低湿玉米籽粒的射频加热模拟与试验

为了准确预测射频加热过程低湿（含水率13.0%～20.0%）玉米籽粒的温度分布变化,该研究结合玉米籽粒的多组分结构特征、热物理特性及介电特性的异质性,建立了玉米籽粒的三维二组分物理几何模型和射频加热数学模型,并利用验证后的模型研究不同姿态和含水率玉米籽粒的射频选择性加热。结果表明：射频加热过程中平放玉米籽粒温度的模拟值与试验值最大相对误差仅为3.47%,玉米籽粒中胚的温度高于胚乳,该模型能很好地预测籽粒内部的选择性加热现象。射频加热过程直立玉米籽粒的几何效应最强,显著提高了胚的电场强度和功率密度,导致其优先加热程度最大,其次是斜放和侧立玉米籽粒的,平放玉米籽粒中胚的优先加热程度最小。射频加热过程含水率为13.0%的玉米籽粒中胚与胚乳的温差逐渐增大,而含水率为16.5%和20.0%的玉米籽粒中胚与胚乳的温差先增大后减小;当玉米籽粒被加热至55 ℃时,含水率为16.5%的玉米籽粒中胚的优先加热程度最大,其次是含水率为13.0%玉米籽粒的,含水率为20.0%的玉米籽粒中胚的优先加热程度最小。研究结果揭示了玉米籽粒的姿态和含水率对其射频选择性加热的影响规律,可为射频加热技术应用于低湿玉米籽粒的热处理过程提供有益借鉴。     

Sequential extraction and single-step cold-acid extraction: A feasibility study for use with freshwater-canal sediments

This investigation examines metal release from freshwater sediment using sequential extraction and single-step cold-acid leaching. The concentrations of Cd, Cr, Cu, Fe, Ni, Pb and Zn released using a standard 3-step sequential extraction (Rauret et al., 1999) are compared to those released using a 0.5 M HCl; leach. The results show that the three sediments behave in very different ways when subject to the same leaching experiments: the cold-acid extraction appears to remove higher relative concentrations of metals from the iron-rich sediment than from the other two sediments. Cold-acid extraction appears to be more effective at removing metals from sediments with crystalline iron oxides than the “reducible” step of the sequential extraction. The results show that a single-step acid leach can be just as effective as sequential extractions at removing metals from sediment and are a great deal less time-consuming.     

Mapping to inform conservation: A case study of changes in semi-natural habitats and their connectivity over 70 years

Intensification of human activities has caused drastic losses in semi-natural habitats, resulting as well in declining connectivity between remaining fragments. Successful future restoration should therefore increase both habitat area and connectivity. The first steps in a framework for doing so are addressed here, which involve the mapping of past habitat change. We present a method which is unique in: the large area covered (2500 km²), the high resolution of the data (25 × 25 m), the long period assessed (70 years), and a system for translation of land use maps into Broad Habitat Types using soil surveys.We digitised land use maps from the 1930s for the county of Dorset in southern England. The resulting map was compared to the UK Land Cover Map of 2000. For our example area, land use shifted dramatically to more intensive agriculture: 97% of all semi-natural grasslands were converted into agriculturally-improved grassland or arable land as were large proportions of the heathlands and rough grasslands (?57%). The other important driver of change was afforestation (+25%). The larger habitat areas became fragmented, with average fragment size of different habitats falling by 31–94%. Furthermore, the connectivity between fragments dropped drastically, by up to 98%.Analyses such as those presented here not only quantify the scale and pattern of habitat loss, but are important to inform land-use planning to restore biodiversity by both increasing the available habitat and facilitating dispersal among habitat fragments. We discuss the possible steps for such a framework.     

Reduction of persistent organic pollutants in fishmeal: a feasibility study

The dioxin, dioxin-like polychlorinated biphenyl (DL-PCB), fat, and dry matter partitioning during fishmeal production have been studied in pilot scale. Most of the dry matter and lipid content in the fishmeal could be ascribed to the press cake intermediate product. Dioxins and DL-PCBs are fat-soluble compounds, and the process partitioning is reflected by the fat partitioning data. Enzyme and heat treatment of the press cake and stickwater concentrate did not improve fat separation. Soybean oil extraction of the press cake reduced the dioxin and DL-PCB content by 97%. Less exchange of fatty acids was observed (56-72%). Combined with fat separation of the stickwater concentrate, the applied process conditions were able to give a fishmeal decontamination rate higher than hexane and isopropanol extraction of the fishmeal. Quantification of fat content based on chloroform/methanol extraction was found to be the best protocol to estimate fat partitioning and decontamination effects. The oil extraction process requires further optimization, but has several advantages compared to organic solvent extraction. These include easy implementation in an existing fishmeal processing line, use of a safe and nonflammable extraction medium, and expected lower investment and operation costs. A new integrated fishmeal and fish oil production and decontamination process line is proposed.     

