Factors affecting forestland owners' allocation of non-forested land to pine plantation for bioenergy in Virginia

Studies have shown that woody bioenergy can have potential economic, social, and environmental benefits. One of the ways to meet the growing biomass demand for woody bioenergy is by allocating currently non-forested land for growing feedstocks such as pine. Towards this end, we conducted a survey on 900 randomly selected private forestland owners in Virginia and asked what proportion of their non-forested land they would allocate for loblolly pine at given bid prices. We then used recursive partitioning based Tobit regression to analyze data. Our results suggest that the experience of having supplied wood for chip-n-saw mills in the past five years, large land holding, prior experience with state/federal financial/technical support programs, among other factors, lead to smaller proportion of non-forested land being allocated for pine. However, a higher price offer, stronger preference for producing non-timber forest products such as evergreen boughs and grapevine, and lesser dependence on working the land for annual income lead to larger proportion of non-forested land being allocate for pine. Our results could assist policy makers in developing and improving land use and energy policies, certification programs, and extension and outreach services. Our contribution also includes the use of threshold analyses to delineate tipping points in variables associated with different response rates and showing the different effect of variables in terms of how they affect the supply of biomass and the supply of land for bioenergy purposes.     

Prediction of zonal and total discharges in smooth straight prismatic compound channels using regression modeling

Experimental results are presented concerning the zonal and total discharge distribution and characteristics in a compound channel cross-section comprising one rectangular main channel and two symmetrical floodplains. The discharges in the main channel, floodplains, and total compound channel are found to be highly correlated to several dimensionless parameters defined using the compound channel cross-section geometry. Multi-variable regression analysis was utilized for developing predictive models that can estimate the main channel, floodplains and total discharges as a function of four different dimensionless parameters. The developed models to predict the zonal and total discharges in compound channels are found to be highly significant according to several major statistics including the model standard error, coefficient of determination (R²), and F-statistic. The developed multi-variable regression-based models are also tested for validity using available experimental data. Several statistical tests applicable to the analysis of residuals have indicated the effectiveness of the developed predictive models.     

Esterification of Free Fatty Acids in <Emphasis Type="Italic">Zanthoxylum bungeanum</Emphasis> Seed Oil for Biodiesel Production by Stannic Chloride

In this study, SnCl₄ was chosen as a solid catalyst for esterification of free fatty acids (FFA) in Zanthoxylum bungeanum seed oil (ZSO). A central composite rotatable design was used to investigate the effect of the methanol-to-oil molar ratio, catalyst amount and reaction time on the SnCl₄-catalyzed esterification of FFA. The methanol-to-oil molar ratio and reaction time clearly affected the conversion efficiency of FFA in the test ranges. Response surface methodology was used to optimize the conditions for SnCl₄-catalyzed esterification. A quadratic polynomial equation was obtained for conversion efficiency of FFA by multiple regression analysis and verification experiments confirmed the validity of the predicted model. Under the optimum conditions, the conversion efficiency of FFA in vegetable oil reached above 96 %. This study demonstrates the effectiveness of SnCl₄ as an acid catalyst for the reduction of high FFA content in vegetable oils to a low level by one-step esterification.     

基于CENTRIST的植物叶片识别研究与实现

针对传统植物识别方法工作任务量大,效率低下,难以保证数据客观性的问题,将CENTRIST视觉特征描述符应用于植物叶片的自动识别,设计出一个基于植物叶片图像的在线自动识别系统,对叶片图像进行预处理并提取其CEN-TRIST特征,使用最近邻分类器进行分类,计算并查询网络数据库中与之最匹配的图像,能够快速识别常见的32种植物叶片,平均正确识别率达到了90%以上。系统的后台使用PHP语言实现,所有叶片图像的信息存储于网络服务器的MySQL数据库中。实验结果表明,该系统对叶片识别具有非常好的效果,而且易于实现,也方便数据扩充和用户使用。     

High hydrostatic pressure assisted degradation of patulin in fruit and vegetable juice blends

The degradation of patulin introduced into different juices then treated with high hydrostatic pressure (HHP) was evaluated. A model juice prepared from apple and spinach (AS) was studied along with commercially available apple-based beverages; Pineapple:Apple:Mint (PAM), Apple:Carrot:Beet:Lemon:Ginger (CAB) and Romaine:Celery:Cucumber:Apple:Spinach:Kale, Parsley:lemon (GJ). The extent of patulin degradation was found to be dependent on applied pressure and processing time (degradation rates ranged from 0.04 to 0.19 ppb/s). The extent of patulin degradation could also be significantly (P < 0.05) correlated with the sulfhydryl group concentration of the juice with ascorbic acid and nitrite being less significant. HHP treatment of 600 MPa for 300 s at 11 °C resulted in a 62 ppb decrease in patulin introduced into GJ juice which also contained the highest level of thiols (97 μM). The thiol concentration of the other juices ranged between 39 and 69 μM with a corresponding decrease in patulin of 43–49 ppb following the same HHP treatment. The study has illustrated that HHP can be applied as a risk management tool to control patulin in apple based beverages although the extent of mycotoxin degradation is dependent on processing conditions and composition of the juice.     

