Green Red Index Research Articles

Effects of external staining on mechanical, optical, and biocompatibility properties of additively manufactured 3Y-TZP ceramic for dental applications

Three mole percent yttria-stabilized tetragonal zirconia polycrystal (3Y-TZP) ceramics are exemplary materials for dental restoration due to their high mechanical strength, fracture toughness, chemical endurance, and biocompatibility. Nevertheless, 3Y-TZP ceramics are opaque and their CAD/CAM manufacturing process may cause micro-cracks in conventional clinical practice. In this study, 3Y-TZP ceramic samples were prepared using vat photopolymerization, pre-sintering, external staining, and final high-temperature sintering. The microstructures, mechanical properties, optical properties, and cytotoxicity of the 3Y-TZP ceramic samples were investigated. The results indicate that with increasing Fe3+ concentration of staining solution from 0.1 mol/L to 0.3 mol/L and increasing staining time from 5 s to 30 min, the 3Y-TZP ceramic samples showed a tetragonal crystal structure of zirconia with densely packed grains and a slight increase in grain size. The flexural strength, Vickers hardness, and fracture toughness of 3Y-TZP ceramic samples stained in 0.1–0.3 mol/L Fe3+ solution for 5 s to 3 min were all greater than 665 MPa, 11.9 GPa, and 5 MPa m1/2, respectively, meeting the mechanical requirements for clinical application. Colorimetric analysis revealed a decrease in L* (black-white index) from 90.4 to 81.3, an increase in a* (green-red index) from −1.5 to 3.2, and an increase in b* (blue-yellow index) from 11.6 to 20.3, approximating the commercial VITA 3D-Master Shade Guide chromaticity. Furthermore, the 3Y-TZP ceramic samples exhibited a cell viability of 90% or higher toward L929 cells.

Bamboo as a substitute for plastic: Research on the application performance and influencing mechanism of bamboo buttons

In the context of the “bamboo as a substitute for plastic” initiative and global restrictions on plastic, the substitution of plastic buttons with bamboo buttons offers significant advantages in terms of resource efficiency, environmental impact, and ecological benefits. This study demonstrated the preparation of bamboo buttons by the manufacturing method of plastic buttons. Then the bamboo buttons were heat-treated to improve their application properties as garment fasteners. It was to explore the application performance and the underlying influencing mechanism of bamboo buttons, encompassing the morphology, physical and chemical properties, color variation, versatility in different scenarios, and mechanical properties of bamboo buttons. The findings demonstrated that heat treatment process had the potential to enhance the surface color uniformity and richness of bamboo buttons. Moreover, a satisfactory linear relationship was observed between the major components of bamboo buttons and the color index. Lignin played a major role in color index, which was negatively correlated with brightness index (L*) and yellow-blue index (b*), and positively correlated with red-green index (a*) and total chromatic difference (ΔEab*). Color variations were observed in bamboo buttons by washing with seawater, chlorine water, and soap (40 °C, 50 °C, 60 °C, and 95 °C). The tensile strength of the bamboo buttonhole gradually decreased from 291.84 ± 28.10 N to 136.69 ± 25.19 N as the temperature increased. However, bamboo buttons met the requirements for light duty applications. The fracture morphology of bamboo buttons was categorized into four forms: linearity, stair pattern, parallel lines, and Y shape. All broken bamboo buttons exhibited fractures along the fiber direction and within the intercellular layer, mainly attributed to the differences in chemical composition between the cell wall and the intercellular layer. This research could provide a theoretical foundation for the promotion and application of bamboo buttons.

Temporal and spatial variability of physical and chemical properties in reclaimed soil after sulphur borehole mining

