Digital technology enablers for resilient and customer driven food value chains

Food production chains have to respond to disrupted global markets and dynamic customer demands. They are coming under pressure to move from a supply to a demand-driven business model. The inherent difficulties in the lifecycle management of food products, their perishable nature, the volatility in global and regional supplier and customer markets, and the mix of objective and subjective drivers of customer demand and satisfaction, compose a challenging food production landscape. Businesses need to navigate through dynamically evolving operational risks and ensure targeted performance in terms of supply chain resilience and agility, as well as transparency and product assurance. While the industrial transition to digitalised and automated food production chains is seen as a response to such challenges, the contribution of industry 4.0 technology enablers towards this aim is not sufficiently well understood. This paper outlines the key features of high performing food production chains and performs a mapping between them and enabling technologies. As digitalisation initiatives gain priority, such mapping can help with the prioritisation of technology enablers on delivering key aspects of high performing food production chains

A Study on SSD Aware Scan Operation Optimization in PostgreSQL Database

Cost functions used by query optimizers in database systems are built around the properties of conventional hardware technologies like spin type hard disk drives. But with the rapid development in storage technology several new technologies have emerged to overcome the limitations in conventional storage media. One such storage technology is flash storage type which belongs to the broader category of SSDs (Solid State Devices). In this paper we discuss a study done to optimize scan operation performance in PostgreSQL database running on flash storage media by changing the random block transfer cost parameter to a suitable value

Risk quantification in cold chain management : a federated learning-enabled multi-criteria decision-making methodology

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Team innovation in retail services : the role of ambidextrous leadership and team learning

Drawing upon the ambidextrous leadership theory for innovation, this study investigates the role of opening and closing leadership behaviors in both exploratory and exploitative learning in teams, and subsequently, in team innovation in the context of retail services. Results based on a survey data set collected from 296 team leaders in retail services in two major cities in Vietnam show that opening leadership behavior positively affects team exploratory learning and closing leadership behavior underlies team exploitative learning. Further, the interaction between opening and closing leadership behaviors positively affects both team exploratory and exploitative learning. Finally, these two types of team learning enhance team innovation. Our findings extend the existing literature on ambidextrous leadership, learning, and innovation to the team level in a transitioning economy and suggest possible ways for team leaders to enhance team innovation performance

Schema-Independent Scientific Data Cataloging Framework

Modern scientific experiments generate vast volumes of data which are hard to keep track of. Consequently, scientists find it difficult to reuse and share these data sets. We address this problem by developing a schema-independent data cataloging framework for efficient management of scientific data. The proposed solution consists of an agent which automatically identifies new data products and extract metadata from them, as well as a server which indexes the metadata using a NoSQL database and provides a REST API for querying, sharing, and reusing the data sets. The novelty of our solution lies in the pluggable metadata extraction logic, extensible data product generation monitors, use of a NoSQL database, and the ability to dynamically add new metadata fields. The use of Apache Solr as the backend database enables the proposed solution to index and search data products much fatser than a solution based on relational databases. For example, our Apache Solr based implementation can resolve full text, sub-string, prefix, and suffix queries 91% - 99% faster than a MySQL-based implementation.IEEE IEEE Sri Lanka Section Robotics and Automation Section Chapter, IEEE Sri Lanka Sectio

Schema-independent scientific data cataloging framework

Modern scientific experiments generate vast volumes of data which are hard to keep track of. Consequently, scientists find it difficult to reuse and share these data sets. We address this problem by developing a schema-independent data cataloging framework for efficient management of scientific data. The proposed solution consists of an agent which automatically identifies new data products and extract metadata from them, as well as a server which indexes the metadata using a NoSQL database and provides a REST API for querying, sharing, and reusing the data sets. The novelty of our solution lies in the pluggable metadata extraction logic, extensible data product generation monitors, use of a NoSQL database, and the ability to dynamically add new metadata fields. The use of Apache Solr as the backend database enables the proposed solution to index and search data products much fatser than a solution based on relational databases. For example, our Apache Solr based implementation can resolve full text, sub-string, prefix, and suffix queries 91% - 99% faster than a MySQL-based implementation

Key Element-Context Model: An Approach to Efficient Web Metadata Maintence

In order to enhance the quality of care, healthcare organisations are increasingly resorting to clinical decision support systems (CDSSs), which provide physicians with appropriate health care decisions or recommendations. However, how to explicitly represent the diverse vague medical knowledge and effectively reason in the decision-making process are still problems we are confronted. In this paper, we incorporate semiotics into fuzzy logic to enhance CDSSs with the aim of providing both the abilities of describing medical domain concepts contextually and reasoning with vague knowledge. A semiotically inspired fuzzy CDSSs framework is presented, based on which the vague knowledge representation and reasoning process are demonstrated

Analyses of phylogenetics, starch granule morphology and consumer preference of <i>Canna indica</i> L. grown in Sri Lanka

