Engineering material selection intensively depends on domain knowledge.In the face of the large number and wide variety of engineering materials, it is very necessary to research and develop an open, shared, and scalable knowledge framework for implementing domain-oriented and knowledge-based material selection. In this paper, the fundamental concepts and relationships involved in all aspects of material selection are analyzed in detail. A novel ontology-based knowledge framework is presented. The ontology-based Semantic Web technology is introduced into the semantic representation of material selection knowledge. The implicit material selection knowledge is represented as a set of labeled instances and RDF instance graphs in terms of the concept model, which provides a formal approach to organizing the captured material selection knowledge. A knowledge retrieval and reasoning approach integrating ontology concepts, instances, knowledge rules, and semantic queries encoded with Query-enhanced Web Rule Language (SQWRL) is proposed. The presented knowledge framework can provide powerful knowledge services for material selection. Finally, based on this knowledge framework, a case study on constructing a mold material selection knowledge system is provided. This work is a new attempt to build an open and shared knowledge framework for engineering material selection. IntroductionWith the development of technologies, the available set of engineering materials is rapidly growing in both type and number. It is estimated that there are more than 80,000 engineering materials available in the world, and new materials are emerging constantly [1]. Engineering materials are usually coupled with series of manufacturing processes. It is estimated that there are at least 1000 different manufacturing processes that can convert engineering materials into desired products[1]. In the material selection process, design engineers have to take into account a large number of factors, such as physical properties, mechanical properties, thermal properties, material cost, and impact on the environment. Hence, the vast number of materials and processes and the complex relationships between the different selection parameters often make the selection of materials for a given component a difficult task [2].Information on engineering materials presents in two categories: data and knowledge. Data is defined as the result of measurements that can be presented as numerical values, whereas knowledge represents the connections between the items of data [3].As the materials involve a large amount of data, it is necessary to employ database information systems to effectively manage, retrieve, and update the material data. A large number of material databases have been built, most of which can be accessed online [4]. Due to their data-oriented representation mode, the material databases still lack a knowledge inference mechanism and are not able to associate the data with facts.Material selection is a highly knowledge-intensive activity, involving knowle...

Sugarcane (Saccharum spp.) is an important economic crop, supplying up to 80% of the table sugar and~60% of bio-ethanol worldwide. Due to population growth and dwindling fossil-fuel reserves, the demand for sugar and bio-ethanol requires significant improvement in sugarcane production. Breeding sugarcane cultivars with high-performance agronomic traits is undoubtedly the most efficient way to achieve this goal. Therefore, evaluating agronomic traits and dissecting underlying loci are critically important for this aim steps in providing genetic resources and molecular markers for selection. In this study, we assembled a diversity panel of 236 elite sugarcane germplasms originally collected from 12 countries. We evaluated 28 agronomic traits in the diversity panel with three replicates. The diversity panel was genotyped using amplified fragment length polymorphism markers, and a total of 1,359 markers were generated. Through the genome-wide association study, we identified three markers significantly associated with three traits evaluated at a stringent threshold (P < 0.05 after Bonferroni correction). The genotypes of the three associated markers grouped respective trait values into two distinct groups, supporting the reliability of these markers for breeding selection. Our study provides putative molecular markers linked to agronomic traits for breeding robust sugarcane cultivars. Additionally, this study emphasized the importance of sugarcane germplasm introduced from other countries and suggested that the use of these germplasms in breeding programs depends on local industrial needs.

In China, sugarcane (Saccharum spp.) hybrid cross-breeding began in 1953; approximately 70 years since then, >100 commercial sugarcane varieties have been created. In this study, 88 commercial varieties bred in China between 1953 and 2010 and 12 original foundational varieties were planted to investigate the effect of improving sugarcane varieties in China. Considering 20 years as a time node, the commercial varieties were classified into four improved generations. Retrospective analysis showed significant improvements in sucrose and other technological characteristics of commercial sugarcane varieties. The adoption of improved varieties over generations has continuously increased sugarcane’s sucrose, juice sugar, and gravity purity, and the difference was significant between Gen1 and Gen3, and between Gen2 and Gen4. Gen4 showed 2.06%, 2.35%, and 3.69% higher sugarcane sucrose (p < 0.01), juice sugar (p < 0.01), and purity (p < 0.05), respectively, and 1.13% lower sugarcane fiber (p < 0.01) than Gen1, the original foundational hybrid varieties. The development of new varieties has improved the technological characteristics of Chinese sugarcane. Sugarcane sucrose, juice sugar, and purity showed an increasing trend. Sugarcane fiber content did not significantly change with the development of new varieties but declined in comparison with the original foundational hybrid varieties.

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Selection of superior clones in sugarcane (Saccharum spp.) breeding programs follows a multistage process, starting in the first stage with selection of seedlings grown from seeds obtained from crosses. Effective selection of seedlings is important but notoriously difficult. Selection validity is affected by experimental error variation and interplant competition effects and is also complicated by the need to consider many different traits that affect economic value of cultivars (e.g., cane yield, sugar content, fiber content, disease resistance, etc.). In this study, we developed an optimized protocol for selection of sugarcane seedlings that balances the desire to maximize genetic gains but also be cost and labor efficient. A population of seedlings in commercial sugarcane breeding programs was first evaluated in a field trial (Stage 1). A subset of the population was then taken at random and grown in a subsequent trial (Stage 2) for evaluation in small plots. Minor modifications to application of the complete selection index that would greatly reduce labor requirements but have only a small impact on reducing genetic gains were then explored, to identify optimal selection protocols for routine application in commercial breeding programs. A procedure is recommended for routine selection of seedlings that involves (a) selection of families based on an index of four traits (stalk diameter, stalk height, trashiness, and pith rating, all derived from measurements of a small sample of seedlings in each family), followed by (b) sequential measurement and culling of individual seedlings in each selected family based on (in order) trashiness, stalk diameter, and pith rating.