Destructive Testing Methods in Their Detection and Quantification.

Reaction to food allergens is on the increase and so is the attending cost on consumers, the food industry, and society at large. According to FDA, the "big-eight" allergens found in foods include wheat (gluten), peanuts, egg, shellfish, milk, tree nuts, fish, and soybeans. Sesame was added to the list in 2023, making the target allergen list nine instead of eight. These allergenic foods are major ingredients in many food products that can cause severe reactions in those allergic to them if found at a dose that can elicit a reaction. Defining the level of contamination that can elicit sensitivity is a work in progress. The first step in preventing an allergic reaction is reliable detection, then an effective quantification method. These are critical steps in keeping contaminated foods out of the supply chain of foods with allergen-free labels. The conventional methods of chemical assay, DNA-PCR, and enzyme protocols like enzyme-linked immunosorbent assay are effective in allergen detection but slow in providing a response. Most of these methods are incapable of quantifying the level of allergen contamination. There are emerging non-destructive methods that combine the power of sensors and machine learning to provide reliable detection and quantification. This review paper highlights some of the critical information on the types of prevalent food allergens, the mechanism of an allergic reaction in humans, the measure of allergenic sensitivity and eliciting doses, and the conventional and emerging AI-based methods of detection and quantification-the merits and downsides of each type.

Identification of spectral ranges that contribute to phytoplasma detection in apple trees - A step towards an on-site method.

'Candidatus Phytoplasma mali' is the bacterial agent associated with Apple Proliferation, a disease that causes high economic losses in affected commercial apple growing regions. The identification of the disease is carried out by visual inspection performed by skilled professionals in the orchards. To confirm an infection, costly molecular laboratory methods must be applied. Furthermore, both methods are very time-consuming. Here, we analysed the potential of a non-destructive method using in-field measurements to differentiate infected from non-infected apple trees (Malus domestica) based on spectral signatures of fresh leaves. By using multivariate statistics, we were able to distinguish infected from non-infected trees and identified the wavelengths relevant for the differentiation. Factors affecting the differentiation performance were the sampling date and bacterial colonization behaviour.

A new non-destructive method for the estimation of annual height increment in standing trees.

Measurement of tree growth is needed in many scientific and production sectors, especially in forestry for wood and biomass production. The assessment of annual height increment in standing living trees, under ambient field conditions, is challenging or even impossible. This study develops a new simple non-destructive method for the estimation of annual height increment in standing trees, based on sampling two increment cores for each targeted tree.,. Τhe method combines the tree annual ring-analysis and trigonometry. The extracted data by the method application can be widely used in many forest disciplines, such as forest ecology, silviculture, and forest management.•Annual height increment in standing trees is a valuable parameter needed in biology, ecology, and forestry.•Measurement of annual height increment in standing trees is a very difficult tusk.•This study develops a new non-destructive and simple method for the estimation of annual height increment in standing trees.

A Study on the Application of Machine and Deep Learning Using the Impact Response Test to Detect Defects on the Piston Rod and Steering Rack of Automobiles.

The main parts of automobiles are the piston rod of the shock absorber and the steering rack of the steering gear, and their quality control is critical in the product process. In the process line, these products are normally inspected through visual inspection, sampling, and simple tensile tests; however, if there is a problem or abnormality, it is difficult to identify the type and location of the defect. Usually, these defects are likely to cause surface cracks during processing, which in turn accelerate the deterioration of the shock absorber and steering, causing serious problems in automobiles. As a result, the purpose of this study was to present, among non-destructive methods, a shock response test method and an analysis method that can efficiently and accurately determine the defects of the piston rod and steering rack. A test method and excitation frequency range that can measure major changes according to the location and degree of defects were proposed. A defect discrimination model was constructed using machine and deep learning through feature derivation in the time and frequency domains for the collected data. The analysis revealed that it was possible to effectively distinguish the characteristics according to the location as well as the presence or absence of defects in the frequency domain rather than the time domain. The results indicate that it will be possible to quickly and accurately check the presence or absence of defects in the shock absorber and steering in the automobile manufacturing process line in the future. It is expected that this will play an important role as a key factor in building a smart factory.

The comparison of Canopeo and samplepoint for measurement of green canopy cover for forage crops in India.

