A Mathematical Model for Fungal Development in Heterogeneous Environments
印度碗状红菇——一个中国新纪录种(英文)

热带作物学报2021, 42(9): 2542 2548 Chinese Journal of Tropical Crops收稿日期 2021-02-23;修回日期 2021-03-20基金项目 国家自然科学基金项目(No. 31770657,No. 31570544,No. 31900016)。
作者简介 陈 彬(1990—),男,博士研究生,研究方向:森林微生物资源遗传多样性。
*通信作者(Corresponding author ):梁俊峰(Liang Junfeng ),E-mail :*******************。
Russula indocatillus , a New Record Species in ChinaCHEN Bin 1, 2, SONG Jie 1, WANG Qian 1, LIANG Junfeng 1*1. Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, Guangdong 510520, China;2. Nanjing For-estry University, Nanjing, Jiangsu 210037, ChinaAbstract: Russula indocatillus was reported as new species to China. A detailed morphological description, illustrations and phylogeny are provided, and comparisons with related species are made. It is morphologically characterized by a brownish orange to yellow ochre pileus center with butter yellow to pale yellow margin, white to cream spore print, subglobose to broadly ellipsoid to ellipsoid basidiospores with bluntly conical to subcylindrical isolated warts, always one-celled pileocystidia, and short, slender, furcated and septated terminal elements of pileipellis. The combination of detailed morphological features and phylogenetic analysis based on ITS-nrLSU-RPB2 sequences dataset indicated that the species belonged to Russula subg. Heterphyllidia sect. Ingratae . Keywords: Russulaceae; new record species; phylogeny; taxonomy DOI 10.3969/j.issn.1000-2561.2021.09.014印度碗状红菇——一个中国新纪录种陈 彬1,2,宋 杰1,王 倩1,梁俊峰1*1. 中国林业科学研究院热带林业研究所,广东广州 510520;2. 南京林业大学,江苏南京 210037摘 要:本研究报道一个中国红菇属新记录种——印度碗状红菇(Russula indocatillus )。
食品专业英语课件

Part 2 食品科技英语的阅读
Lesson 1 WHO Strategy on Food Safety
Summary WHO has been actively participating in the
development of principles and recommendations for the safety assessment of GM foods derived from genetically modified organisms(GMO). The results developed in the course of various expert consultations from the basis for guidelines on national levels and are presently being incorporated into internationally recognized standards. 对于由转基因生物生产的食品转基因食品,WHO一直以来积 极致力于制订其安全评价的原则和建议。不同专家基于本 译文 国的技术水平而商讨的结果是各国制定标准的指导性依据, 而且这些结论正逐渐成为公认的权威标准。
3. What can you learn from Paragraph 3 ?
A. Most developing countries are not willing to be responsible for the consequence of using the new technology. B. Most developing countries are willing to be responsible for the consequence of using the new technology. C. Most developed countries are not willing to be responsible for the consequence of using the new technology. D. Most developed countries are willing to be responsible for the consequence of using the new technology.
数字农业英语作文

数字农业英语作文Title: The Transformation of Digital AgricultureWith the advancement of technology, the agriculture industry has undergone a significant transformation in recent years. Digital agriculture, also known as precision agriculture, has emerged as a revolutionary approach to farming that leverages modern technologies to optimize production efficiency, reduce environmental impact, and ensure food security. This essay explores the key aspects and benefits of digital agriculture.One of the main components of digital agriculture is the use of precision farming techniques. This includes the adoption of drones, satellite imagery, and GPS technology to monitor and manage crop growth. With these tools, farmers can precisely analyze soil conditions, crop health, andirrigation needs, allowing for targeted interventions and optimized resource utilization.Moreover, data analytics plays a crucial role in digital agriculture. By collecting and analyzing vast amounts of data on weather patterns, soil quality, and crop performance, farmers can make informed decisions to improve productivity and profitability. Machine learning algorithms enable predictive modeling, helping farmers anticipate challenges and optimize farming practices.Another key aspect of digital agriculture is the development of smart farming equipment. From automated tractors to robotic harvesters, these technologies streamline farm operations and reduce manual labor. By integrating IoT sensors and cloud computing, farmers can remotely monitor and control equipment, leading to increased efficiency and reduced costs.Furthermore, digital agriculture promotes sustainable farming practices. By adopting precision irrigation systems and variable rate fertilization, farmers can minimize water usage and chemical inputs, reducing environmental impact and promoting biodiversity. This not only benefits the ecosystem but also enhances the long-term viability of farming operations.In addition to improving farm productivity, digital agriculture also plays a vital role in ensuring food security. By facilitating real-time monitoring of crop health and yield predictions, farmers can better plan and manage their harvests, reducing food waste and improving food distribution systems. This is particularly crucial in addressing globalfood challenges and ensuring access to nutritious food forall.Overall, digital agriculture represents a paradigm shiftin the way we approach farming. By harnessing the power oftechnology and data-driven insights, farmers can enhance sustainability, productivity, and resilience in the face of changing climates and market dynamics. As we continue to innovate and adopt new technologies, digital agriculture will play an increasingly vital role in shaping the future of food production.。
基于模糊数学法的辣木籽杂粮面包配方优化及其品质分析

吕俊丽,任志龙,云月英,等. 基于模糊数学法的辣木籽杂粮面包配方优化及其品质分析[J]. 食品工业科技,2023,44(23):167−174. doi: 10.13386/j.issn1002-0306.2023010105LÜ Junli, REN Zhilong, YUN Yueying, et al. Formulation Optimization and Quality Analysis of Moringa Seed Multigrain Bread Based on Fuzzy Mathematics[J]. Science and Technology of Food Industry, 2023, 44(23): 167−174. (in Chinese with English abstract). doi:10.13386/j.issn1002-0306.2023010105· 工艺技术 ·基于模糊数学法的辣木籽杂粮面包配方优化及其品质分析吕俊丽1, *,任志龙2,云月英1,郭 慧1(1.内蒙古科技大学生命科学与技术学院,内蒙古包头 014010;2.包头轻工职业技术学院食品生物与检测系,内蒙古包头 014035)摘 要:为了满足人们对营养食品的需求,本研究以面包为载体,运用模糊数学感官评价法,以感官评分为依据,通过单因素和正交试验对辣木籽杂粮面包配方进行优化,在此基础上,分析了辣木籽杂粮面包的理化特性和抑菌特性。
结果显示:辣木籽杂粮面包的因素影响顺序为:辣木籽添加量>薏米添加量>红豆添加量>红薯泥的添加量,辣木籽杂粮面包最佳配方为:牛奶34%,黄油7.5%,全蛋液40%,酵母添加量为0.8%,白糖添加量5.1%,辣木籽的添加量为2.6%,红薯泥的添加量为2.1%,红豆的添加量为1.6%,薏米的添加量为2.1%。
此配方下面包的模糊数学感官评分最高(86.35分),此时面包味道浓郁,松软适口,过氧化值、酸价、菌落总数均符合国家标准,蛋白质含量比普通面包高5.6 g/100 g 。
2023-2024学年上海市静安区高三上学期期末教学质量调研考试英语试题

2023-2024学年上海市静安区高三上学期期末教学质量调研考试英语试题Directions: After reading the passage below, fill in the blanks to make the passages coherent and grammatically correct. For the blanks with a given word, fill in each blank with the proper form of the given word; for the other blanks, use one word that best fits each blank.Japan’s robot revolution in senior careJapan’s artificial intelligence expertise is transforming the elder care industry, with 1 (specialize) robotic care accomplishing more than just taking pressure off the critical shortage of caregivers. Senior care facilities across Japan are testing out such new robots 2 deliver a collection of social and physical health care and the government-backed initiative has been met with positive reviews by elderly residents.The rapidly graying population 3 (eye) by the government as a potential market for medical technology now. Disappointing government predictions show that by 2025, Japan's first baby boomers will have turned 75 and about 7 million people are likely to suffer from some form of dementia (痴呆). The nation won't be able to avoid a dementia crisis 4 an additional 380,000 senior care workers.The long-standing shortage of professional care workers has encouraged the Japanese government 5 (simplify) procedures for foreign caregivers to be trained and certified. The current Technical Intern Training Program between Vietnam, the Philippines, and Indonesia, under 6 Economic Partnership Agreement, was extended to include nursing care as well as agriculture, fishery, and construction sectors.7 the government made efforts to increase the numbers of senior care workers, the target number of foreign graduates has still fallen flat, with the national caregiver examination proving a major obstacle to pass. The success