Canna indica is a tuber crop which has many medicinal values. In Sri Lanka, C. indica tubers are consumed in rural areas and mainly available in street-markets of Nuwara-Eliya and Kandy Districts. In the present study, we assessed the phylogenetics of C. indica, starch granule morphology and consumer preference of C. indica tubers in comparison to the popular tuber crops. The phylogenetic analysis was conducted based on the sequence polymorphism at rbcL, atpB gene, trnL-trnF and trnH-psbA marker-loci with respect to the ornamental Canna spp. in Sri Lanka and the previously published sequences of Canna spp. The starch granules were isolated and observed under optical and scanning electron microscopes. The diameter and the surface area of the starch granules were measured under the optical microscope and subjected to analysis of variance. As C. indica tubers are consumed as boiled tuber pieces in Sri Lanka, the consumer preference analysis was conducted using the boiled tuber pieces C. indica, Xanthosoma sagittifolium, Manihot esculenta, Solanum tuberosum, and Ipomoea batatas. The phylogenetic tree based on rbcL marker revealed that C. indica in Sri Lanka is slightly divergent from the other Canna spp. Only the polymorphism of the atpB gene can be used to differentiate C. indica from the ornamental Canna sp. in Sri Lanka. The morphological analysis of starch granules revealed that C. indica has the biggest scallop-seashell shaped starch granules compared to other tuber species. The boiled C. indica tubers were accepted better than that of X. sagittifolium, rated equally to the tubers of S. tuberosum and M. esculenta, and rated less than I. batatas. The hardy and fibrous nature of C. indica tubers must be the major limiting factors for achieving the highest consumer preference highlighting the need of breeding for better texture in tuber

Assessment of the association between yield parameters and polymorphic sites of the <i>Ghd7</i> locus in a core-set of rice cultivars grown in Sri Lanka

Yield improvement is a major aspect in rice breeding programs. Ghd7 is a pleiotropic gene which regulates yield, plant height, and heading date in rice. Although Ghd7 has been previously cloned and sequenced in several other rice cultivars, none of the studies have been conducted for Sri Lankan rice germplasm. Therefore, in this study, we assessed the yield performance of 12 rice cultivars, genetic polymorphism of Ghd7 locus and associations between DNA markers and yield traits. Breeder seeds of the selected cultivars were obtained from RRDI, Bathalagoda, and established under greenhouse conditions at Peradeniya, Sri Lanka in Maha and Yala seasons, 2017. The cultivars were subjected to morphometric analysis, genotyped for 12 DNA markers and sequenced at Seq7-8 locus. Morphometric data were subjected to single marker analysis using General Linear Model (GLM) in SAS 9.4. Here we reported six marker haplotypes based on the arrangement of 13 DNA maker alleles at Ghd7. Moreover, twenty-three SNP/INDEL variations at Seq7-8 locus revealed close genetic relationships between the rice cultivars Bg 90-2, Bg 352 and At 307, Bg310. Four polymorphic markers (Seq7-8, Seq1-2, RM5436 and RM5346) were significantly associated with rice yield traits so that they could be used in marker assisted selection. The SNPs/INDELs of Ghd7 were significantly associated with all the yield traits except 100 seed weight and 100 endosperm weight. Thus the present study demonstrate the possibility of employing marker assisted breeding to improve rice yield using the polymorphic genomic information at Ghd7 locus

The establishment of the species-delimits and varietal-identities of the cultivated germplasm of Luffa acutangula and Luffa aegyptiaca in Sri Lanka using morphometric, organoleptic and phylogenetic approaches.

Luffa acutangula and L. aegyptiaca are two vegetable species commonly found in South and South East Asia. L. acutangula is widely grown; however, L. aegyptiaca is considered as an underutilized crop. The species delimits, phylogenetic positions, and the varietal identities of L. acutangula and L. aegyptiaca in Sri Lanka are not known. Thus, in the present study, we aimed to establish the species delimits and varietal identities of L. acutangula and L. aegyptiaca varieties grown in Sri Lanka using morphometric, phylogenetic and organoleptic assessments. We assessed five varieties of L. acutangula and three varieties of L. aegyptiaca. The vegetative and reproductive data were collected for the morphometric analysis and DNA sequence polymorphism of the makers rbcL, trnH-psbA and ITS for the phylogenetic analysis. We also conducted an organoleptic assessment based on taste parameters; aroma, bitterness, color, texture, and overall preference using the dishes prepared according to the most common Sri Lankan recipe for Luffa. The variation of the vegetative and reproductive traits grouped L. acutangula varieties into two distinct clusters. The trnH-psbA polymorphism provided the basis for the species delimits of L. acutangula and L. aegyptiaca. The rbcL and ITS polymorphisms provided the basis for the identities of the varieties of L. aegyptiaca and L. acutangula respectively. In the phylogeny, the L. acutangula varieties of Sri Lanka formed a unique clade and the L. aegyptiaca varieties formed a reciprocal monophyletic group in comparison to worldwide L. aegyptiaca reported. The taste parameters aroma, texture, color, and overall preference were significantly different among the Luffa varieties. The L. aegyptiaca varieties received lower preference in the organoleptic assessment. The present study sets the species delimits, phylogenetic positions and the varietal identities of the cultivated germplasm of Luffa and revealed the distinct morphological and organoleptic properties of each variety