Linking GlutoPeak attributes of flour to genome variation

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Diagnostic MixoLab signatures to distinguish flour quality attributes

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The wheat proteome in relation to flour mixing properties

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An information-based decision support framework for eAgriculture

The ability of farmers to acquire knowledge to make decisions is limited by the information quality and applicability. An inconsistency in information delivery and standards for the integration of information also limits the decision making process. Knowledge Discovery in Databases (KDD) methodology described for the data mining is an example of how frameworks can be used to facilitate such data integration. This research will examine how such a ICT based framework can be used to facilitate the acquisition of knowledge for the farmer decision making process. The Farmer Knowledge and Decision Support Framework (FKDSF) takes information provided to farmers and utilizes processes that deliver this critical information for knowledge acquisition. This framework describes steps for data capture, analysis and data processing which precede the delivery of the integrated information for the farmer. Information is collected from disparate sources, captured and validated according to defined rules. Data mining tools then process and integrate the data into a format that contributes to the knowledge base that can be readily used by the farmer. This research paper will show how the proposed framework may be used for farmer knowledge acquisition using simulated data and discusses how it can be used in an agricultural industry context

Evaluating the impact of rainfall and temperature on wheat dough strength in Western Australia

Background and objectives Western Australian wheat farmers rely on the international market to sell their wheat. One advantage they have in the market place is Australia's reputation for good and reliable wheat quality. However, consecutive years of weaker‐than‐expected dough strength placed specific consistency concerns on Western Australian hard‐grained wheat exports. To investigate why weak dough strength occurred, a multi‐season set of data was compiled. It was made up of quality results from historical crop reports and breeder trials. Recycling of data was an efficient initial step to examine the problem, but to overcome limitations, modeled climate measurements and phenotype information needed to be combined with the quality data to allow mixed model statistics to be used for analysis of the unbalanced data. Findings The key findings were three climate measurements linked to weak dough properties as measured by extensograph maximum resistance. A negative relationship between dough strength and rainfall in the period 60 days after flowering, tested as the percentage of total growing season rainfall, was found. Two temperature‐related measurements were identified as having a positive relationship with dough strength. These were the number of consecutive days that had a maximum temperature of ≥28°C and mean daily temperature range occurring during the 60‐day period after flowering. Conclusions The combined impact of moisture and temperature levels during the post‐flowering period on wheat dough strength builds on the previous understanding of high temperatures changing dough strength. Significance and novelty The recycling of data was a useful first step in understanding a complex issue, and the results provide a reference guide for further research into understanding the interaction between a changing growing environment and important wheat quality parameters

Effective ICTs in agricultural value chains to improve food security: An international perspective

This paper examines the grains value chain in agriculture, and identifies the importance in developing strategies which could better secure food production. The study highlights examples of successful integration of ICTs in agricultural supply and value chains. The development of strategies to integrate these ICTs into the supply chain will be proposed. It will be argued that the use of high powered computing for data mining and other technologies such as sensor networks, mobile communications, and GPS technologies can revolutionize the efficiency of these supply chains and therefore improve the food security. The study carried out a situational analysis of agricultural resources using standard internet search engines and applying data mining techniques in order to demonstrate how such technologies can be used to show difference in value chains across different situations. An assessment of the study found that the results from the grain-industry dataset support the similar supply chain grouping reported for other research studies. These groupings reflect the more-developed food industry supply chains and may not capture all the interactions in less-developed supply chains. For example, when several of the food production processes are carried out by one food producer, the activities will be more difficult to identify

Using big data to predict the likelihood of low falling numbers in wheat

Background and objectives: Preharvest sprouting in wheat reduces quality and impacts farmer profitability. The international recognized falling number test can be used to measure that damage. Trying to understand the complex interactions that cause a reduction in wheat quality, equating to low falling number levels, is challenging. An alternative research approach to replicated experiments was to use a multiseason dataset of load-by-load delivery information to investigate whether correlations between falling number levels and 40 climate measurements could be identified. Findings: This study used over 250,000 falling number data points from individual truckloads tested during seven harvests in Western Australia. The analyses identified relative humidity measured at the maximum temperature and daily temperature range as having consistent correlations with falling number levels over multiple seasons. Other climate measurements were also observed to have significant correlations with falling number, but these were less consistent within and between seasons. Conclusions: The linkage of humidity and temperature range levels in the period before harvest commences to the occurrence of low falling number levels helps to further understand the complex interactions that change starch quality. Significance and novelty: The findings demonstrate that value can be obtained from the use of a large, nonexperimentally designed dataset

An eAgriculture-based decision support framework for information dissemination

The ability of farmers to acquire knowledge to make decisions is limited by the information quality and applicability. Inconsistencies in information delivery and standards for the integration of information also limit decision making processes. This research uses a similar approach to the Knowledge Discovery in Databases (KDD) methodology to develop an ICT based framework which can be used to facilitate the acquisition of knowledge for farmers’ decision making processes. This is one of the leading areas of research and development for information technology in an agricultural industry, which is yet to utilize such technologies fully. The Farmer Knowledge and Decision Support Framework (FKDSF) takes information provided to farmers and utilizes processes that deliver this critical information for knowledge acquisition. The framework comprises data capture, analysis, and data processing, which precede the delivery of the integrated information for the farmer. With information collected, captured, and validated from disparate sources, according to defined sets of rules, data mining tools are then used to process and integrate the data into a format that contributes to the knowledge base used by the farmer and the agricultural industry

Crossdocking en consolidatie : distributieconcept voor de levensmiddelenbranche

Veel ondernemingen zien zich genoodzaakt hun distributieconcept te veranderen. Hogere, meer diverse en sneller veranderende klantenwensen zorgen voor een toenemende logistieke complexiteit en toenemende logistieke kosten. Met name in de levensmiddelenbranche zijn levertijd, leverfrequentie en leverbetrouwbaarheid van essentieel belang geworden. De eisen die consumenten stellen aan de retailers worden vertaald in eisen die de retailers stellen aan de groothandel, die ze weer doorvertaalt aan de producenten. Steeds vaker mag een logistiek dienstverlener de consequenties van deze toenemende eisen tegen minimale kosten opvangen

Crossdocking en consolidatie : distributieconcept voor de levensmiddelenbranche

Veel ondernemingen zien zich genoodzaakt hun distributieconcept te veranderen. Hogere, meer diverse en sneller veranderende klantenwensen zorgen voor een toenemende logistieke complexiteit en toenemende logistieke kosten. Met name in de levensmiddelenbranche zijn levertijd, leverfrequentie en leverbetrouwbaarheid van essentieel belang geworden. De eisen die consumenten stellen aan de retailers worden vertaald in eisen die de retailers stellen aan de groothandel, die ze weer doorvertaalt aan de producenten. Steeds vaker mag een logistiek dienstverlener de consequenties van deze toenemende eisen tegen minimale kosten opvangen