rate for foreign students was a merely 106 students last year, 8 has slightly improved to 216 students this year. Another depressing reality is that 19 to 38 percent of foreign nurses who pass the exam opt to leave the industry and return home, 9 (cite) tough work conditions and long hours. Given the challenges, this is 10 the government believes care robots will be able to step in.Directions: Complete the following passage by using the words in the box. Each word can only be used once. Note that there is one word more than you need.A. smoothingB. remainC. switchedD. likelihoodE. impactF. tipG. broadly H. headed I. booming J. positioning K. reliablySea-level rise predictionsA team of University of Idaho scientists is studying a fast-moving glacier in Alaska in hopes of developing better predictions on how quickly global sea levels will rise.Tim Bartholomaus, a professor in the Department of Geography and Geological Sciences, spent several weeks on Turner Glacier in Alaska’s southeastern 11 near Disenchantment Bay. The glacier is unique because, unlike other glaciers, it rises greatly every five to eight years.A surging glacier is defined, 12 , as one that starts flowing at least 10 times faster than normal. But the how and why of that glacial movement is poorly understood, although recent research suggests that global climate change increases the 13 of glacial surging.During Turner’s surges, the mass of ice and rock will increase its speed from roughly 3 feet a day to 65 feet per day.All of that is important because glaciers falling into the ocean are a major contributor to sea level rise, and current clima te change models don’t 14 account for these movements. For example, Greenland’s glaciers are one of the leading contributors to global sea-level rise. Since the early 2000s, Greenland 15 from not having any effect on world sea levels, to increasing sea level by about 1 millimeter per year. Half of that yearly increase is due to warmer average temperatures, which leads to more ice melting. The other half, however, is because glaciers in Greenland are, as a whole, moving faster and running into the ocean more frequently.Glacial movement has something to do with water running underneath the glacier. Glaciers are full of holes, and water runs through those holes. When the water pressure is high underneath a glacier, it starts to move, partly because it’s li fting the mass of ice and rock off the ground and partly because it’s 16 the underside of the glacier.But how exactly does that water move through the glacier, and how does the movement 17 the glacier’s speed? Those are the questions the scientists ho pe to answer.Bartholomaus, some graduate students and researchers from Boise State University, 18 onto the ice in August. They set up a base camp at the toe of the glacier and spent their days flying in on helicopters. They placed roughly 30 instruments, burying them deeply into the glacier and 19 them on rock outcroppings (露岩) alongside the glacier. This summer the team will return to get the instruments and replace batteries. Those instruments will 20 on and around the glacier until the glacier surge stops, providing researchers with before and after data.Investors probably expect that following the suggestions of stock analysts would make them better off than doing the exact opposite. _________, recent research by Nicola Gennaioli and his colleagues shows that the best way to gain excess return s would be to invest in the shares least favored by analysts. They compute that, during the last 35 years, investing in the 10 percent of U. S. stocks analysts were most _________ about would have yielded on average 3 percent a year._________, investing in the 10 percent of stocks analysts were most pessimistic about would have yielded a surprising 15 percent a year.Gennaioli and colleagues shed light on this _________ with the help of cognitive sciences and, in particular, using Kahneman and Tversky's concept of representativeness. Decision makers, according to this view, _________ the representative features of a group or a phenomenon. These are defined as the features that occur more frequently in that group than in a baseline reference group.After observing strong earnings growth—the explanation goes—analysts think that the firm may be the next Google. “Googles” are in fact more frequent among firms experiencing strong growth, which makes them _________. The problem is that “Googles” are very _________ in absolute terms. As a result, expectations become too optimistic, and future performance_________. A model of stock prices in which investor beliefs follow this logic can account both qualitatively and quantitatively for the beliefs of analysts and the dynamics (动态变化) of stock returns.In related work, the authors also show that the same model can _________ booms and busts in the volume of credit and interest rate spreads.These works are part of a research project aimed at taking insights from cognitive sciences and at__________them into economic models. Kahneman and Tversky's concept of “representativeness” lies at the heart of this effort. “In a classical example, we __________ to think of Irishmen as redheads because red hair is much more frequent among Irishmen than among the rest of the world,” Prof. Gennaioli says. “However, only 10 percent of Irishmen are redheads. In our work, we develop models of belief formation that show this logic and study the __________ of this important psychological force in different fields.”Representativeness helps describe __________ and behavior in different fields, not only in financial markets. One such field is the formation of stereotypes about social groups. In a recent experimental paper, Gennaioli and colleagues show that representativeness can explain self-confidence, and in particular the __________ of women to compete in traditionally male subjects, such as mathematics.A slight prevalence of __________ male math ability in the data is enough to make math ability un-representative for women, driving their under confidence in this particular subject.21.A.Consequently B.Furthermore C.Nevertheless D.Meanwhile22.A.curious B.controversial C.concerned D.optimistic23.A.In brief B.By contrast C.In addition D.Without doubt 24.A.engagement B.concentration C.puzzle D.definition25.A.memorize B.prioritize C.modernize D.fertilize26.A.representative B.argumentative C.executive D.sensitive27.A.harsh B.adaptable C.crucial D.rare28.A.cheers B.disappoints C.stabilizes D.improves29.A.account for B.count on C.suffer from D.hold up30.A.pouring B.admitting C.integrating D.tempting31.A.pretend B.afford C.offer D.tend32.A.effects B.delights C.intervals D.codes33.A.companions B.scales C.expectations D.findings34.A.necessity B.involvement C.perseverance D.reluctance35.A.equivalent B.exceptional C.mysterious D.distressing Montessori was born in Italy in 1870 with progressive parents, who frequently communicated with the country’s leading thinkers and scholars. This enlightened family environment provided Montessori with many advantages over other young girls of the time.Her mother’s support was vital for some impo rtant decisions, such as her enrolment in a technical school after her elementary education. Her parents’ support also proved to be essential for her decision to study medicine, a field that was dominated by men.Soon after graduating, in 1896, Montessori began work as a voluntary assistant in a clinic at the University of Rome, where she cared for children with learning difficulties. The rooms were bare, with just a few pieces of furniture. One day, she found that the children were enthusiastically playing with breadcrumbs (面包屑) that had dropped on the floor. It then occurred to her that the origin of some intellectual disabilities could be related with poverty. With the right learning materials, these and other young minds could be nurtured, Montessori concluded.The observation would lead Montessori to develop a new method of education that focused on providing optimal stimulation during the sensitive periods of childhood.At its centre was the principle that all the learning materials should be child-sized and designed