Canopy covers can be measured using destructive (visual) and non-destructive methods (spectral indices, photogrammetry, visual assessment, and quantum sensor). The precision of crop cover estimation, however, is dependent on the selection of appropriate methods. Studies were conducted at the Indian Grassland and Fodder Research Institute, Jhansi to compare the forage crops canopy cover estimated using photogrammetry software (Canopeo and SamplePoint) and visual assessments. Assessments were performed in three summer crops (corn, cowpea, and sorghum), two winter crops (Egyptian clover, and oats), and bare ground condition. For each plot, three nadir images (directly above the canopy) were captured using digital cameras from a height of 1.5 m above the soil surface between 10 AM to 2 PM on bright sunny days. The results indicated that the relationships between visual assessment and Canopeo (regression coefficient, (R2 = 0.96), visual assessment and SamplePoint (0.96), and Canopeo and SamplePoint (0.98) were linear when data were pooled across all the crops. SamplePoint and Canopeo is further, appropriate for cowpea (Pearson coefficient (R = 0.99 and 0.94), oats (0.92 and 0.97), and sorghum (0.46 and 0.51), respectively. SamplePoint and Canopeo are not suitable for berseem (-0.15) and corn (-0.61), respectively, due to dead residues after the first harvest in berseem and taller corn might have influenced the image quality. Therefore, the stage of the crop, the height of the crop, and dead residues around the plants can greatly influence the estimation of crop cover. In conclusion, the results indicated that this photogrammetry software can be used for non-destructive crop canopy measurement with the above-mentioned precautions in the forage crops tested. •Forage canopy cover is estimated generally by visual scoring, and the outcome varies widely from person to person.•Photogrammetry methods (Canopeo and SamplePoint) were positiviely correlated with visual scoring for cowpea, oats, and sorghum.•However, Canopeo and SamplePoint may not suitable for taller crops like corn and ratoon crops like berseem.

Key Factors for Implementing Magnetic NDT Method on Thin UHPFRC Bridge Elements.

This paper provides an overview of the use of the magnetic NDT method for estimating the fibre content, and fibre orientation and efficiency factors in thin UHPFRC elements/layers, along any two orthogonal directions. These parameters are of utmost importance for predicting the post-cracking tensile strength in the directions of interest. After establishing meaningful correlations at the lab-specimen scale, this NDT method can be effectively implemented into quality control protocols at the industrial production scale. The current study critically addresses the influence of key factors associated with using this NDT method in practice and provides recommendations for its efficient implementation.

Non-Destructive Detection of Pentachlorophenol Residues in Historical Wooden Objects.

Wood is a natural polymeric material that is an important constituent of many heritage collections. Because of its susceptibility to biodegradation, it is often chemically treated with substances that can be harmful to human health. One of the most widely used wood preservatives was pentachlorophenol (PCP), which is still present in museum objects today, although its use has been restricted for about forty years. The development of non-destructive methods for its determination, suitable for the analysis of valuable objects, is therefore of great importance. In this work, two non-destructive solid-phase microextraction (SPME) methods were developed and optimized, using either headspace or contact mode. They were compared with a destructive solvent extraction method and found to be suitable for quantification in the range of 7.5 to 75 mg PCP/kg wood at room temperature. The developed semi-quantitative methods were applied in the wooden furniture depot of National Museum of Slovenia. PCP was detected inside two furniture objects using headspace mode. The pesticide lindane was also detected in one object. The indoor air of the depot with furniture was also sampled with HS SPME, and traces of PCP were found. According to the results, SPME methods are suitable for the detection of PCP residues in museum objects and in the environment.

Monitoring fatigue damage in different CAD/CAM materials: A new approach with optical coherence tomography.