Mining contributes to the creation of degraded areas that are difficult to rehabilitate because they are subject to various transformations. Specifically, sulphur mining using the Frasch borehole method causes multidirectional changes of soil properties and thus presents challenges for post-mining rehabilitation. The aim of the current study was to evaluate the effectiveness of agricultural (meadow-type) reclamation and to understand how the soil recovers over time by assessing the spatio-temporal variability of the reclaimed soil after borehole sulphur mining. Selected soil properties and spectral indices based on satellite data were analysed: before reclamation, 3 years after reclamation and 15 years after reclamation. Texture, bulk density, porosity, water capacity, total organic carbon (TOC) and pH were measured and distribution maps of these parameters were generated using kriging. Additionally, maps of spectral indices (Green Normalized Difference Vegetation Index, Normalized Difference Soil Moisture Index, Soil Adjusted Vegetation Index, Enhanced Vegetation Index and Red–Green Index) based on Landsat imagery were created to support the field survey data. The soil revealed high temporal and spatial variability, as evidenced by the distributions of measured parameters and their coefficients of variation at different reclamation stages. Multidirectional remodelling of the soil structure occurred, resulting in changes in the differential porosity, field water capacity, texture, reaction and TOC. Statistically confirmed differences in soil parameters between sampling points were observed. The variability of the physical and chemical parameters at the individual sampling point also differed between the reclamation stages. We observed a general trend towards homogenisation of the spatial distributions of the soil parameters. This was also confirmed by the maps of spectral indices, which showed establishment and development of a continuous vegetation cover and the subsequent improvement of its condition.

DISCOLORATION OF OAK VENEER INDUCED BY METAL IONS

The 3 mm thick oak veneers were discolored by single ions of Fe2+, Cu2+, and Mn2+ and mixed ions of Fe2+-Cu2+, Fe2+-Mn2+, and Cu2+-Mn2+. The brightness (L*), red-green index (a*), and yellow-blue index (b*) of the veneers changed by varying degrees with the changes in ion mass fraction, temperature, heating time, ion species, and ion mass fraction ratio. The maximum values of total color difference (△E*) of the veneers were 38.94, 11.79, and 9.42 for Fe2+, Cu2+, and Mn2+. Moreover, the total color difference (△E*) values of 24.07, 13.71, and 4.45 were observed for Fe2+-Cu2+, Fe2+-Mn2+, and Cu2+-Mn2+ mixed ions. The veneers showed different degrees of vibrational peaks after discoloration. According to the ultraviolet spectrum, Fe2+ had a red shift in the ultraviolet absorption band of the unsaturated carbonyl compound and benzene ring compound. Moreover, the dark effect of Fe2+, Fe2+-Cu2+, Fe2+-Mn2+, Mn2+, Cu2+-Mn2+, and Cu2+ gradually decreased. The surface of the veneer was flat, without any rupture or deformation, and the pores were clear after treatment.

Effect of Fe2O3 doping on color and mechanical properties of dental 3Y-TZP ceramics fabricated by stereolithography-based additive manufacturing

In this study, iron(III) oxide (Fe2O3)-doped zirconia (3Y-TZP) ceramics with desirable mechanical and color properties for dental restorations were fabricated by stereolithography-based additive manufacturing. Six zirconia ceramic paste specimens with high solid loading (58 vol%) and reasonably low viscosity were prepared according to doped content of Fe2O3 (0–0.14 wt%). Zirconia ceramics were fabricated using commercial stereolithography three-dimensional printer and sintered at 1500 °C for 4 h to obtain final dense parts with a relative density of above 99%. Effects of Fe2O3 doping on microstructure, mechanical properties, and color of 3Y-TZP ceramics were investigated. Results indicate that Fe2O3 exhibited little effect on the shrinkage and density of colored ceramics compared to uncolored ceramics. Average grain size of 3Y-TZP ceramics sintered at 1500 °C increased with increasing content of Fe2O3. X-ray diffraction analysis showed that tetragonal phase was dominant phase structure of white and colored 3Y-TZP ceramics, and monoclinic phase increased with increasing Fe2O3 content. Compared to uncolored specimens, Fe2O3 exhibited negative effects on three-point flexural strength (mean > 879.70 MPa), Vickers hardness (mean > 12.14 GPa), and indentation fracture toughness (mean > 4.23 MPa m1/2) of the colored specimens. With the increase in the content of Fe2O3 from 0 to 0.14 wt%, L* (black–white index) value decreased from 83.39 to 79.54, a* (green–red index) value increased from −2.28 to −0.74, and b* (blue–yellow index) value increased from 1.15 to 17.94. Chromaticity (L*, a*, b*) fell within the range of natural tooth color, indicating that it is suitable for dental application because of its color compatibility with natural teeth. In addition, the transmittance slightly decreased with increasing Fe2O3 content. Thus, Fe2O3-doped 3Y-TZP ceramics can be used as potential candidates for aesthetic dental restoration materials.