to appeal to all the senses. In addition, each child should also be allowed to move and act freely, and use their creativity and problem-solving skills. Teachers took the role of guides, supporting the children without press or control.Mont essori opened her first Children’s House in 1907. When the Fascists (法西斯主义者) first came into power in Italy in 1922, they initially embraced her movement. But they soon came to oppose the emphasis on the children’s freedom of expression. Montessori’s value s had always been about human respect, and the rights of children and women, but the Fascists wanted to use her work and her fame.Things reached a breaking point when the Fascist tried to influence the schools’ educational content, and in 1934 Montessori and her son decided to leave Italy. She didn’t return to her homeland until 1947, and she continued to write about and develop her method until her death in 1952, at the age of 81.36. The primary reason for Montessori to develop a new educational method was ______.A.her family’s supportive influence on her educationB.her experience as a voluntary assistant in a clinicC.her observation of children playing with breadcrumbs happilyD.her decision to study medicine, a field dominated by men37. What was a central principle of Montessori’s educational method as described in the passage?A.Providing standardized, one-size-fits-all learning materials.B.Encouraging strict discipline and control over children’s actions.C.Focusing on rote memorization and competition.D.Creating a free and children-centered learning environment.38. Montessori decided to leave Italy in 1934 because .A.she wanted to explore other countries and culturesB.she wanted to avoid the Fascist’s influence on her workC.she was offered a better job in a different countryD.she wanted to retire and enjoy a peaceful life in another country39. Which of the following words can best describe Montessori in this passage?A.Observant and innovative. B.Traditional and emotional.C.Progressive and dependent. D.Open-minded and indifferent. Reducing the workweek to four days could have a climate benefit. In addition to improving the well-being of workers, cutting working hours may reduce carbon emissions. But those benefits would depend on a number of factors, experts emphasize, including how people choose to spend nonworking time.Commuting and travelTransportation is the biggest contributor to greenhouse emissions. A November 2021 survey of2,000 employees and 500 business leaders in the United Kingdom found that if all organizations introduced a four-day week, the reduced trips to work would decrease travel overall by more than 691 million miles a week.But the climate benefits of less commuting could be eliminated, experts said, if people choose to spend their extra time off traveling, particularly if they do so by car or plane.Energy usageShorter working hours could lead to reductions in energy usage, experts said. According to a 2006 paper, if the United States adopted European work standards, the country would consume about 20 percent less energy.Energy could also be conserved if fewer resources are needed to heat and cool large office buildings, reducing demands on electricity. For example, if an entire workplace shuts down on the fifth day, that would help lower consumption — less so if the office stays open to accommodate employees taking different days off.Lifestyle changesIt’s possible that fewer working hours may lead some people to have a larger carbon footprint, bu t experts say research suggests that most people are likely to shift toward more sustainable lifestyles.One theory is that people who work more and have less free time tend to do things in more carbon-intensive ways, such as choosing faster modes of transportation or buying prepared foods. Convenience is often carbon-intensive and people tend to choose convenience when they're time-stressed. Meanwhile, some research suggests that those who work less are more likely to engage in traditionally low-carbon activities, such as spending time with family or sleeping.“When we talk about the four-day workweek and the environment, we focus on the tangible, but actually, in a way, the biggest potential benefit here is in the intangible,” experts said.40. What is identified as the leading cause of greenhouse emissions according to the passage?A.The well-being of employees.B.The conservation of energy.C.Commuting and travel.D.The European work standard.41. What can be inferred from the underlined sentence “the biggest potential benefit here is in the intangible” in the last paragraph?A.People will have big potential in achieving intangible benefits while working.B.People are more likely to engage in carbon-intensive activities due to time constraints.C.People may shift toward more sustainable lifestyles and lower carbon footprints.D.People may travel more frequently by car or plane during their extra time off.42. The passage is mainly written to .A.highlight the importance of shortening working time in the context of well-beingB.provide an overview of transportation emissions worldwideC.analyze the impact of reduced working hours on mode of businessD.illustrate factors affecting the climate benefits of a shorter workweekThe cultivation of plants by ants is more widespread than previously realized, and has evolved on at least 15 separate occasions.There are more than 200 species of ant in the Americas that farm fungi (真菌) for food, but this trait evolved just once sometime between 45 million and 65 million years ago. Biologists regard the cultivation of fungi by ants as true agriculture appearing earlier than human agriculture because it meets four criteria: the ants plant the fungus, care for it, harvest it and depend on it for food.By contrast, while thousands of ant species are known to have a wide variety of interdependent relationships with plants, none were regarded as true agriculture. But in 2016, Guillaume Chomicki and Susanne Renner at the University of Munich, Germany, discovered that an ant in Fungi cultivates several plants in a way that meets the four criteria for true agriculture.The ants collect the seeds of the plants and place them in cracks in the bark of trees. As the plants grow, they form hollow structures called domain that the ants nest in. The ants defecate (排便) at designated absorptive places in these domain, providing nutrients for the plant. In return, as well as shelter, the plant provides food in the form of fruit juice.This discovery prompted Chomicki and others to review the literature on ant-plant relationships to see if there are other examples of plant cultivation that have been overlooked. “They have never really been looked at in the framework of agriculture,” says Chomicki, who is now at the University of Sheffield in the UK. “It’s definitely widespread.”The team identified 37 examples of tree-living ants that cultivate plants that grow on trees, known as epiphytes (附生植物). By looking at the family trees of the ant species, the team was able to determine on how many occasions plant cultivation evolved and roughly when. Fifteen is a conservative estimate, says Campbell. All the systems evolved relatively recently, around 1million to 3 million years ago, she says.Whether the 37 examples of plant cultivation identified by the team count as true agriculture depends on the definitions used. Not all of the species get food from the plants, but they do rely on them for shelter, which is crucial for ants living in trees, says Campbell. So the team thinks the definition of true agriculture should include shelter as well as food.43. According to biologists, why is ant-fungus cultivation considered as a form of true agriculture?A.Because it occurred earlier than human agriculture.B.Because it fulfills the standards typical of agricultural practices.C.Because it redefines the four criteria for true human agriculture.D.Because it is less common than previously thought.44. What motivated Chomicki and others to review the literature on ant-plant relationships?A.They determined on new family trees of the ant species.B.They overlooked some tree-living ants that provided nutrients