PURPOSE: To investigate fatigue damage over time, monolithic posterior computer-aided-designed/computer-aided-manufactured (CAD/CAM) crowns were artificially aged in a mouth-motion-simulator, and damage was monitored with optical coherence tomography (OCT). METHODS: Forty-eight crowns were milled of six different CAD/CAM-materials (n=8), including 3Y-TZP (Lava Plus,'3Y'), 4Y-PSZ (Pritidentamultidisc,'4Y'), 5Y-PSZ (Prettauanterior,'5Y'), zirconia-reinforced lithium silicate (CeltraDuo,'ZLS'), hybrid ceramic (Vita Enamic,'VE'),and resin composite (BrilliantCrios,'COM'), and were adhesively luted on CAD/CAM-milled human molars. Specimens were artificially aged in a mouth-motion-simulator (50-500N, 2Hz, 37°C) for a period of 1 million cycles. Before loading and every 250,000 cycles, the specimens were investigated with spectral domain (SD)-OCT (RS-3000). The maximum vertical and horizontal damage were measured with imaging-processing-software (ImageJ). After testing, the specimens were sliced and analysed via light microscope (Zeiss) to compare the new OCT method with the established light microscope method. Data were subjected to ANCOVA and 2x4-ANOVA. RESULTS: No failure occurred during mouth-motion-simulation. However, all specimens (except for 3Y and 4Y) showed fatigue damage. There was a significant difference in the maximum damage between the CAD/CAM-materials (p<.05). ZLS exhibited the highest damage, followed by VE, COM and 5Y. While damage associated with 5Y was initially noticed after 750,000 cycles, all other materials already showed crack formation after 250,000 cycles. Furthermore, a linear increase in damage over time was noticed in all materials. Due to the shallow light penetration of OCT, damage in the outer area could only be visualized with light microscope. CONCLUSIONS: OCT is feasible for monitoring fatigue damage over time within different CAD/CAM-materials, particularly for subsurface damages.

Space-resolved determination of the mineral nutrient content in tree-rings by X-ray fluorescence.

X-ray fluorescence spectroscopy (XRF) offers rapid, multi-elemental, low cost and non-destructive elemental analysis. Different studies have used this technique to investigate distribution and concentration of essential and deleterious elements in vegetation. Special emphasis has been recently placed on the key aspects concerning sampling processes, laboratory protocols and calibration methods for quantitative analysis. The aim of the present study was to develop a quantitative methodology to determine the nutrient content in Pinus taeda tree-rings by XRF. Using a 1 mm X-ray excitation beam from a Rh X-ray tube at 30 kV and 600 µA, and dwell time of 20 s, we present calibration curves for P, S, K, Ca, Mn and Fe based on multi-elemental standard addition using wood matrix of 17-year-old Pinus taeda trees. Satisfactory recoveries of our XRF approach for Ca, P, Mn, S and K (<115%), and tolerable for Fe (123%) were obtained compared to inductively coupled plasma optical emission spectrometry results. The non-destructive and quantitative XRF method allows assessing annual element concentrations of P. taeda trees, in order to provide tools for monitoring the nutrient dynamic in an experimental plantation. Furthermore, a method for elemental quantification based on multi-elemental standard addition using wood matrix is described as a useful procedure for future applications.

Estimation of leaf area of Erythroxylum citrifolium from linear leaf dimensions / Estimativa da área foliar de Erythroxylum citrifolium a partir de dimensões lineares da folha

Erythroxylum citrifolium is a neotropical plant species recorded in all regions of Brazil. Determining leaf area is of fundamental importance to studies related to plant propagation and growth. The objective was to obtain an equation to estimate the leaf area of E. citrifolium from linear dimensions of the leaf blade (length and width). A total of 200 leaf blades were collected in Parque Estadual Mata do Pau-Ferro in the municipality of Areia, state of Paraíba, Northeast Brazil. The models evaluated were: linear, linear without intercept, quadratic, cubic, power and exponential. The best model was determined by the criteria of: high coefficient of determination (R²), low root mean square error (RMSE), low Akaike information criterion (AIC), high Willmott concordance index (d) and a BIAS index close to zero. All of the models constructed satisfactorily estimated the leaf area of E. citrifolium, with coefficients of determination above 0.9050, but the power model using the product between length and width (L*W) y = 0.5966 * LW1.0181 was the best, with the highest values of R² and d, low values of RMSE and AIC, and a BIAS index closest to zero.

Erythroxylum citrifolium é uma espécie de planta neotropical com registros em todas as regiões do Brasil. A determinação da área foliar é de fundamental importância em estudos relacionados a propagação e crescimento vegetal. O objetivo foi obter uma equação que permita estimar a área foliar de E. citrifolium a partir de dimensões lineares do limbo foliar (comprimento e largura). Foram coletados 200 limbos foliares no Parque Estadual Mata do Pau-Ferro, Areia, Paraíba, Nordeste do Brasil. Os modelos empregados foram: linear, linear sem intercepto, quadrático, cúbico, potencial e exponencial. Os critérios utilizados para escolher o melhor modelo, teve como base o maior coeficiente de determinação (R²), menor raiz do quadrado médio do erro (RMSE), menor critério de informação de Akaike (AIC), maior índice de concordância de Willmott (d) e índice BIAS mais próximo de zero. Todos os modelos construídos podem estimar satisfatoriamente a área foliar de E. citrifolium, com coeficientes determinação acima de 0,9050, porém o modelo potencial utilizando o produto entre comprimento e largura (L*W) y = 0,5966 * LW1,0181 é o mais indicado, com os maiores valores de R² e d, menores valores de RMSE e AIC, e índice BIAS mais próximo de zero.