Using Statistical Methods to Comparatively Analyze the Visual Characteristics of Flattened Bamboo Boards in Different Bamboo Culms.

Different flattened bamboo boards will produce different visual effects, which directly determine consumers’ preferences. However, their visual characteristics were unknown. To clarify the visual effects of flattened bamboo boards in different bamboo culms, the visual, physical, and psychological quantities were firstly studied using their quantitative color and glossiness measurements, combined with quantitative semantic differential and statistical methods. Key results revealed that the values of lightness L* and blue–yellow index b* from the base to the top of the bamboo culms tended to decrease gradually, while green–red index a* values exhibited an increasing trend, and glossiness GZL (GZT) showed no significant difference. The L* value of bamboo outer layer (30.18) was smaller than that of the outer (61.90) and the inner (68.68), which had an increasing trend from the outside to the inside of the bamboo culm, while the GZL (GZT) values corresponded to 6.07 (4.66), 4.51 (3.12), and 2.77 (2.55), showing an opposite trend. The a* and b* values present a rise-fall tendency. According to visual psychological assessment, the outer was reflected as an “artificial–decorative”, “smooth–warm”, and “comfort–sophisticated” feeling; the inner had an “artificial–practical”, “smooth–warm”, and “comfort–sophisticated” sense; the bamboo outer layer had an “nature–practical”, “rough–cold”, and “sick–primitive” sense. Furthermore, predictive models for visual psychological quantities were constructed. This work provides a theoretical data basis for furniture design and standard materials application of flattened bamboo boards.

IMPACT OF HEAT TREATMENT ON THE SURFACE COLOR AND GLOSSINESS OF YOUNG EUCALYPTUS WOOD

The study analyzed the impact of heat treatment conditions (temperature and duration) on the surface color and glossiness of young eucalyptus wood. The young eucalyptus wood samples were treated at different treatment temperatures (165°C, 185°C, 205°C) and duration (2 h, 3 h, 4 h). The color of the young eucalyptus wood was determined using CIE L*a*b* system and the gloss was measured with glossmeter at 20°, 60°, and 85° incident angle before and after the heat treatment. The total color difference ( ), lightness (L*), red-green index (a*), and yellow-blue index (b*), were investigated at different treatment conditions. The values of L* and b* decrease continuously with the increasing temperature and duration. The results of analysis of variance (two-way ANOVA) indicate that the heat treatment temperature has a significant effect on the colorimetric properties of the heat-treated young eucalyptus wood. The gloss decreased after the heat treatment for both perpendicular and parallel directions. ANOVA analysis showed that the treatment temperature duration have a significant effect on the parallel glossiness of 85°(p＜0.05). These are probably due to differences in surface roughness between untreated and heat-treated wood. To achieve the desired color like teak wood, the preferred temperature is no more than 185°C.

An Integration of Linear Model and ‘Random Forest’ Techniques for Prediction of Norway Spruce Vitality: A Case Study of the Hemiboreal Forest, Latvia

The increasing extreme weather and climate events have a significant impact on the resistance and resilience of Norway spruce trees. The responses and adaptation of individual trees to certain factors can be assessed through the tree breeding programmes. Tree breeding programmes combined with multispectral unmanned aircraft vehicle (UAV) platforms may assist in acquiring regular information of individual traits from large areas of progeny trials. Therefore, the aim of this study was to investigate the vegetation indices (VI) to detect the early stages of tree stress in Norway spruce stands under prolonged drought and summer heatwave. Eight plots within four stands throughout the vegetation season of 2021 were monitored by assessing spectral differences of tree health classes (Healthy, Crown damage, New crown damage, Dead trees, Stem damage, Root rot). From all tested VI, our models showed a moderate marginal R2 and total explanatory power—for Normalized Difference Red-edge Index (NDRE), marginal R2 was 0.26, and conditional R2 was 0.49 (p < 0.001); for Normalized Difference Vegetation Index (NDVI), marginal R2 was 0.34, and conditional R2 was 0.60 (p < 0.001); for Red Green Index (RGI), marginal R2 was 0.36, and conditional R2 was 0.55 (p < 0.001); while for Chlorophyll Index (CI), marginal R2 was 0.27, and conditional R2 was 0.49 (p < 0.001). The reliability of the identification of tree health classes for selected VI was weak to fair (overall classification accuracy ranged from 34.4% to 56.8%, kappa coefficients ranged from 0.09 to 0.34) if six classes were assessed, and moderate to substantial (overall classification accuracy ranged from 71.1% to 89.6% and kappa coefficient from 0.39 to 0.71) if two classes (Crown damage and Healthy trees) were tested.