for the plants.C.They never studied the ant-plant relationships within the context of agriculture.D.They never identified any an t species that engaged in cultivation of fungi.45. Which of the following statements is supported by the team's findings according to the passage?A.Ants’ cultivation of plants is limited to a few specific species.B.The cultivation of fungi by ants is considered the earliest form of agriculture.C.True agriculture in ants involves only food-related interactions with plants.D.Ants have independently cultivated plants on at least 15 distinct occasions.46. What is the passage mainly about?A.The evolution of ants in the plant kingdom.B.The widespread occurrence of ant-plant cultivation.C.The discovery of a new ant species engaging in agriculture.D.The contrast between ant agriculture and human agriculture.What is the likelihood of you having someone who looks just like you? Would it be a good thing? And if you did have one, would you want to meet them?Consider how often your facial features are used to identify you. Your passport, ID card and driving license all feature your face. 47 You may need your face to unlock your smartphone and possibly even need it to exclude you from being present at a crime scene.The word “doppelgänger” refers to a person who looks the same as you, essentially sharing your features; those that you thought were unique to you and your identity. Not identical twins, as a doppelgänger has no relation to you. The idea originated in German folklore. 48So, let's get real. What are the chances of you having one in the first place? There's said to be a one in 135 chance of an exact match for you existing anywhere in the world, so the chances are pretty low, despite folk wisdom promising you otherwise. And the chances of meeting? The mathematical certainty of finding this particular person is supposedly less than one in a trillion.That said, these statistics may be a good thing. Historically, having a double wasn't always a positive. Back in 1999, an innocent American man, indistinguishable from the real criminal, was sent to prison for robbery, where he stayed for 19 years. 49 . In a different case, a woman in New York was accused of trying to poison her doppelgänger with deadly cheesecake so that she could steal her identity!50 The fascination with doppelgängers may be rooted in historical beliefs that facial resemblance meant they were from the same family or had a common ancestor. It leads to the hope that one day you will meet your lookalike, creating the thrill of a potentially strange meeting. However, as these encounters can be both interesting and disturbing, we understand that after such an experience, you might not want to meet your doppelgänger again.passage in no more than 60 words. Use your own words as far as possible.Competitive CheerleadingOver the years, cheerleading has taken two primary forms: game-time cheerleading and competitive cheerleading. Game-time cheerleaders’ main goal is to entertain the crowd and lead them with team cheers, which should not be considered a sport. However, competitive cheerleading is more than a form of entertainment. It is really a competitive sport.Competitive cheerleading includes lots of physical activity. The majority of the teams require a certain level of tumbling (翻腾运动) ability. It’s a very common thing for gymnasts, so it’s easy for them to go into competitive cheerleading. Usually these cheerleaders integrate lots of their gymnastics experience including their jumps, tumbling, and overall energy. They also perform lifts and throws.Competitive cheerleading is also an activity that is governed by rules under which a winner can be declared. It is awarded points for technique, creativity and sharpness. Usually the more difficult the action is, the better the score is. That’s why cheerleaders are trying to experience great difficulty in their performance. Besides, there is also a strict rule of time. The whole performance has to be completed in less than three minutes and fifteen seconds, during which the cheerleaders are required to stay within a certain area. Any performance beyond the limit of time is invalid.Another reason for the fact that competitive cheerleading is one of the hardest sports is that it has more reported injuries. According to some research, competitive cheerleading is the number one cause of serious sports injuries to women. Generally, these injuries affect all areas of the body, including wrists, shoulders, ankles, head, and neck.There can be no doubt that competitive cheerleading is a sport with professional skills. It should be noted that it is a team sport and even the smallest mistake made by one teammate can bring the score of the entire team down. So without working together to achieve the goal, first place is out of reach. ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ________________________________________________________________________________ ___________________________________________________________________________52. 如果不好好准备,周五的演讲可能会变得一塌糊涂。
豆腐_豆浆_中屎肠球菌生长的温度预测模型

豆腐(豆浆)中屎肠球菌生长的温度预测模型李 博1 李里特1 辰巳英三2 李再贵1(11中国农业大学食品科学与营养工程学院,北京100083;21日本国农林水产省国际农林水产业研究中心)收稿日期:2002206207基金项目:中日国际合作项目作者简介:李 博,博士,副教授,主要从事食品安全和食品中微生物的研究。
摘 要 采用预测食品微生物学的方法研究了豆腐(豆浆)中主要腐败微生物屎肠球菌的生长规律,建立了屎肠球菌在豆浆培养基中的初级和二级预测模型,研究了0~55℃屎肠球菌的生长曲线。
结果表明,在适温阶段屎肠球菌的生长曲线呈典型的S 形,适合用G ompertz 模型拟合;当温度接近最低生长温度和最高生长温度时,适合用线性回归方程拟合。
屎肠球菌在豆浆中生长的温度模型符合Ratkowsky3式。
根据预测模型,屎肠球菌的最低生长温度为418℃,最高生长温度为5416℃,最适生长温度为41℃。
对模型进行了验证。
关键词 预测模型;屎肠球菌;豆腐;生长模型中图分类号 TS 20113;TS 21412 文章编号 100724333(2003)022******* 文献标识码 APredictive model for effect of temperature on the growth ofE.faecium in tofu (soymilk )Li Bo 1, Li Lite 1, Tatsumi Eizo 2, Li Zaigui 1(11College of Food Science &Nutritional Engineering ,China Agricultural University ,Beijing 100083,China ;21J apan International Research Center for Agricultural Sciences ,Ministry of Agriculutre ,Forestry and isheries )Abstract The growth characteristics of the major spoila ge bacteria in tofu - E.faecium was studie d by using themethod of pre dictive microbiology.And pre dictive models for the growth curves and the effects of temp erature on growth of microorganism were esta blishe d.Growth curves were fitte d by using the model of Logistic ,Gomp ertz and Monod functions ,and sp ecific growth rates derive d from the curve fitting were modele d.The exp eriment res ults were as follows :A study to build mathematical models that pre dict the growth of E.faecium in s oymilk (tofu )was carrie d out.Growth curves were obtaine d at 0-55℃.The Gomp ertz model were found to fit with repres entation of exp eri 2mental curves which are typical sigmoidal at 10-50℃.The Monod function were found to fit with the exp erimental curve at below 10℃or a bove 50℃.The variations of growth rate with temp erature were modele d.Data processing of the model has shown that the minimum growth temp erature for E.faecium is 418℃,the maximum growth temp erature is 5416℃and the optimal growth temp erature is 41℃.The validity of the pre dictive model was evaluate d under con 2trolle d la boratory conditions using s oymilk.K ey words pre dictive modeling ;Enterococcus faecium ;tofu ;growth model 豆腐是我国的传统食品。
Mathematical modeling of drying of pretreated