Pore Structure Damages in Cement-Based Materials by Mercury Intrusion: A Non-Destructive Assessment by X-Ray Computed Tomography.

Mercury intrusion porosimetry (MIP) is questioned for possibly damaging the micro structure of cement-based materials (CBMs), but this theme still has a lack of quantitative evidence. By using X-ray computed tomography (XCT), this study reported an experimental investigation on probing the pore structure damages in paste and mortar samples after a standard MIP test. XCT scans were performed on the samples before and after mercury intrusion. Because of its very high mass attenuation coefficient, mercury can greatly enhance the contrast of XCT images, paving a path to probe the same pores with and without mercury fillings. The paste and mortar showed the different MIP pore size distributions but similar intrusion processes. A grey value inverse for the pores and material skeletons before and after MIP was found. With the features of excellent data reliability and robustness verified by a threshold analysis, the XCT results characterized the surface structure of voids, and diagnosed the pore structure damages in terms of pore volume and size of the paste and mortar samples. The findings of this study deepen the understandings in pore structure damages in CBMs by mercury intrusion, and provide methodological insights in the microstructure characterization of CBMs by XCT.

NIR spectroscopic method for the detection of calcium carbide in artificial ripening of mangoes (Magnifera indica).

The present study presents a novel method employing Near Infrared Spectroscopy (NIR) for detection of the use of calcium carbide in artificial ripening of mangoes. Use of calcium carbide has been banned in artificial ripening of fruits as it contains traces of arsenic. Mango samples were ripened artificially using calcium carbide and compared with naturally ripened mangoes using NIR spectroscopic wavelength ranging from 600 to 1100 nm. The captured NIR spectra from mango samples were analysed using multivariate methods including principal component analysis, particle least square and successive projection algorithm. The obtained results showed distinguishing zones for naturally and artificially ripened mangoes. Furthermore, the arsenic content was obtained through ICP-MS analysis, and it was found that mangoes ripened artificially using calcium carbide have a higher content of arsenic. Hence, arsenic was used as a principal component in the analysis. The developed method is not unique to samples that were grown in any particular region or year as it and can be used universally as NIR will give the distinguishing comparison between naturally- and artificially ripened mangoes. This method is simple, non-invasive, non-destructive and rapid for detection of use of calcium carbide in the artificial ripening of mangoes.

Leaf area estimation for Psychotria carthagenensis and Psychotria hoffmannseggiana as a function of linear leaf dimensions

Determining leaf area is important for studies involving plant growth and development. The aim of the present study was to obtain models for estimating leaf area of Psychotria carthagenensis and Psychotria hoffmannseggiana using linear measurements of leaf blades (length and width). Two hundred leaf blades of each species were collected in Parque Estadual Mata do Pau-Ferro in the municipality of Areia, Paraíba, Northeast Brazil. The equations evaluated for producing potential models included the following: linear, quadratic, potential and exponential. The criteria used to determine the best model(s) were as follows: high coefficient of determination (R²), low root-mean-square error (RMSE), low Akaike information criterion (AIC), high Willmott concordance index (d) and a BIAS ratio close to zero. All evaluated models satisfactorily estimated leaf area for the two species, but the equation ŷ = 0.6373 * LW0.9804 was the most appropriate for P. carthagenensis, while ŷ = 0.6235 * LW0.9712 was the most appropriate for P. hoffmannseggiana.