Electrospun carboxymethyl cellulose-gelatin nanofibrous films encapsulated with Mentha longifolia L. essential oil for active packaging of peeled giant freshwater prawn

The aims of the current study were to encapsulate Mentha longifolia L. essential oil (MEO; 0.5, 1, and 2%) into carboxymethyl cellulose-gelatin (CMC-GE) nanofibers via electrospinning and to evaluate the effects of fabricated nanofibrous films on improving the shelf-life of peeled freshwater prawns during refrigerated storage for 14 days. CMC-GE-MEO 0.5%, CMC-GE-MEO 1%, and CMC-GE-MEO 2% nanofibrous films showed significantly lower force (21.74–25.33 N), tensile strength (6.52–8.56 MPa), water vapor permeability (7.25-9.34 × 10‾4 g mm/m2 h Pa), and swelling index (20.14–27.45%) compared to the neat CMC-GE (p < 0.05). The elongation at break significantly increased when MEO was incorporated into the CMC-GE (p < 0.05). The neat CMC-GE had the highest blue-yellow index (b = 1.02 ± 0.01) and the lowest green-red index (a = −0.12 ± 0.01) and lightness (L = 95.92 ± 0.07). CMC-GE-MEO 1% and CMC-GE-MEO 2% nanofibrous films successfully improved the microbial population and chemical property of peeled prawns for 12 and 14 days, respectively. Prawns packaged with CMC-GE-MEO 2% nanofibrous film had significantly the highest sensory scores in terms of odor, color, texture, taste, and total acceptance throughout the study period (p < 0.05).

Detecting Biophysical Characteristics and Nitrogen Status of Finger Millet at Hyperspectral and Multispectral Resolutions

Finger millet (Eleusine coracana Gaertn L.) is an important grain crop for small farmers in many countries. Reliable estimates of crop parameters, such as crop growth and nitrogen (N) content, through remote sensing techniques can improve in-season management of finger millet. This study investigated the relationships of hyperspectral reflectance with canopy height, green canopy cover, leaf area index (LAI), and N concentrations of finger millet using an optimal waveband selection procedure with partial least square regression (PLSR). Predictive performance of 13 vegetation indices (VIs) computed from the original hyperspectral data as well as synthesized Landsat-8 and Sentinel-2 data were evaluated and compared for estimating various crop parameters with simple linear regression (SLR) and multilinear regression (MLR) models. The optimal wavebands determined by PLSR were mostly concentrated within 1,000–1,100 nm for both LAI and dry biomass but were scattered for other canopy parameters. The SLR statistics resulted in the simple ratio pigment index (SRPI) and red/green index (RGI) performing best when predicting LAI (R2v = 0.53–0.59) and canopy cover (R2v = 0.72–0.76). The blue/green index (BGI1) was strongly related to canopy height (R2v = 0.65–0.78), dry biomass (R2v = 0.42–0.49), and N concentration (R2v = 0.70–0.83) of finger millet, regardless of spectral resolutions. The MLR approach, using four maximum VIs as input variables, improved the prediction accuracy of N concentration by 14% compared to both SLR and waveband selection methods. VIs computed from synthesized Landsat-8 and Sentinel-2 satellite data resulted in similar or greater prediction accuracy than hyperspectral data for various canopy parameters of finger millet, indicating publicly accessible multispectral data could serve as alternative to hyperspectral data for improved crop management decisions via precision agriculture.

Effect of different drying treatments on the physicochemical, functional, and antioxidant properties of Bacopa monnieri.