Geographical classification of honey samples by near-infrared spectroscopy: a feasibility study

The potential of near-infrared (NIR) spectroscopy to determine the geographical origin of honey samples was evaluated. In total, 167 unfiltered honey samples (88 Irish, 54 Mexican, and 25 Spanish) and 125 filtered honey samples (25 Irish, 25 Argentinean, 50 Czech, and 25 Hungarian) were collected. Spectra were recorded in transflectance mode. Following preliminary examination by principal component analysis (PCA), modeling methods applied to the spectral data set were partial least-squares (PLS) regression and soft independent modeling of class analogy (SIMCA); various pretreatments were investigated. For unfiltered honey, best SIMCA models gave correct classification rates of 95.5, 94.4, and 96% for the Irish, Mexican, and Spanish samples, respectively; PLS2 discriminant analysis produced a 100% correct classification for each of these honey classes. In the case of filtered honey, best SIMCA models produced correct classification rates of 91.7, 100, 100, and 96% for the Argentinean, Czech, Hungarian, and Irish samples, respectively, using the standard normal variate (SNV) data pretreatment. PLS2 discriminant analysis produced 96, 100, 100, and 100% correct classifications for the Argentinean, Czech, Hungarian, and Irish honey samples, respectively, using a second-derivative data pretreatment. Overall, while both SIMCA and PLS gave encouraging results, better correct classification rates were found using PLS regression.     

Colorimetric sensor arrays for the analysis of beers: a feasibility study

Eighteen commercial beers have been analyzed in both liquid and gas phases using colorimetric sensor arrays made from selected chemically responsive dyes printed on a hydrophobic membrane. Digital imaging of the dye array before and after exposure to the complex analytes in either the liquid phase or the head-gas provides a color change profile as a unique fingerprint for the specific analyte. The digital data libraries generated were analyzed using statistical and chemometric methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). In either liquid- or gas-phase experiments, facile identification of specific beers was achieved using comparison of the color change profiles; using HCA statistical analysis the error rate of identification was <3%. Differentiation between even very similar beers proved to be straightforward. In addition, differentiation of pristine beer from the effects of watering or decarbonation proved to be possible. These results suggest that colorimetric sensor arrays may prove to be useful for quality assurance/quality control applications of beers and perhaps other beverages.     

Assessing disease risk at the wildlife–livestock interface: A study of Sierra Nevada bighorn sheep

Despite evidence that domestic sheep diseases threaten the persistence of bighorn sheep populations, the economic consequences of restricting domestic sheep grazing has polarized the debate, with some arguing that disease risk posed by domestic sheep has been exaggerated and grazing restrictions should be eased. We constructed a model to assess how different management strategies (grazing allotment closures, grazing time reductions, and reduced probability of stray domestic sheep) affect the risk of respiratory disease transmission from domestic sheep to endangered Sierra Nevada bighorn sheep, and to predict population-level impacts of an outbreak. Even when management strategies reduced risk of interspecies contact to less than 2% per year, our model predicted a 50% probability of a catastrophic respiratory disease outbreak during the next 10 bighorn sheep generations. If an outbreak occurs in the near future, the model predicts that the smallest Sierra Nevada bighorn sheep population would have a 33% probability of quasi-extinction. To eliminate all risk of contact and potential disease transmission, domestic sheep cannot be grazed on allotments that overlap with areas utilized by Sierra Nevada bighorn sheep. Where wildlife and domestic animal populations share limited habitat, and there is documented evidence of a substantial disease threat and extinction risk, stakeholders must recognize that the only way to eliminate contact and risk of disease transmission is to give priority to one species or the other. If conservation is the priority, difficult decisions will need to be made to balance trade-offs between economic livelihoods and species conservation.     

Authentication of organic feed by near-infrared spectroscopy combined with chemometrics: a feasibility study

Organic products tend to retail at a higher price than their conventional counterparts, which makes them susceptible to fraud. In this study we evaluate the application of near-infrared spectroscopy (NIRS) as a rapid, cost-effective method to verify the organic identity of feed for laying hens. For this purpose a total of 36 organic and 60 conventional feed samples from The Netherlands were measured by NIRS. A binary classification model (organic vs conventional feed) was developed using partial least squares discriminant analysis. Models were developed using five different data preprocessing techniques, which were externally validated by a stratified random resampling strategy using 1000 realizations. Spectral regions related to the protein and fat content were among the most important ones for the classification model. The models based on data preprocessed using direct orthogonal signal correction (DOSC), standard normal variate (SNV), and first and second derivatives provided the most successful results in terms of median sensitivity (0.91 in external validation) and median specificity (1.00 for external validation of SNV models and 0.94 for DOSC and first and second derivative models). A previously developed model, which was based on fatty acid fingerprinting of the same set of feed samples, provided a higher sensitivity (1.00). This shows that the NIRS-based approach provides a rapid and low-cost screening tool, whereas the fatty acid fingerprinting model can be used for further confirmation of the organic identity of feed samples for laying hens. These methods provide additional assurance to the administrative controls currently conducted in the organic feed sector.     