Leaf area estimation of squash 'Brasileirinha' by leaf dimensions / Estimação da área foliar de abobrinha 'Brasileirinha' por dimensões foliares

ABSTRACT: The objectives of this work were estimate the leaf area of squash 'Brasileirinha' by linear dimensions of the leaves and check models available in the literature. An experiment was conducted in the 2015/16 sowing season. Were collected 500 leaves and in each one, were measured the length (L), width (W) and length×width product (LW) and determined the real leaf area (LA). Then, 400 leaves were separated to generate models of the leaf area (LA) as a function of linear dimension (L, W or LW) of squash. The remaining 100 leaves were used for the validation of models. A second experiment was conducted in the 2016/17 sowing season. Were collected 250 leaves, used only for the validation of the models of the first experiment. There is collinearity between L and W and, therefore, models using the LW product are not recommended. The model LA=0.5482W2 + 0.0680W (R²=0.9867) is adequate for leaf area estimation of squash 'Brasileirinha'.

RESUMO: Os objetivos deste trabalho foram estimar a área foliar de abobrinha 'Brasileirinha' por dimensões lineares das folhas e testar modelos disponíveis na literatura. Foi conduzido um experimento na safra 2015/16 sendo coletas 500 folhas. Em cada folha foram mensurados comprimento (L), largura (W), calculado produto comprimento×largura (LW) e determinada a área foliar real (LA). Depois, 400 folhas foram separadas para a geração de modelos da área foliar real (LA) em função da dimensão linear (L, W ou LW) de abobrinha. As demais 100 folhas foram utilizadas na validação dos modelos. Um segundo experimento foi conduzido na safra 2016/17, no qual foram coletadas 250 folhas utilizadas na validação dos modelos gerados no primeiro experimento. Existe colinearidade entre L e W e, por isso, os modelos que utilizam o produto LW não são recomendados. O modelo LA=0,5482W2+0,0680W (R²=0,9867) é adequado para a estimação de área foliar de abobrinha 'Brasileirinha'.

In situ label-free monitoring of human adipose-derived mesenchymal stem cell differentiation into multiple lineages.

Precise characterizations of stem cell differentiation into specific lineages, especially in non-destructive and non-invasive manner, are extremely important for generating patient-specific cells without mass loss of differentiated cells. Here, we report a new method capable of in situ label-free quantification of stem cell differentiation into multiple lineages, even at a single cell level. The human adipose-derived mesenchymal stem cells (hADMSCs) were first differentiated into two different types of cells (osteoblasts and adipocytes) and these differentiated cells were then intensively analyzed by micro-Raman spectroscopy. Interestingly, the Raman peaks assigned to lipid droplets and hydroxyapatite were found to be highly specific to the adipocyte (fat cell) and osteoblast (bone cell) and were thus found to be useful for generating label-free single cell Raman images in combination with CH3 (2935 cm-1) peaks for visualizing cell shape. Remarkably, based on these Raman images, we found that the osteogenesis of hADMSCs could be determined and quantified after 9 days of differentiation, which is a week earlier than with the typical alizarin red staining method. In the case of adipogenesis, the increase of lipid droplets in the cytoplasm at the single cell level could be clearly visualized and detected during the entire period of adipogenesis, which is impossible using any other currently available methods such as Oil Red O and immunostaining. Hence, the new method reported in this study is highly promising as an analytical tool for precise in-situ monitoring of stem cell differentiation, and could facilitate the use of stem cell-based materials for the regenerative therapies.

Leaf area estimation from linear measurements in different ages of Crotalaria juncea plants

ABSTRACT The goal of this study was to estimate the leaf area of Crotalaria juncea according to the linear dimensions of leaves from different ages. Two experiments were conducted with C. juncea cultivar IAC-KR1, in the 2014/2015 sowing seasons. At 59, 82, 102, 129 days after sowing (DAS) of the first and 61, 80, 92, 104 DAS of the second experiment, 500 leaves were collected, totaling 4,000 leaves. In each leaf, the linear dimensions were measured (length, width, length/width ratio and length × width product) and the specific leaf area was determined through Digimizer and Sigma Scan Pro software, after scanning images. Then, 3,200 leaves were randomly separated to generate mathematical models of leaf area (Y) in function of linear dimension (x), and 800 leaves for the models validation. In C. juncea, the leaf areas determined by Digimizer and Sigma Scan Pro software are identical. The estimation models of leaf area as a function of length × width product showed superior adjustments to those obtained based on the evaluation of only one linear dimension. The linear model Ŷ=0.7390x (R2=0.9849) of the real leaf area (Y) as a function of length × width product (x) is adequate to estimate the C. juncea leaf area.

Allometric models and aboveground biomass stocks of a West African Sudan Savannah watershed in Benin.