Mathematical modeling of drying of pretreated and untreated pumpkinT.Y.Tunde-Akintunde &G.O.OgunlakinRevised:13February 2011/Accepted:26April 2011#Association of Food Scientists &Technologists (India)2011Abstract In this study,drying characteristics of pretreated and untreated pumpkin were examined in a hot-air dryer at air temperatures within a range of 40–80°C and a constant air velocity of 1.5m/s.The drying was observed to be in the falling-rate drying period and thus liquid diffusion is the main mechanism of moisture movement from the internal regions to the product surface.The experimental drying data for the pumpkin fruits were used to fit Exponential,General exponential,Logarithmic,Page,Midilli-Kucuk and Parabolic model and the statistical validity of models tested were determined by non-linear regression analysis.The Parabolic model had the highest R 2and lowest χ2and RMSE values.This indicates that the Parabolic model is appropriate to describe the dehydration behavior for the pumpkin.Keywords Pumpkin fruits .Hot air drying .Effective diffusivity .Mathematical modellingNomenclature a Drying constant b Drying constant c Drying constant DR Drying rate (g water/g dry matter*h)k Drying constant,1/min M e Equilibrium moisture content(kg water/kg dry matter)M i Initial moisture content (kg water/kg dry matter)M R Dimensionless moisture ratioMR exp,i Experimental dimensionless moisture ratio MR pre,i Predicted dimensionless moisture ratio M t Moisture content at any time of drying (kg water/kg dry matter)M t +dtMoisture content at t +dt (kg water/kg dry matter)N Number of observationsn Drying constant,positive integer R 2Coefficient of determination t Time (min)W Amount of evaporated water (g)W 0Initial weight of sample (g)W 1Sample dry matter mass (g)z Number of constants χ2Reduced chi-squareIntroductionPumpkin (cucurbita mixta )is a fruit rich in Vitamin A,potassium,fiber and carbohydrates.It is a versatile fruit that can be used for either animal feed or for human consumption as a snack,or made into soups,pies and bread.The high moisture content of the fruit makes it susceptible to deterioration after harvest.The most common form of preservation being done locally is drying.It is a means of improving storability by increasing shelf-life of the food product.Dried products can be stored for months or even years without appreciable loss of nutrients.Drying also assist in reducing post harvest losses of fruits and vegetables especially which can be as high as 70%(Tunde-Akintunde and Akintunde 1996).Sun drying is the common method of drying in the tropical region.However the process is weather depen-T.Y .Tunde-Akintunde (*):G.O.Ogunlakin Department of Food Science and Engineering,Ladoke Akintola University of Technology,PMB 4000,Ogbomoso,Oyo State,Nigeria e-mail:toyositunde@J Food Sci TechnolDOI 10.1007/s13197-011-0392-2dent Also,the drying of food products with the use of sun-drying usually takes a long time thus resulting in products of low quality.There is a need for suitable alternatives in order to improve product quality.Hot air dryers give far more hygienic products and provide uniform and rapid drying which is more suitable for the food drying processes(Kingsly et al.2007a;Doymaz 2004a).Many types of hot-air dryers are being used for drying agricultural products.However the design of such driers for high-moisture foods constitutes a very complex problem owing to the characteristics of vegetable tissues.One of the most important factor that needs to be considered in the design of driers is the proper prediction of drying rate for shrinking particles and hence the appropriate drying time in the dryer needs to be investigated.This can be achieved by determination of the drying characteristics of the food material.Therefore the thin layer drying studies which normally form the basis of understanding the drying characteristics of food materials has to be carried out for each food material.Studies have been carried out on thin layer drying of some food materials(Gaston et al.2004), fruits(Doymaz2004a,c;Simal et al.2005),leaves and grasses(Demir et al.2004).Though there has been some literature on drying of pumpkin(Alibas2007;Doymaz2007b;Sacilik2007),the selection of appropriate model to describe the drying process for the variety common in the country and within the experimental conditions considered in this study is yet to be done.Thin layer drying models used in the analysis of drying characteristics are usually theoretical,semi-theoretical or purely empirical.A number of semi-theoretical drying models have been widely used by various researchers(Sharma and Prasad2004;Simal et al.2005;Sogi et al.2003;Togrul and Pehlivan2004).A number of pre-treatments can be applied depending on the food to be dried,its end use,and availability(Doymaz 2010).Pretreatment of food materials which includes; blanching,osmotic dehydration,soaking in ascorbic acid before or on drying have been investigated to prevent the loss of colour by inactivating enzymes and relaxing tissue structure.This improves the effect of drying by reducing the drying time and gives the eventual dried products of good nutritional quality(Kingsly et al.2007b;Doymaz 2010).Various commercially used pretreatments include potassium and sodium hydroxide,potassium meta bisul-phate,potassium carbonate,methyl and ethyl ester emul-sions,ascorbic and citric acids,(Kingsly et al.2007a,b; Doymaz2004a,b;El-Beltagy et al.2007).However non-chemical forms of pretreatment are generally preferred especially among small-scale processors in the tropics. Blanching as a pre-treatment is used to arrest some physiological processes before drying vegetables and fruits.It is a heat pre-treatment that inactivates the enzymes responsible for commercially unacceptable darkening and off-flavours.Blanching of fruits and vegetables is generally carried out by heating them with steam or hot water(Tembo et al.2008).However other forms of blanching i.e.oil-water blanching have been used by Akanbi et al.(2006)in a previous study for pretreating chilli.These forms of blanching were observed to have an effect on the drying rate and quality of the dried chili. However oil-water blanching pretreatments have not been studied for pumpkin.The aim of this study was:(a)to study the effect of the different blanching pre-treatments on the drying times and rate,and(b)to fit the experimental data to seven mathematical models available in the literature.Materials and methodsExperimental procedureFresh pumpkin fruit were purchased from Arada,a local market in Ogbomoso,Nigeria.The initial average moisture content of fresh pumpkin samples was deter-mined by oven drying method(AOAC1990),and it was found to be91.7%(wet basis)or10.90(g water/g dry matter).The samples were washed and peeled after which the seeds were removed.The pumpkin was then sliced into pieces of5mm×5mm dimensions.The blanching pre-treatments for inactivation of enzymes are as indicated below while untreated samples(UT)were used as the control.i)Samples submerged in boiling water for3minutes andcooling immediately in tap water-(WB)ii)Samples steamed over boiling water in a water bath (WBH14/F2,England)for3minutes and cooled immediately in tap water-(SB)iii)Samples dipped for3minutes in a homogenized mixture of oil and water of ratio1:20(v/v)with0.1g of butylated hydroxyl anisole(BHA)heated to95°C-(O/W B)In all the pretreatments the excess water was removed by blotting the pretreated pumpkin samples with tissue paper.The moisture contents after pretreatment were12.69(g water/g dry matter)for water and oil-water blanching and11.5(g water/g dry matter)for steam blanching.Drying procedureThe drying experiments of pumpkin samples were carried out in a hot-air dryer(Gallenkamp,UK)having three tiers of trays. Perforated trays having an area of approximately0.2m2wereJ Food Sci Technolplaced on each tier and the trays were filled with a single layer of the pumpkin samples.The air passes from the heating unit and is heated to the desired temperature and channeled to the drying chamber.The hot air passes from across the surface and perforated bottom of the drying material and the direction of air flow was parallel to the samples.The samples utilised for each experimental condition weighed 200±2g.Drying of the pumpkin was carried out at drying temperatures of 40to 800C with 20°C increment,and a constant air velocity of 1.5m/s for all circumstances.The dryer was adjusted to be selected temperature for about half an hour before the start of experiment to achieve the steady state conditions.Weight loss of samples was measured at various time intervals,ranging from 30min at the beginning of the drying to 120min during the last stages of the drying process by means of a digital balance (PH Mettler)with an accuracy of ±0.01g.The samples were taken out of the dryer and weighed during each of the time intervals.Drying was stopped when constant weight was reached with three consecutive readings.The experiments were repeated twice and the average of the moisture ratio at each value was used for drawing the drying curves.Model nameModelReferencesExponential modelMR ¼exp Àkt ðÞEl-Beltagy et al.