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.     

Determination of nitrate in forages by using selective ion electrode: collaborative study

Each of 10 collaborating laboratories analyzed 4 blind duplicate pairs of forage samples for nitrate, by using a potentiometric method. Two forage controls and a 100 000 mg KNO3/L standard were also provided. Nitrate was extracted into an aqueous Al2(SO4)3 solution containing 70 mg KNO3/L and quantitated with a nitrate-selective electrode. Standards were prepared using extracting solution as diluent. Nitrate concentrations in forage samples ranged from less than 0.50 to 4.35% KNO3. Repeatability coefficients of variation (CVo) ranged from 1.74 to 3.61%, and reproducibility coefficients of variation (CVx) ranged from 6.92 to 7.66%. Mean recovery of a 0.55% KNO3 spike was 94.5%. The method has been adopted official first action.     

Mapping soil erodibility in southeast China at 250 m resolution: Using environmental variables and random forest regression with limited samples

Soil erodibility (K factor) mapping has been accomplished mainly by soil map-linked or geo-statistical interpolation. However, the resulting maps usually have coarse spatial resolution at a regional scale. The objectives of this study were a) to map the K factors using a set of environmental variables and random forest (RF) model, and b) to identify the important environmental variables in the predictive mapping on a regional scale. We collected 101 surface soil samples across southeast China in the summer of 2019. For each sample, we measured the particle size distribution and organic matter content, and calculated the K factors using the nomograph equation. The hyperparameters of RF were optimized through 5-fold cross validation (m_try = 2, n_tree = 500, p = 63), and a digital map with 250 m resolution was generated for the K factor. The lower and upper limits of a 90% prediction interval were also produced for uncertainty analysis. It was found that the important environmental variables for the K factor prediction were relief, climate, land surface temperature and vegetation indexes. Since the existing K factor map has an average polygonal area of 6.8 km², our approach dramatically improves the spatial resolution of the K factor to 0.0625 km². The new method captures more distinct differences in spatial details, and the spatial distribution of the K factor derived from RF prediction followed a similar pattern with kriging interpolation. This suggests the presented approach in this study is effective for mapping the K factor with limited sampling data.     

Estimating the annual runoff frequency distribution based on climatic conditions and catchment characteristics: A case study across China

Estimation of the annual runoff frequency distribution is an essential basis for water resource management. This study proposes a framework for estimating the annual runoff frequency distribution across 252 catchments in China based on climatic conditions and catchment characteristics from 1956 to 2000. The Budyko land-specific parameter n, which intergrates influences other than the mean climate conditions, is firstly estimated based on easily ascertainable catchment characteristics without the requirements of having long-term runoff observations. Second, the annual runoff statistical parameters, namely, the mean value and standard deviation (STD), are derived based on the Budyko rainfall-runoff model with the central moment method. Finally, the annual runoff on any recurrence interval is obtained by the Pearson-III frequency function. Results show that the parameter n can be estimated from the catchment average slope, longitude, and climatic seasonality index. The estimated statistical parameters of annual runoff have acceptable agreement with observed values (mean value: R² ∼0.94, STD: R² ∼0.91, and both relative errors <10%). In addition, estimated annual runoff at each catchment for typical wet and dry years (25% and 75% ranked percentiles) coincides well with observed values, with R² of 0.92–0.93 and relative errors less than 10%. This result indicates the robustness of this framework for estimating the annual runoff frequency distribution, which provides a simple and effective tool for ungauged or poorly gauged catchments.     