Bacopa monnieri (L.) Wettst is a very high-value medicinal plant that is commonly used for improving cognitive functions. However, the availability of very limited information on the drying method of B. monnieri has prompted to optimize a suitable drying method. The present study therefore aimed to evaluate the influence of the following six drying treatments on the quality of B. monnieri sample: microwave drying at 300 W and 600 W, hot air-drying at 50°C and 70°C, solar drying, and freeze-drying (FD). The quality attributes of the dried samples were comparatively analyzed in terms of color, total color difference, moisture content, water activity (a w), antioxidant activity, and bacoside A and bacopaside I content. The results of this study showed significant differences (P < 0.05) among the different drying methods in International Commission on Illumination (CIE) parameters, namely lightness index (L*), red-green index (a*), and yellow-blue index (b*), ΔE and a values. Among the samples dried with the six drying methods, freeze-dried B. monnieri samples had an attractive color with the lowest total color difference value (11.415%), a w value (0.15%), and maximum bacoside A (3.389%) and bacopaside I (0.620%) content. Moreover, Fourier transform infrared spectroscopy (FT-IR) analysis showed no major difference in the functional groups in B. monnieri samples processed by the different drying methods. Considering the retention of quality after drying, FD was found to be very effective for future large-scale production of good quality dried B. monnieri products.

Rapid Recognition of Field-Grown Wheat Spikes Based on a Superpixel Segmentation Algorithm Using Digital Images.

Wheat spike number, which could be rapidly and accurately estimated by the image processing technology, serves as the basis for crop growth monitoring and yield prediction. In this research, simple linear iterative clustering (SLIC) was performed for superpixel segmentation of the digital images of field-grown wheat. Firstly, certain characteristic color parameters were extracted and analyzed from the digital images, and the classifiers with the highest accuracy were chosen for subsequent image classification. Next, the main body of wheat spike was extracted through a series of morphological transformation and estimate was performed for each region. Backbone of the head was extracted, and the number of inflection points of backbone was detected. Then the wheat spike number was determined by combining the estimate of inflection points of backbone and the estimate for each region. Finally, the wheat spike number estimate was verified under four nitrogen fertilizer levels. The results were as follows: (1) Super green value (Eg) and normalized red green index (Dgr) were used as classification features to recognize wheat spikes, soil and leaves; (2) compared with pixel-based image processing, wheat spike recognition effect was much better after superpixel segmentation, as the main body of wheat spike extracted was more clear and morphology more intact; and (3) wheat plants had better growth under high nitrogen fertilizer level, and the accuracy of wheat spike number estimation was also the highest, which was 94.01%. The growth status was the worst under no nitrogen fertilizer application, and the accuracy of wheat spikes number estimation was also the lowest, which was only 80.8%. After excluding the no nitrogen condition, the accuracy of wheat spikes number estimation among mixed samples with more uniform growth status was up to 93.8%, which was an increase by 10.1% than before the exclusion. Wheat spikes number estimate based on superpixel segmentation and color features was a rapid and accurate method that was applicable to the field environment. However, this method was not recommended for use when the growth status of wheat was poor or of high heterogeneity. The findings provided reference for field-grown wheat yield estimate.

On the Potentiality of UAV Multispectral Imagery to Detect Flavescence dorée and Grapevine Trunk Diseases