(2007)Generalized exponential model MR ¼Aexp Àkt ðÞShittu and Raji (2008)Logarithmic model MR ¼aexp ðÀkt Þþc Akpinar and Bicer (2008)(Page ’s model)MR ¼exp Àkt n ðÞSingh et al.(2008)Midilli –Kucuk model MR ¼aexp Àkt n ðÞþbt Midilli and Kucuk (2003)Parabolic modelMR ¼a þbt þct 2Sharma and Prasad (2004),Doymaz (2010)Table 1Mathematical models fitted to pretreated pumpkin drying curves100200300400Drying Time (min)WB SBO/W B UT0.10.20.30.40.50.60.70.80.910100200300Drying Time (min)M o i s t u r e R a t i o00.10.20.30.40.50.60.70.80.91M o i s t u r e R a t i oWB SB O/W B UT00.10.20.30.40.50.60.70.80.91M o i s t u r e R a t i o100200300Drying Time (min)WB SB O/W B UTbacFig.1Drying curve of pump-kin slices dried at (a )40,(b )60and (c )80°C (WB-water blanched,SB-steam blanched,O/W B-oil water blanched,UT-untreated).Each observation is a mean of two replicate experiments (n =2)J Food Sci TechnolMathematical modelingThe moisture content at any time of drying (kg water/kg dry matter),M t was calculated as follows:M t ¼W o ÀW ðÞÀW 1W 1ð1ÞWhere W 0is the initial weight of sample,W is the amount of evaporated water and W 1is the sample dry matter mass.The reduction of moisture ratio with drying time was used to analyse the experimental drying data.The moisture ratio,M R,was calculated as follows:M R ¼M t ÀM eM i ÀM e¼exp ÀKt ðÞð2ÞWhere M t ,M i and M e are moisture content at any time of drying (kg water/kg dry matter),initial moisture content (kg water/kg dry matter)and equilibrium moisture content (kg water/kg dry matter),respectively.The equilibrium moisture contents (EMCs)were deter-mined by drying until no further change in weight wasobserved for the pumpkin samples in each treatment and drying condition (Hii et al.2009)The drying constant,K ,is determined by plotting experimental drying data for each pretreatment and drying temperature in terms of Ln M R against time (t)where M R is moisture ratio.The slope,k,is obtained from the straight line graphs above.The drying rate for the pumpkin slices was calculated as follows:DR ¼M t þdt ÀM tdtð3ÞWhere DR is drying rate,M t +dt is moisture content at t +dt (kg water/kg dry matter),t is time (min).The moisture ratio curves obtained were fitted with six semi-theoretical thin layer-drying models,Exponential,Generalized exponential,Page,Logarithmic,Midilli -Kucuk and Parabolic models (Table 1)in order to describe the drying characteristics of pretreated pumpkin.These linear forms of these models were fitted in the experimental data using regression technique.To evaluate the models,a nonlinear regression procedure was per-formed for six models using SPSS (Statistical Package for00.020.040.060.080.10.12Drying Time (h)D r y i n g r a t e (g w a t e r /g D M .h )WB SB O/W B UT00.020.040.060.080.10.120.140.160.180246Drying time (h)D r y i n g r a t e (g w a t e r /g D M .h )WB SB O/W B UT00.010.020.030.040.050.060246Drying Time (h)D r y i n g R a t e (g w a t e r /g D M .h )WB SB O/W B UTbacFig.2Drying rate curve of pretreated pumpkin dried at (a )40,(b )60and (c )80°C (WB-water blanched,SB-steam blanched,O/W B-oil water blanched,UT-untreated).Each observation is a mean of two replicate experiments (n =2)J Food Sci Technolsocial scientists)11.5.1software package.The correlation coefficient (R 2)was one of the primary criteria to select the best equation to account for variation in the drying curves of dried samples.In addition to R 2,other statistical parameters such as reduced mean square of the deviation (χ2)and root mean square error (RMSE)were used to determine the quality of the fit.The higher the value of R 2and the lower the values of χ2and RMSE were chosen as the criteria for goodness of fit.(Togrul and Pehlivan 2002;Demir et al.2004;Doymaz 2004b ;Goyal et al.2006).The above parameters can be calculated as follows:#2¼PN i ¼1MR ðexp ;i ÞÀMR ðpred ;i ÞÀÁN Àz2ð4ÞRMSE ¼1N XN i ¼1MR pred ;i ÀMR exp ;i ÀÁ2"#12ð5ÞWhere MR exp,i and MR pre,i are experimental and pre-dicted dimensionless moisture ratios,respectively;N is number of observations;z is number of constantsResults and discussion Drying characteristicsThe characteristics drying curves showing the changes in moisture ratio of pretreated pumpkin with time at drying temperatures of 40,60and 80°C are given in Fig.1.Figure 2show the changes in drying rate as a function of drying time at the same temperatures.It is apparent that moisture ratio decreases continuously with drying time.According to the results in Fig.1,the drying air temperature and pre-treatments had a significant effect on the moisture ratio of the pumpkin samples as expected.This is in agreement with the observations of Doymaz (2010)for apple slices.The figures show that the drying time decreased with increase in drying air temperature.Similar results were also reported for food products by earlierTable 2Drying constant (K)values for pretreatment methods and drying temperaturesDrying Temperature (°C)Pretreatment method Steam Blanching Water Blanching Oil-Water Blanching Untreated 400.45290.44580.42260.4029600.62230.61630.60150.5637800.78840.78710.78370.7803Model nameCoefficient of determination (R 2)Reducedchi-square (χ)Root mean square error (RMSE)40°CGeneralized Exponential Model 0.95180.0058240.071384Exponential Model 0.96550.0051960.062424Logarithmic Model 0.96840.0056210.059272Page Model0.973750.0032790.048397Midilli –Kucuk model 0.863980.0277520.109059Parabolic model 0.99630.0004730.0164460°CGeneralized Exponential Model 0.98740.0013820.035049Exponential Model 0.98820.0013460.032351Logarithmic Model 0.99420.0007850.022878Page Model0.980390.001110.028847Midilli –Kucuk model 0.818570.0145140.085189Parabolic model 0.99410.0004480.01672680°CGeneralized Exponential Model 0.95640.0038620.058588Exponential Model 0.96220.0038610.054796Logarithmic Model 0.97250.0107950.082138Page Model0.95950.0086160.080386Midilli –Kucuk model 0.937020.022370.105759Parabolic model0.98650.0032920.04685Table 3Curve fitting criteria forthe various mathematical models and parameters for pumpkin pre-treated with water blanching and dried at temperatures of 40,60and 80°CJ Food Sci TechnolModel nameCoefficient of determination (R 2)Reducedchi-square (χ)Root mean square error (RMSE)40°CGeneralized Exponential Model 0.95930.0048430.065095Exponential Model 0.96890.0042740.056615Logarithmic Model 0.968960.0050650.056262Page Model0.95990.0045870.057237Midilli –Kucuk model 0.818470.0342380.121134Parabolic model 0.99490.0006490.01925260°CGeneralized Exponential Model 0.987370.0013540.034688Exponential Model 0.98760.0014480.033563Logarithmic Model 0.990810.0008640.023994Page Model0.97490.0012870.031073Midilli –Kucuk model 0.982270.0169220.091982Parabolic model 0.99410.0005980.01933680°CGeneralized Exponential Model 0.94360.0054840.069818Exponential Model 0.951870.0108440.060609Logarithmic Model 0.958190.0052010.082325Page Model0.922370.0065670.070179Midilli –Kucuk model 0.955020.0210930.102696Parabolic model0.979590.0047230.058882Table 4Curve fitting criteria for the various mathematical models and parameters for pumpkin pre-treated with steam blanching and dried at temperatures of 40,60and 80°CModel nameCoefficient of determination (R 2)Reducedchi-square (χ)Root mean square error (RMSE)40°CGeneralized Exponential Model 0.94540.0067290.076734Exponential Model 0.96030.0059530.066819Logarithmic Model 0.961750.0069530.065922Page Model0.96450.0045960.057295Midilli –Kucuk model 0.838010.0328130.118587Parabolic model 0.99560.0008220.02167260°CGeneralized Exponential Model 0.976650.0017910.039903Exponential Model 0.982710.002020.039642Logarithmic Model 0.986950.0016620.033287Page Model0.974690.0012580.03072Midilli –Kucuk model 0.88840.0083740.064708Parabolic model 0.99280.0004530.01682280°CGeneralized Exponential Model 0.947850.0047940.065279Exponential Model 0.95540.00480.061101Logarithmic Model 0.96250.0120260.086696Page Model0.932230.0106440.089346Midilli –Kucuk model 0.94940.0200940.100234Parabolic model0.983570.0043540.053874Table 5Curve fitting criteria for the various mathematical models and parameters for pumpkin pre-treated with