Nutrient limitation of alpine plants: Implications from leaf N : P stoichiometry and leaf δ15N

Nitrogen (N) deposition can affect grassland ecosystems by altering biomass production, plant species composition and abundance. Therefore, a better understanding of the response of dominant plant species to N input is a prerequisite for accurate prediction of future changes and interactions within plant communities. We evaluated the response of seven dominant plant species on the Tibetan Plateau to N input at two levels: individual species and plant functional group. This was achieved by assessing leaf N : P stoichiometry, leaf δ¹⁵N and biomass production for the plant functional groups. Seven dominant plant species—three legumes, two forbs, one grass, one sedge—were analyzed for N, P, and δ¹⁵N 2 years after fertilization with one of the three N forms: NO$ _3^- $ , NH$ _4^+ $ , or NH₄NO₃ at four application rates (0, 7.5, 30, and 150 kg N ha^–1 y^–1). On the basis of biomass production and leaf N : P ratios, we concluded that grasses were limited by available N or co‐limited by available P. Unlike for grasses, leaf N : P and biomass production were not suitable indicators of N limitation for legumes and forbs in alpine meadows. The poor performance of legumes under high N fertilization was mainly due to strong competition with grasses. The total above‐ground biomass was not increased by N fertilization. However, species composition shifted to more productive grasses. A significant negative correlation between leaf N : P and leaf δ¹⁵N indicated that the two forbs Gentiana straminea and Saussurea superba switched from N deficiency to P limitation (e.g., N excess) due to N fertilization. These findings imply that alpine meadows will be more dominated by grasses under increased atmospheric N deposition.     

Triacylglycerol analysis for the quantification of cocoa butter equivalents (CBE) in chocolate: feasibility study and validation

A new European legislation (2000/36/CE) has allowed the use of vegetable fats other than cocoa butter (CB) in chocolate up to a maximum value of 5% in the product. The vegetable fats used in chocolate are designated as cocoa butter replacements and are called cocoa butter equivalents (CBE). The feasibility of CBE quantification in chocolate using triacylglycerol (TAG) profiles was conducted by analyzing 55 samples of CBs and 31 samples of CBEs using a liquid chromatograph equipped with an evaporative light scattering detector (HPLC-ELSD). Statistical evaluation of the data obtained has been performed, and a simulation study has been carried out to assess the viability to use this method for quantifying the amount of CBE in real mixtures and in chocolates. The TAGs POP, POS, PLS, and the ratios POP/PLS, POS/PLP (P, palmityl; O, oleyl; S, stearyl; L, linoleyl) are particularly significant to discriminate between CB and CBE. Analysis of 50 mixtures between 5 different CBEs and 10 different CBs at 2 different concentration levels is presented. The data are visualized and interpreted. A mathematical model has been developed to assess the amount of CBE in real mixtures. This predictive model has been successfully applied and validated on dark chocolates including authorized CBE. The results are affected by +/-2.1% absolute average error. In particular, estimations between 10 and 20% of CBE show a very good match. On the other hand, values equal to or smaller than 5% show a larger prediction error (detection limit of the method). For the main purpose of this method (i.e., quantification of CBE at 5% max in chocolate, which represents about 15% of the total fat) this model shows very good results. For milk chocolate, the mathematical model can also be used if TAG are integrated from partition number (PN) 46 to 54. Consequently, the model proposed provides sufficient information to verify the real application of the European legislation.     

Conservation justice in metropolitan Cape Town: A study at the Macassar Dunes Conservation Area

Conservation justice, a concept analogous to environmental justice, suggests that local communities are entitled to receive fair treatment and meaningful involvement in the development and implementation of conservation policy. In this study, of an urban conservation project in Cape Town, South Africa, we contribute to the ongoing conversation about the importance of community-based conservation approaches. Conservationists must work to plan and implement projects in ways that are not only acceptable to stakeholders, but inspire local community involvement in achieving conservation goals. Given its location in the impoverished Cape Flats region of metropolitan Cape Town and its unique ecological and conservation value, the Macassar Dunes Conservation Area warrants a conservation justice approach. We conducted semi-structured interviews with members of interested and affected communities, then analyzed stakeholder perspectives on biodiversity protection, fencing, and informal housing. The results suggest that despite disparity among groups in needs and perspectives, conservation projects have potential to deliver tangible benefits to all stakeholder groups. A belief in conservation is universal across stakeholder lines, but contrasting needs and perspectives of the studied groups lead to conflicting views on important issues of implementation. An understanding of different stakeholder groups’ specific needs and interests is therefore essential for successful implementation of sustainable urban conservation projects.     

A case study in conservation politics: California's coastline initiative

The people of the State of California (USA) have voted to put coastline development under strict State control; control had previously been vested in local communities, in so far as it had existed at all. The newly-established policy represents a major break with tradition, as government authority over zoning and other development control has previously always been vested in the local community. It also represents a major break with the American tradition of unguided growth and development, for scenic and recreational values were considered more important by the majority of voters. Analysis of voting patterns shows that the strongest support was found among urbanites without much coastal access, while the strongest opposition was found in rural coastal counties (which stand to lose money) and rural mountain counties (where developers fear the mountains may be regulated next).