Among grapevine diseases affecting European vineyards, Flavescence dorée (FD) and Grapevine Trunk Diseases (GTD) are considered the most relevant challenges for viticulture because of the damage they cause to vineyards. Unmanned Aerial Vehicle (UAV) multispectral imagery could be a powerful tool for the automatic detection of symptomatic vines. However, one major difficulty is to discriminate different kinds of diseases leading to similar leaves discoloration as it is the case with FD and GTD for red vine cultivars. The objective of this paper is to evaluate the potentiality of UAV multispectral imagery to separate: symptomatic vines including FD and GTD (Esca and black dead arm) from asymptomatic vines (Case 1) and FD vines from GTD ones (Case 2). The study sites are localized in the Gaillac and Minervois wine production regions (south of France). A set of seven vineyards covering five different red cultivars was studied. Field work was carried out between August and September 2016. In total, 218 asymptomatic vines, 502 FD vines and 199 GTD vines were located with a centimetric precision GPS. UAV multispectral images were acquired with a MicaSense RedEdge® sensor and were processed to ultimately obtain surface reflectance mosaics at 0.10 m ground spatial resolution. In this study, the potentiality of 24 variables (5 spectral bands, 15 vegetation indices and 4 biophysical parameters) are tested. The vegetation indices are selected for their potentiality to detect abnormal vegetation behavior in relation to stress or diseases. Among the biophysical parameters selected, three are directly linked to the leaf pigments content (chlorophyll, carotenoid and anthocyanin). The first step consisted in evaluating the performance of the 24 variables to separate symptomatic vine vegetation (FD or/and GTD) from asymptomatic vine vegetation using the performance indicators from the Receiver Operator Characteristic (ROC) Curve method (i.e., Area Under Curve or AUC, sensibility and specificity). The second step consisted in mapping the symptomatic vines (FD and/or GTD) at the scale of the field using the optimal threshold resulting from the ROC curve. Ultimately, the error between the level of infection predicted by the selected variables (proportion of symptomatic pixels by vine) and observed in the field (proportion of symptomatic leaves by vine) is calculated. The same methodology is applied to the three levels of analysis: by vineyard, by cultivar (Gamay, Fer Servadou) and by berry color (all red cultivars). At the vineyard and cultivar levels, the best variables selected varies. The AUC of the best vegetation indices and biophysical parameters varies from 0.84 to 0.95 for Case 1 and 0.74 to 0.90 for Case 2. At the berry color level, no variable is efficient in discriminating FD vines from GTD ones (Case 2). For Case 1, the best vegetation indices and biophysical parameter are Red Green Index (RGI)/ Green-Red Vegetation Index (GRVI) (based on the green and red spectral bands) and Car (linked to carotenoid content). These variables are more effective in mapping vines with a level of infection greater than 50%. However, at the scale of the field, we observe misclassified pixels linked to the presence of mixed pixels (shade, bare soil, inter-row vegetation and vine vegetation) and other factors of abnormal coloration (e.g., apoplectic vines).

Analyzing the feasibility of a space-borne sensor (SPOT-6) to estimate the height of submerged aquatic vegetation (SAV) in inland waters

Remote sensing based approaches have been widely used over the years to monitor and manage submerged aquatic vegetation (SAV) or aquatic macrophytes mainly by mapping their spatial distribution and at the most, modeling SAV biomass. Remote sensing based studies to map SAV heights are rare because of the complexities in modeling water column optical proprieties. SAV height is a proxy for biomass and can be used to estimate plant volume when combined with percent cover. The objective of this study was to explore the feasibility of a satellite sensor to estimate the SAV height distribution in an inland reservoir. Also to test different radiative transfer theory based bio-optical models for estimating SAV heights using SPOT-6 data. The satellite-based multispectral data have rarely been used and SPOT-6 data, to the best of our knowledge, have never been used to estimate SAV heights in inland water bodies. In addition to depth and hydroacoustic data, in situ hyperspectral radiance and irradiance were measured at different depths to compute remote sensing reflectance (Rrs) and the attenuation coefficients (Kd and KLu). Two models, Palandro et al. (2008) and Dierssen et al. (2003), were used to derive bottom reflectance from both in situ and atmospherically corrected SPOT-6 Rrs. Bottom reflectance-based vegetation indices (green-red index, slope index, and simple ratio) were used to estimate SAV heights. Validation was performed using echosounder acquired hydroacoustic data. In situ model calibration produced an R2 of 0.7, however, the validation showed a systematic underestimation of SAV heights and high Root Mean Square Error (RMSE); indicating that there is a greater sensitivity in in situ models to localized variations in water column optical properties. The model based on SPOT-6 data presented higher accuracy, with R2 of 0.54 and RMSE of 0.29 m (NRMSE = 15%). Although the models showed a decreased sensitivity for SAVs at depths greater than 5 m with a height of 1.5 m, the finding nonetheless is significant because it proves that re-calibration of existing bottom reflectance models with more field data can enhance the accuracy to be able to periodically map SAV heights and biomass in inland waters. Although the initial results presented in this study are encouraging, further calibration of the model is required across different species, seasons, sites, and turbidity regime in order to test its application potential.