oil-water blanching and dried at temperatures of 40,60and 80°CJ Food Sci TechnolModel nameCoefficient of determination (R 2)Reducedchi-square (χ)Root mean square error (RMSE)40°CGeneralized Exponential Model 0.948760.0058960.071829Exponential Model 0.95850.0056790.065264Logarithmic Model 0.959110.0067350.06488Page Model0.94120.0064750.068007Midilli –Kucuk model 0.78980.0399250.130808Parabolic model 0.985950.0018690.03267860°CGeneralized Exponential Model 0.97350.0024360.046534Exponential Model 0.97490.0028840.047363Logarithmic Model 0.981070.0011850.028035Page Model0.95840.0021470.040127Midilli –Kucuk model 0.76690.0163070.090296Parabolic model 0.990390.0011790.0272280°CGeneralized Exponential Model 0.949980.0045840.063836Exponential Model 0.95720.0047680.060896Logarithmic Model 0.959850.0050460.057999Page Model0.920160.0077380.069542Midilli –Kucuk model 0.95070.0179590.09476Parabolic model0.97750.0042850.056692Table 6Curve fitting criteria for the various mathematical models and parameters for untreated pumpkin and dried at temper-atures of 40,60and 80°CDrying Time (h)M o i s t u r e R a t i oDrying Time (h)M o i s t u r e R a t i oDrying Time (h)M o i s t u r e R a t i obacFig.3Comparison of experi-mental and predicted moisture ratio values using Parabolic model for pretreated pumpkin dried at (a )40,(b )60and (c )80°C (WBE-water blanched experimental,SBE-steam blanched experimental,O/W BE-oil water blanchedexperimental,UTE-untreated experimental,WBP-waterblanched predicted,SBP-steam blanched predicted,O/W BP-oil water blanched predicted,UTP-untreated predicted).Each observation is a mean of two replicate experiments (n =2)J Food Sci Technolresearchers(Sacilik and Elicin2006;Lee and Kim2009; Kumar et al.2010).The drying time required to lower the moisture ratio of water blanched samples to0.034when using an air temperature of40°C(5h)was approximately twice that required at a drying air temperature of80°C (2.5h).This same trend occurred for both untreated and other pretreatment methods.The drying time required to reach moisture ratio of0.018for drying temperature of60°C for samples pretreated with steam blanching was3h while the corresponding values for water blanched,oil-water blanched and control samples were3.5,3.9and4h respectively.The difference in drying times of pre-treated samples with steam blanching was16.7%,30%and33.3%shorter than water blanched,oil-water blanched and control samples,re-spectively.Similar trends were observed at drying temper-atures of40and80°C.All the pretreated samples had higher drying curves than the untreated samples generally(Fig.1).This is an indication of the fact that various forms of blanching pretreatments increase the drying rate for pumpkin samples. This is similar to the observations of Goyal et al.(2008), Doymaz(2007a),Kingsly et al.(2007a),Doymaz(2004b) for apples,tomato,peach slices and mulberry fruits.The difference in drying is more pronounced at the initial stages of drying when the major quantity of water is evaporated while at the latter stages of drying the difference in the amount of water evaporated is not as pronounced as the early drying stages.The difference in the drying of the different pretreatments experienced in the initial stages becomes less pronounced with increase in drying temper-ature.This may be because at higher temperatures the driving force due to diffusion from the internal regions to the surface is higher thus overcoming hindrances to drying more effectively resulting in more uniform drying.The K values for pretreated samples were higher than that of untreated samples for all the drying temperatures(Table2). This confirms the fact that the various forms of blanching pretreatments increased the rate at which drying took place.Analysis of the drying rate curves(Fig.2)showed no constant-rate period indicating that drying occurred during the falling-rate period.Therefore,it can be considered a diffusion-controlled process in which the rate of moisture removal is limited by diffusion of moisture from inside to surface of the product.This is similar to the results reported for various agricultural products such Amasya red apples (Doymaz2010),peach(Kingsly et al.2007a),yam(Sobukola et al.2008),and tumeric(Singh et al.2010).Fitting of drying curveSPSS statistical software package for non-linear regression analysis was used to fit moisture ratio against drying time to determine the constants of the four selected drying models.The R2,χ2and RMSE used to determine the goodness of fit of the models are shown in Tables3,4,5 and6.The Parabolic model gave the highest R2value which varied from0.9963to0.9775for experimental conditions considered in this study.The values ofχ2and RMSE for the Parabolic model which varied from0.000448 to0.004723and0.01644to0.058882respectively were the lowest for all the models considered.From the tables,it is obvious that the Parabolic model therefore represents the drying characteristics of pretreated pumpkin(for individual drying runs)better than the other models(Generalized exponential,Exponential,Logarithmic,Page or Midilli–Kucuk)considered in this study.The comparison between experimental moisture ratios and predicted moisture ratios obtained from the Parabolic model at drying air temperature of40°C,60°C and80°C for pumpkin samples are shown in Fig.3.The suitability of the Parabolic model for describing the pumpkin drying behaviour is further shown by a good conformity between experimental and predicted moisture ratios as seen in Fig.3.This is similar to the observations of Doymaz(2010)for drying of red apple slices at55,65and75°C.ConclusionThe effect of temperature and pre-treatments on thin layer drying of pumpkin in a hot-air dryer was investigated. Increase in drying temperature from40to80°C decreased the drying time from5hours to4hours for all the samples considered.The pretreated samples dried faster than the untreated samples.Samples pretreated with steam blanch-ing had shorter drying times(hence higher drying rates) compared to water blanched,oil-water blanched and control samples The entire drying process occurred in falling rate period and constant rate period was not observed.The suitability of four thin-layer equations to describe the drying behaviour of pumpkin was investigated.The model that had the best fit with highest values of R2and lowest values ofχ2,MBE and RMSE was the Parabolic model. Thus this model was selected as being suitable to describe the pumpkin drying process for the experimental conditions considered.ReferencesAkanbi CT,Adeyemi RS,Ojo A(2006)Drying characteristics and sorption isotherm of tomato slices.J Food Eng73:141–146 Akpinar AK,Bicer Y(2008)Mathematical modelling of thin layer drying process of long green pepper in solar dryer and under open sun.Energy Conver Manag49:1367–1375Aliba I(2007)Microwave,air and combined microwave–air-drying parameters of pumpkin slices.LWT40:1445–1451J Food Sci TechnolAOAC(1990)Official methods of analysis,15th edn.Association of Official Analytical Chemists,ArlingtonDemir V,Gunhan T,Yagcioglu AK,Degirmencioglu A(2004) Mathematical modeling and the determination of some quality parameters of air-dried bay leaves.Biosys Eng88(3):325–335 Doymaz I(2004a)Drying kinetics of white mulberry.J Food Eng61(3):341–346Doymaz I(2004b)Pretreatment effect on sun drying of mulberry fruit (Morus alba L.).J Food Eng65(2):205–209Doymaz I(2004c)Convective air drying characteristics of thin layer carrots.J Food Eng61(3):359–364Doymaz I(2007a)Air-drying characteristics of tomatoes.J Food Eng 78:1291–1297Doymaz I(2007b)The kinetics of forced convective air-drying of pumpkin slices.J Food Eng79:243–248Doymaz I(2010)Effect of citric acid and blanching pre-treatments on drying and rehydration of Amasya red apples.Food Bioprod Proc 88(2–3):124–132El-Beltagy A,Gamea GR,Amer Essa AH(2007)Solar drying characteristics of strawberry.J Food Eng78:456–464Gaston AL,Abalone RM,Giner SA,Bruce DM(2004)Effect of modelling assumptions on the effective water diffusivity in wheat.Biosys Eng88(2):175–185Goyal RK,Kingsly ARP,Manikantan MR,Ilyas SM(2006)Thin layer drying kinetics of raw mango slices.Biosys Eng95(1):43–49 Goyal