Renewable-based generation expansion under a green certificate market

Quota obligations represent a policy instrument to reduce carbon emissions and incentivize renewable-based electricity generation. This support scheme places an obligation on generating companies to comply with a quota of renewable-based production. Eligible renewable units receive one certificate for each MWh, while fossil-based generating companies must buy certificates to comply with the requirement. This paper proposes a family of generation expansion models that include both an electricity and a certificate market to investigate to which degree a given quota obligation and non-compliance penalty incentivize the capacity expansion of renewable-based generation. Two market players are considered, namely, a renewable-based generating company with null operating cost and a weather-dependent capacity factor; and a fossil-based generating company with a fixed capacity and known fuel cost function. First, a complementarity model that determines the optimal capacity of the renewable-based producer considering a perfectly competitive market is proposed. Next, market players are assumed to compete in quantities à la Cournot to maximize their profits, being the generation expansion model formulated as a mathematical problem with equilibrium constraints. The relevance of properly setting the non-compliance penalty for each level of competition to comply with a given quota obligation is quantified and discussed using an stylized example.     

A new solar based multigeneration system with hot and cold thermal storages and hydrogen production

A multigeneration system based on solar thermal energy associated with hot and cold thermal storage is designed and analyzed energetically and exergetically. The system produces electricity, a heating effect, a cooling effect, hydrogen, and dry sawdust biomass as outputs by means of organic Rankine cycles, a heat pump, two absorption chillers, an electrolyser, and a belt dryer. The intermittent behavior of the renewable energy source is addressed through the incorporation of hot and cold thermal storage systems to operate an organic Rankine cycle and provide cooling at night. The performance assessment indicates that the overall (day and night) energy and exergy efficiencies are 20.7% and 13.7%, respectively. The majority of the total exergy destruction is attributable to the sawdust belt dryer, at about 64.0%.     

Two Mychonastes isolated from freshwater bodies are novel potential feedstocks for biodiesel production

Microalgae have been considered as ideal feedstocks for biodiesel production but the potential application is still under investigations. Here, eight kinds of microalgae were identified from water samples based on the morphologic and phylogenetic analyses. Among these eight microalgae, two Mychonastes S4 and S15 exhibited relative faster growth rate in the early culture stage and the highest contents of lipids. The two Mychonastes also showed higher C18:1 contents than the two Chlorella which were traditionally considered to be potential species for biodiesel production. As one kind of less researched microalgae, this study suggests Mychonastes should be a potential feedstock for biodiesel production. The application of the microalgal biodiesel still have some limiting factors, however, it is promising based on better lipid extraction technology and more relevant studies.     

A Multiplex PCR Assay for the Rapid and Sensitive Detection of Methicillin‐Resistant Staphylococcus aureus and Simultaneous Discrimination of Staphylococcus aureus from Coagulase‐Negative Staphylococci

Abstract: Methicillin‐resistant Staphylococcus aureus (MRSA) is a global health concern, which had been detected in food and food production animals. Conventional testing for detection of MRSA takes 3 to 5 d to yield complete information of the organism and its antibiotic sensitivity pattern. So, a rapid method is needed to diagnose and treat the MRSA infections. The present study focused on the development of a multiplex PCR assay for the rapid and sensitive detection of MRSA. The assay simultaneously detected 4 genes, namely, 16S rRNA of the Staphylococcus genus, femA of S. aureus, mecA that encodes methicillin resistance, and one internal control. It was rapid and yielded results within 4 h. The analytical sensitivity and specificity of the multiplex PCR assay was evaluated by comparing it with the conventional method. The analytical sensitivity of the multiplex PCR assay at the DNA level was 10 ng DNA. The analytical specificity was evaluated with 10 reference staphylococci strains and was 100%. The diagnostic evaluation of MRSA was carried out using 360 foodborne staphylococci isolates, and showed 99.1% of specificity, 96.4% of sensitivity, 97.5% of positive predictive value, and 97.3% of negative predictive value compared to the conventional method. The inclusion of an internal control in the multiplex PCR assay is important to exclude false‐negative cases. This test can be used as an effective diagnostic and surveillance tool to investigate the spread and emergence of MRSA.     

Explicit solution for normal depth of parabolic section of open channels

To obtain the normal depth of parabolic section of open channels, multiple known parameters were incorporated into a comprehensive one by transforming basic equations, and a concept of the non-dimensional normal depth was introduced. The normal depth equations were simplified into a non-dimensional iterative formula that was proved to have a high velocity of convergence. By analyzing the comprehensive parameter and dimensionless normal depth under condition of usually adopted sizes of parabolic channels and through establishing their relationship, the iterative initial value of normal depth was obtained. The normal depth of parabolic channels was acquired by substituting the initial value into the iteration formula. The error analysis was made and a case study was provided as an application example. The case study showed that the iteration formula was very simple, convenient and precise for determining the normal depth of parabolic channels with the maximum relative error of normal depth being less than 0.34% when the ratio of width to depth was between 0.2 and 20.