Retrieval of absorption coefficients for a drinking water source using a green–red band quasianalytical algorithm

This study proposed a green–red band quasianalytical algorithm, QAA-GRI, and evaluates its performance using an in situ dataset from Lake Qiandaohu, a drinking water source, in China. First, by shifting the reference wavelength from 555 to 510 nm, a green–red index (GRI) can be calculated from remote sensing reflectance at 510, 560, and 620 nm, and the index was then used to retrieve the total absorption coefficients at the reference band, a ( 510 ) . Second, a semianalytical model based on a ( 510 ) and the GRI was deduced to establish the QAA-GRI, replacing the empirical model in quasianalytical algorithm version 5 (QAA-v5). The QAA-GRI was applied to retrieve absorption coefficients from an in situ dataset of Lake Qiandaohu, and the QAA-GRI’s performance was compared with that of QAA-v5 and another red–green QAA-based approach (QAA-RGR). The results demonstrate that, for this dataset, the QAA-GRI exhibited better performance (R2 = 0.81, mean absolute percentage error, MAPE = 15.7 % ), which indicated a clear improvement in the accuracy of absorption coefficient retrieval, compared with QAA-v5 (R2 = 0.56, MAPE = 21.2 % ) and QAA-RGR (R2 = 0.67, MAPE = 22.6 % ). In addition, to illustrate the QAA-GRI’s assumptions and its applicability, the QAA-GRI was also applied to an in situ dataset from Taihu Lake, a highly turbid and eutrophic water source. As predicted, when applied to Taihu Lake, the QAA-GRI did not perform as well as it did when applied to Lake Qiandaohu because of the former’s extremely high turbidity, which can cause greater uncertainty with regard to backscattering coefficients. This study suggests that the QAA-GRI is better suited to the retrieval of absorption coefficients from drinking water resources. Our algorithm will also have potential applications to satellite data from the Medium Resolution Imaging Spectrometer or Ocean and Land Color Instrument.

Directional laminated thermally modified bamboo: Physical, mechanical, and fire properties

Laminated bamboo with radial (LBR) and tangential (LBT) layered structures was manufactured using heat-treated moso bamboo and phenol-formaldehyde adhesive. The physical, mechanical, and fire-related properties were determined. The results showed that layer structure and heat treatment had an impact on the properties of laminated bamboo. LBR showed good mechanical properties, though heat treatment compromised its integrity somewhat. Heat treatment decreased the lightness and incre6/28ased the green-red index, blue-yellow index, saturation, and total color difference. The samples exhibited changes in two HRR peaks during the combustion process, corresponding to two main release stages for smoke production. Heat-treatment improved the heat rate release (HRR), total heat release (THR), and the effective heat of combustion (EHC) properties, but also they decreased the smoke performances, resulting in higher total suspended particulate (TSP), specific extinction area (SEA), CO, and CO2 yield. LBR is suggested to be manufactured for possible use as a structural engineering material.

Modeling and predicting of the color changes of wood surface during CO2 laser modification

Abstract To adopt a greener approach, a novel thermal treatment for wood was proposed. Poplar wood surface was treated by CO2 laser and the surface color changes were evaluated by CIELAB color space. The treated and untreated surface were scanned by Epson scanner to measure lightness difference (ΔL*), red-green index difference (Δa*) and yellow-blue index difference (Δb*), then the total color difference (ΔE*) was calculated. The laser energy load on wood surface caused characteristic changes in the chemical component, which were determined by means of Fourier infrared spectrometer (FTIR). Response surface methodology (RSM) was used for modelling and to establish a relationship between color changes and laser modification parameters. The results showed that the feed speed, sweep width and laser power had significant effects on color changes of wood surface. The ΔE* increased with the increasing of laser power, however it decreased with increasing of feed speed and sweep width, because of the amount of heat transferring decreased with the increasing of feed speed and sweep width. The results of FTIR revealed chemical structure in the wood components, which is one of the reasons to the color changes of the wood surfaces. The established quadratic mathematical model applied to describe the relationship between color changes and laser modification parameters had a good prediction. It will be useful for selecting appropriate modification parameters to achieve desired color changes.

Evaluation of ground-level and space-borne sensor as tools in monitoring nitrogen nutrition status in immature and mature oil palm

ABSTRACTMonitoring nitrogen (N) in oil palm is crucial for the production sustainability. The objective of this study is to examine the capability of visible (Vis), near infrared (NIR) and a combination of Vis and NIR (Vis + NIR) spectral indices acquired from different sensors for predicting foliar N content of different palm age groups. The N treatments varied from 0 to 2 kg per palm, subjected according to immature, young mature and prime mature classes. The Vis + NIR indices from the ground level-sensor that is green + red + NIR (G + R + NIR) was the best index for predicting N for immature palms (R2 = 0.91), while Vis indices blue + red (B + R) and Green Red Index from the space-borne sensor were significantly useful for N assessment of young and prime mature palms (R2 = 0.70 and 0.50), respectively. The application of vegetation indices for monitoring N status of oil palm is beneficial to examine extensive plantation areas.