BACKGROUND: The estimation of forest biomass changes due to land-use change is of significant importance for estimates of the global carbon budget. The accuracy of biomass density maps depends on the availability of reliable allometric models used in combination with data derived from satellites images and forest inventory data. To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on allometric equations and the spatial distribution of aboveground biomass stocks in each land use/land cover (LULC) class is needed for the different ecological zones. Such information has been sparse for the West African Sudan Savannah zone. This paper provides new data and results for this important zone. The analysis combines satellite images and locally derived allometric models based on non-destructive measurements to estimate aboveground biomass stocks at the watershed level in the Sudan Savannah zone in Benin. RESULTS: We compared three types of empirically fitted allometric models of varying model complexity with respect to the number of input parameters that are easy to measure at the ground: model type I based only on the diameter at breast height (DBH), type II which used DBH and tree height and model type III which used DBH, tree height and wood density as predictors. While for most LULC classes model III outperformed the other models even the simple model I showed a good performance. The estimated mean dry biomass density values and attached standard error for the different LULC class were 3.28 ± 0.31 (for cropland and fallow), 3.62 ± 0.36 (for Savanna grassland), 4.86 ± 1.03 (for Settlements), 14.05 ± 0.72 (for Shrub savanna), 45.29 ± 2.51 (for Savanna Woodland), 46.06 ± 14.40 (for Agroforestry), 94.58 ± 4.98 (for riparian forest and woodland), 162 ± 64.88 (for Tectona grandis plantations), 179.62 ± 57.61 (for Azadirachta indica plantations), 25.17 ± 7.46 (for Gmelina arborea plantations), to 204.92 ± 57.69 (for Eucalyptus grandis plantations) Mg ha-1. The higher uncertainty of agroforestry system and plantations is due to the variance in age which affects biomass stocks. CONCLUSION: The results from this study help to close the existing knowledge gap with respect to biomass allometric models at the watershed level and the estimation of aboveground biomass stocks in each LULC in the Sudan Savannah in West Africa. The use of model type I, which relies only on the easy to measure DBH, seems justified since it performed almost as good as the more complex model types II and III. The work provided useful data on wood density of the main species of the Sudan Savannah zone, the related local derived biomass expansion factor and the biomass density in each LULC class that would be an indispensable information tool for carbon accounting programme related to the implementation of the Kyoto Protocol and REDD+ (reducing emissions from deforestation and forest degradation, and forests conservation, sustainable management of forests, and enhancement of forest carbon stocks) initiatives.

Bioimpedance as a tool for evaluating the body composition of suruvi (Steindachneridion scriptum) / Bioimpedância como ferramenta de análise da composição corporal do suruvi (Steindachneridion scriptum)

Abstract Bioelectrical impedance analysis (BIA) is regarded as an important tool for evaluating the body composition of different animals in a rapid, non-destructive, and low-cost manner. A South American fish species, Steindachneridion scriptum, known as suruvi, was selected for study in this investigation. A protocol to produce fish with different body composition was used to allow BIA to adequately predict the body composition of suruvi. The fish were fed twice each day with two different diets; a low lipid diet (8.90%), and a high lipid diet (18.68%). These dietary differences allowed suruvi specimens with different body compositions to be produced. The BIA readings were determined using a Quantum X Bioelectrical Body Composition Analyzer. Two readings (dorsal and ventral) were obtained for each fish. After BIA readings were obtained, the proximate composition of the fish bodies for each individual was determined. All of the study data were used to establish correlation equations between proximate analyses and BIA values. Strong correlations were found for S. scriptum. The highest correlations were obtained for the following pairs of quantities, using BIA data from dorsal readings: moisture and resistance in series (R2 = 0.87); protein and resistance in series (R2 = 0.87); and ash and reactance in parallel (R2 = 0.82). We conclude that BIA is an effective method in determining the body composition of S. scriptum without sacrificing the fish. However, to expand the use of this new technology it is important to define strict BIA protocols to guarantee accurate estimates.