RK,Mujjeb O,Bhargava VK(2008)Mathematical modeling of thin layer drying kinetics of apple in tunnel dryer.Int J Food Eng 4(8):Article8Hii CL,Law CL,Cloke M,Suzannah S(2009)Thin layer drying kinetics of cocoa and dried product quality.Biosys Eng102:153–161 Kingsly RP,Goyal RK,Manikantan MR,Ilyas SM(2007a)Effects of pretreatments and drying air temperature on drying behaviour of peach slice.Int J Food Sci Technol42:65–69Kingsly ARP,Singh R,Goyal RK,Singh DB(2007b)Thin-layer drying behaviour of organically produced tomato.Am J Food Technol 2:71–78Kumar R,Jain S,Garg MK(2010)Drying behaviour of rapeseed under thin layer conditions.J Food Sci Technol47(3):335–338 Lee JH,Kim HJ(2009)Vacuum drying kinetics of Asian white radish (Raphanus sativus L.)slices.LWT-Food Sci Technol42:180–186Midilli A,Kucuk H(2003)Mathematical modeling of thin layer drying of pistachio by using solar energy.Energy Conver Manag 44(7):1111–1122Sacilik K(2007)Effect of drying methods on thin-layer drying characteristics of hull-less seed pumpkin(Cucurbita pepo L.).J Food Eng79:23–30Sacilik K,Elicin AK(2006)The thin layer drying characteristics of organic apple slices.J Food Eng73:281–289Sharma GP,Prasad S(2004)Effective moisture diffusivity of garlic cloves undergoing microwave convective drying.J Food Eng65(4):609–617Shittu TA,Raji AO(2008)Thin layer drying of African Breadfruit (Treculia africana)seeds:modeling and rehydration capacity.Food Bioprocess Technol:1–8.doi:10.1007/s11947-008-0161-zSimal S,Femenia A,Garau MC,Rossello C(2005)Use of exponential,page and diffusion models to simulate the drying kinetics of kiwi fruit.J Food Eng66(3):323–328Singh S,Sharma R,Bawa AS,Saxena DC(2008)Drying and rehydration characteristics of water chestnut(Trapa natans)as a function of drying air temperature.J Food Eng87:213–221Singh G,Arora S,Kumar S(2010)Effect of mechanical drying air conditions on quality of turmeric powder.J Food Sci Technol47(3):347–350Sobukola OP,Dairo OU,Odunewu A V(2008)Convective hot air drying of blanched yam slices.Int J Food Sci Technol43:1233–1238 Sogi DS,Shivhare US,Garg SK,Bawa SA(2003)Water sorption isotherms and drying characteristics of tomato seeds.Biosys Eng 84(3):297–301Tembo L,Chiteka ZA,Kadzere I,Akinnifesi FK,Tagwira F(2008) Blanching and drying period affect moisture loss and vitamin C content in Ziziphus mauritiana(Lamk.).Afric J Biotech7:3100–3106Togrul IT,Pehlivan D(2002)Mathematical modeling of solar drying of apricots in thin layers.J Food Eng55:209–216Togrul IT,Pehlivan D(2004)Modeling of thin layer drying kinetics of some fruits under open air sun drying process.J Food Eng65(3):413–425Tunde-Akintunde TY,Akintunde BO(1996)Post-harvest losses of food crops:sources and solutions.Proceedings of the Annual Conference of the Nigerian Society of Agricultural Engineers, Ile-Ife,Nigeria from November19–22,1996.V ol18:258–261J Food Sci Technol。
北美数学建模PROBLEMA、B、C、D题翻译-6页

PROBLEM A:The Ultimate Brownie Pan终极布朗尼潘When baking in a rectangular pan heat is concentrated in the 4 corners and the product gets overcooked at the corners (and to a lesser extent at the edges). In a round pan the heat is distributed evenly over the entire outer edge and the product is not overcooked at the edges. However, since most ovens are rectangular in shape using round pans is not efficient with respect to using the space in an oven. 当在一个矩形的锅热烘烤时,热量被浓缩在4个角落中,并在拐角处(以及在较小程度上在边缘处):产品会过头。
在一个圆形盘中,热量被均匀地分布在整个外缘,并且在边缘处的产品不过头。
然而,因为大多数烤炉使用圆形平底锅,而形状是矩形的,这样是效率不高的相对于使用在烘箱中的空间。
Develop a model to show the distribution of heat across the outer edge of a pan for pans of different shapes -rectangular to circular and other shapes in between. 开发一个模型来显示横跨平底锅平底锅不同形状-矩形之间的圆形和其他形状的外边缘的热量分布。
Assume1. A width to length ratio of W/L for the oven which is rectangular in shape.2. Each pan must have an area of A.3. Initially two racks in the oven, evenly spaced.1宽度与长度之比(W / L)的是矩形的烘箱。
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The internal substrate is also considered to be motile and the motility ability of the fungus to translocate nutrients around the mycelial netverified by Olsson (see [9,10]), translocation can be reasonable modelled
(iii) an internal substrate concentration, these components *=D dt The spatial movement
asin
a =
Aa+a2s
in - w,
asex Dssxhx =
at
at
Dsl,ASin a2sin f(a, +
- f(a,
systems
systems). Therefore, they provide an experimentally and observationally accessible model system for investigating the dynamic origins of phenotype patterns in such systems. However, their utility in this role has been limited on two counts: first, by the tendency to treat them as purely additive assemblages of effectively discrete, individual lengths of hyphae (hyphal growth units) that duplicate at regular intervals. Second, all previous models have considered fungi grown in perfectly uniform conditions. This is certainly not the situation fungi encounter when growing in any natural environment, and a consideration of the effects of heterogeneity is essential for any true understanding of their form and function. That such environments by Ritz cause dramatic [I], Rayner changes to their growth characteristics has been shown experimentally the geometric setting discussed below, by Park [4]. [2,3], and in
We would like to thank A. D. M. Rayner for his significant supported by EPSRC Grants GR/J35511 and GR/K92641, interest.
contribution to this ongoing project. This work was
and analyzed a model for In a series of papers, Davidson et al. (see [5-B]) h ave formulated the macroscopic development of mycelia growing in homogeneous environmental conditions. The model considers the mycelium in its most abstracted form, as a continuous self-fueling system which uses energy gained from nutrients and water in the environment to produce biomass which in turn assimilates more energy. The model therefore, does not require the consideration of the
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PII: SO893-9659(98)00102-S
active transport we now discuss. Essentially, nutrients can pass though the hyphal wall by three main mechanisms-passive diffusion, facilitated diffusion, and active transport. The last involves the action of membranebound enzymes that use energy derived from the hydrolysis of ATP to pump out protons, so generating a proton gradient across which nutrients can be transferred against a concentration gradient. It can reasonably be assumed that active transport of nutrients is the major mechanism by which fungi gains energy from their environment and the main loss of nutrients to the exterior occurs simply in response to a gradient in the concentration from inside to outside (see [2, pp. 42441). The other mechanisms stated above may play secondary roles in cross membrane transport, but in this model we shall assume their effects to be negligible. Unlike Edelstein and Segel [ll] who have also developed a model for fungal growth including internal/external nutrient concentrations (but consider growth in homogeneous environments), as suggested above, we include a mechanism by which internal nutrients are transported to the exterior. Hence, the transport function has two parts f = fin + f,,“t, where fin and f,,“t stand for the influx and leakage terms, respectively. As the activator is necessary for the absorption of nutrients, we assume that &(O, a, .) = 0. It is also assumed that the activator concentration is positively correlated to the rate of absorption, i.e., -1 2 0. As the influx of nutrients
and we also thank B. D. Sleeman for his continued
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F. A. DAVIDSON AND A. W. PARK
microscopic distribution of hyphal boundaries nor depend on knowledge of specific physiological or genetic mechanisms. In this paper, we present a new model formulated to investigate the response of fungal mycelia to a heterogeneous simulations external environment. Comparisons The model is introduced with experimental and one-dimensional are made. numerical are discussed. observations
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mechanism of diffusion. rate is a measure of the work. As experimentally by diffusion. The ratio represent high efficiency.