Genetic and nongenetic factors associated with milk color in dairy cows

Milk color is one of the sensory properties that can influence consumer choice of one product over another and it influences the quality of processed dairy products. This study aims to quantify the cow-level genetic and nongenetic factors associated with bovine milk color traits. A total of 136,807 spectra from Irish commercial and research herds (with multiple breeds and crosses) were used. Milk lightness (Lˆ*), red-green index (aˆ*) and yellow-blue index (bˆ*) were predicted for individual milk samples using only the mid-infrared spectrum of the milk sample. Factors associated with milk color were breed, stage of lactation, parity, milking-time, udder health status, pasture grazing, and seasonal calving. (Co)variance components for Lˆ*,aˆ*, and bˆ* were estimated using random regressions on the additive genetic and within-lactation permanent environmental effects. Greater bˆ* value (i.e., more yellow color) was evident in milk from Jersey cows. Milk Lˆ* increased consistently with stage of lactation, whereas aˆ* increased until mid lactation to subsequently plateau. Milk bˆ* deteriorated until 31 to 60 DIM, but then improved thereafter until the end of lactation. Relative to multiparous cows, milk yielded by primiparae was, on average, lighter (i.e., greater Lˆ*), more red (i.e., greater aˆ*), and less yellow (i.e., lower bˆ*). Milk from the morning milk session had lower Lˆ*,aˆ*, and bˆ* Heritability estimates (±SE) for milk color varied between 0.15 ± 0.02 (30 DIM) and 0.46 ± 0.02 (210 DIM) for Lˆ*, between 0.09 ± 0.01 (30 DIM) and 0.15 ± 0.02 (305 DIM) for aˆ*, and between 0.18 ± 0.02 (21 DIM) and 0.56 ± 0.03 (305 DIM) for bˆ* For all the 3 milk color features, the within-trait genetic correlations approached unity as the time intervals compared shortened and were generally <0.40 between the peripheries of the lactation. Strong positive genetic correlations existed between bˆ* value and milk fat concentration, ranging from 0.82 ± 0.19 at 5 DIM to 0.96 ± 0.01 at 305 DIM and confirming the observed phenotypic correlation (0.64, SE = 0.01). Results of the present study suggest that breeding strategies for the enhancement of milk color traits could be implemented for dairy cattle populations. Such strategies, coupled with the knowledge of milk color traits variation due to nongenetic factors, may represent a tool for the dairy processors to reduce, if not eliminate, the use of artificial pigments during milk manufacturing.

A semianalytical MERIS green‐red band algorithm for identifying phytoplankton bloom types in the East China Sea

AbstractA new bio‐optical algorithm based on the green and red bands of the Medium Resolution Imaging Spectrometer (MERIS) is developed to differentiate the harmful algal blooms of Prorocentrum donghaiense Lu (P. donghaiense) from diatom blooms in the East China Sea (ECS). Specifically, a novel green‐red index (GRI), actually an indicator for a(510) of bloom waters, is retrieved from a semianalytical bio‐optical model based on the green and red bands of phytoplankton‐absorption and backscattering spectra. In addition, a MERIS‐based diatom index (DIMERIS) is derived by adjusting a Moderate Resolution Imaging Spectroradiometer (MODIS) diatom index algorithm to the MERIS bands. Finally, bloom types are effectively differentiated in the feature spaces of the green‐red index and DIMERIS. Compared with three previous MERIS‐based quasi‐analytical algorithm (QAA) algorithms and three existing classification methods, the proposed GRI and classification method have the best discrimination performance when using the MERIS data. Further validations of the algorithm by using several MERIS image series and near‐concurrent in situ observations indicate that our algorithm yields the best classification accuracy and thus can be used to reliably detect and classify P. donghaiense and diatom blooms in the ECS. This is the first time that the MERIS data have been used to identify bloom types in the ECS. Our algorithm can also be used for the successor of the MERIS, the Ocean and Land Color Instrument, which will aid the long‐term observation of species succession in the ECS.