Resumo A análise da impedância bioelétrica (BIA) é considerada uma importante ferramenta para avaliar a composição corporal de diferentes animais de uma maneira rápida, não-destrutiva e de baixo custo. A espécie Sul-americana Steindachneridion scriptum, popularmente conhecida como suruvi, foi selecionada para este estudo. Foi utilizado um protocolo para produzir peixes com distintas composições corporais, permitindo a validação da BIA para análise adequada da composição corporal do suruvi. Os peixes foram alimentados duas vezes ao dia com duas dietas diferentes: uma de baixo teor lipídico (8,90%) e outra de alto teor lipídico (18,68%). Essa diferença nas dietas possibilitou a produção de indivíduos com diferentes composições corporais. As leituras da BIA foram determinadas utilizando-se o equipamento Quantum X Bioelectrical Body Composition Analyzer. Duas leituras (dorsal e ventral) foram obtidas para cada peixe. Após as leituras, para cada peixe individualmente, a composição proximal dos peixes foi determinada. Todos os dados obtidos foram utilizados para estabelecer as equações de correlação entre as análises proximais e os valores da BIA. Fortes correlações foram encontradas para S. scriptum. As maiores correlações foram obtidas para as análises dorsais a seguir: umidade e resistência em série (R2 = 0,87); proteína e resistência em série (R2 = 0,87); cinzas e reactância em paralelo (R2 = 0,82). Pode-se concluir que o método BIA é eficiente em determinar a composição corporal do suruvi S. scriptum sem sacrificar o animal. No entanto, para expandir o uso desta nova tecnologia é necessário definir protocolos rigorosos para garantir estimativas precisas.

Bioimpedance as a tool for evaluating the body composition of suruvi (Steindachneridion scriptum)

Abstract Bioelectrical impedance analysis (BIA) is regarded as an important tool for evaluating the body composition of different animals in a rapid, non-destructive, and low-cost manner. A South American fish species, Steindachneridion scriptum, known as suruvi, was selected for study in this investigation. A protocol to produce fish with different body composition was used to allow BIA to adequately predict the body composition of suruvi. The fish were fed twice each day with two different diets; a low lipid diet (8.90%), and a high lipid diet (18.68%). These dietary differences allowed suruvi specimens with different body compositions to be produced. The BIA readings were determined using a Quantum X Bioelectrical Body Composition Analyzer. Two readings (dorsal and ventral) were obtained for each fish. After BIA readings were obtained, the proximate composition of the fish bodies for each individual was determined. All of the study data were used to establish correlation equations between proximate analyses and BIA values. Strong correlations were found for S. scriptum. The highest correlations were obtained for the following pairs of quantities, using BIA data from dorsal readings: moisture and resistance in series (R2 = 0.87); protein and resistance in series (R2 = 0.87); and ash and reactance in parallel (R2 = 0.82). We conclude that BIA is an effective method in determining the body composition of S. scriptum without sacrificing the fish. However, to expand the use of this new technology it is important to define strict BIA protocols to guarantee accurate estimates.

Resumo A análise da impedância bioelétrica (BIA) é considerada uma importante ferramenta para avaliar a composição corporal de diferentes animais de uma maneira rápida, não-destrutiva e de baixo custo. A espécie Sul-americana Steindachneridion scriptum, popularmente conhecida como suruvi, foi selecionada para este estudo. Foi utilizado um protocolo para produzir peixes com distintas composições corporais, permitindo a validação da BIA para análise adequada da composição corporal do suruvi. Os peixes foram alimentados duas vezes ao dia com duas dietas diferentes: uma de baixo teor lipídico (8,90%) e outra de alto teor lipídico (18,68%). Essa diferença nas dietas possibilitou a produção de indivíduos com diferentes composições corporais. As leituras da BIA foram determinadas utilizando-se o equipamento Quantum X Bioelectrical Body Composition Analyzer. Duas leituras (dorsal e ventral) foram obtidas para cada peixe. Após as leituras, para cada peixe individualmente, a composição proximal dos peixes foi determinada. Todos os dados obtidos foram utilizados para estabelecer as equações de correlação entre as análises proximais e os valores da BIA. Fortes correlações foram encontradas para S. scriptum. As maiores correlações foram obtidas para as análises dorsais a seguir: umidade e resistência em série (R2 = 0,87); proteína e resistência em série (R2 = 0,87); cinzas e reactância em paralelo (R2 = 0,82). Pode-se concluir que o método BIA é eficiente em determinar a composição corporal do suruvi S. scriptum sem sacrificar o animal. No entanto, para expandir o uso desta nova tecnologia é necessário definir protocolos rigorosos para garantir estimativas precisas.