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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Trejo Beltran, Dax Yair;

    This study investigates the adoption of Internet of Things-enhanced Smart Packaging within the Food Supply Chain (FSC) to combat food waste and enhance operational efficiency. With global challenges like food waste and operational efficiency persisting, innovative technologies can advance the FSC. By examining the drivers and barriers influencing IoT-enhanced Smart Packaging adoption, this exploratory research provides a general understanding of its potential impact. Semi-structured interviews were conducted with experts spanning companies from producers to grocers, as well as packaging manufacturers. Thematic analysis of these interviews uncovers crucial insights. Key drivers, including consumer requirements, food quality monitoring, efficiency, and sustainability emerged alongside barriers such as cost, consumer perception, technological complexities, and regulatory uncertainties. The findings highlight the potential to reduce food waste and enhance efficiency and visibility through IoT-enhanced Smart Packaging. Additionally, they highlight the need for stakeholder collaboration, governmental support, and effective education to expedite adoption and achieve sustainable outcomes within the FSC. This research offers a unique perspective on the evolving landscape of IoT-enhanced Smart Packaging adoption, its transformative potential, and the challenges it aims to address.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ MSpace at the Univer...arrow_drop_down
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    Authors: Scott, Ashlyn;

    While abrupt weaning is a common practice in commercial swine barns, it subjects piglets to numerous changes at once which is often associated with negative welfare. Our objective was to study the effects of pre-weaning socialization (starting at 1 to 3 days of age) in multi-litter groups as well as object enrichment (burlap sheet) in the pre- and post-weaning environment. We compared piglet performance, behaviour, and welfare across 6 treatments that combined group size (1 vs. 2 vs. 4 litters mixed pre-weaning) and burlap provision (yes vs. no). We recorded piglet behaviour, piglet body weights, and sow and piglet lesion scores. An ANOVA linear model was run on all normal conforming data, while data that did not meet the normality criteria were transformed or analyzed using a non-parametric test. SOCIAL ENRICHMENT (PRE-WEANING MIXING): Increased burlap use and cross-sucking with group size (P 0.10). Overall, social and object enrichment allow piglets to socialize with others at a younger age and redirect their attention and aggression toward objects such as burlap, which does not negatively impact piglet performance and can improve piglet behaviour and welfare around weaning.

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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Smith, Jaime;
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    Authors: Doderai, Anaïs;
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    Authors: Mendoza, Paulene;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Education and Resear...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Education and Resear...arrow_drop_down
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Lakshmi, Vijaya; Corbett, Jacqueline;

    The world is confronted with the grand challenge of food insecurity amidst growing populations and the climate crisis. Artificial intelligence (AI) deployed in agricultural decision support systems (AgriDSS) raises both hopes and concerns for increasing agricultural productivity in sustainable ways. We conduct a scoping review to uncover the roadblocks to the use of AI-supported AgriDSS in sustainable agriculture. Based on the corpus of 121 articles, we find that the effective use of AI-supported AgriDSS is hindered at technical, social, ethical, and ecological levels. Then, drawing on the experiential learning perspective, we propose how conjoint experiential learning (CEL) can enhance sustainable agricultural practices by enhancing both AI and human learning and overcoming roadblocks in using AgriDSS. Based on this conceptual framework, we build a research agenda that suggests blind spots and possible directions for future research.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CorpusULarrow_drop_down
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      CorpusUL
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Pérez Maldonado, Manuel Alejandro; Ofori-Darko, Daniel; Nichols, Vanessa; Reid-Smith, Richard; +1 Authors
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DSpace at the Univer...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ DSpace at the Univer...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Good, Kenton; Severson, Sarah;

    The University of Alberta Library has been actively expanding its use of the Internet Archive platform to consolidate its already-digitized collections and upload newly digitized materials. In this presentation, they will discuss some of the tools they use to better manage those digital collections.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Education and Resear...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://doi.org/10.7939/r3-5cf...
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      https://doi.org/10.7939/r3-5cf...
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    Authors: Encabo, Jan Bryan;

    Understanding the carrying capacity and the stocking rates of crown lands is critical for the beef industry in the Prairies that relies heavily on these lands for grazing. The overall goal of this study was to examine the current carrying capacities and stocking rates of the crown lands in Manitoba. The main objectives of this study were to i) classify each crown land parcel in the province by land cover type or vegetation type and ii) estimate the carrying capacities and stocking rates of each parcel and compare these to the current stocking rates allowed by the provincial crown land leases. This study used remote sensing and geographic information system (GIS) technologies for land cover monitoring and estimation of carrying capacities and stocking rates. Based on the assessment of remotely sensed land cover inventories, forest and shrubland were found to be the dominant land cover types in the crown lands compared to native and tame grasslands, which are more desirable for grazing due to higher forage quality and palatability. Then, the carrying capacities were estimated from past field surveys that measured forage productivity in different ecoregions of Manitoba. The carrying capacities were used to calculate the stocking rates based on the delineated land cover types within each crown land parcel. Results show that the current stocking rates of the majority of the crown lands were lower than the estimated stocking rates. This suggests that these parcels were being undergrazed compared to the current grazing intensities permitted by the lease contracts. Overall, the forage resources of the crown lands in Manitoba were being undergrazed by -44.64%. This study can contribute to the existing management of crown lands and it also demonstrated the potential of remote sensing technology to improve and expedite land cover monitoring and stocking rate estimation for crown land managers in the future.

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    Authors: Miralda, Shania;

    This research includes two studies on estimating crop yield using satellite-based vegetation indices. For the first study, the objective is to compare eight different functional forms for estimating U.S crop yield using satellite based NDVI. For the second study, the objective is to examine 10 satellite-based vegetation indices for estimating U.S crop yield. For both studies, corn, soybeans, spring wheat, and winter wheat data for crop yield (bushel/acre) were obtained from the USDA NASS from 2008 to 2019 for a total of 12 years covering all 48 states in the United States except Hawaii and Alaska (though different states are included, based on where the crops are grown). Data for the vegetation indices were obtained from the MODIS satellite using 250m resolution level and selecting for maximum Vegetation Index values. The methodology used regression with crop yield as the dependent variable. The main independent variable is the selected vegetation index (e.g NDVI, GOSAVI, etc). A time trend variable is also included, and dummy variables for U.S States. Results for the first study indicated that relationship between NDVI and crop yield was mostly nonlinear, and piecewise regression was generally found to be the most suitable functional form. Results for the second study showed that for all 10 indices analyzed, that RDVI, GOSAVI, and GSAVI provided better estimates of crop yield than the commonly used NDVI. These results should be useful in providing a better understanding of various functional forms and various satellite based vegetation indices for improving crop yield estimation.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Trejo Beltran, Dax Yair;

    This study investigates the adoption of Internet of Things-enhanced Smart Packaging within the Food Supply Chain (FSC) to combat food waste and enhance operational efficiency. With global challenges like food waste and operational efficiency persisting, innovative technologies can advance the FSC. By examining the drivers and barriers influencing IoT-enhanced Smart Packaging adoption, this exploratory research provides a general understanding of its potential impact. Semi-structured interviews were conducted with experts spanning companies from producers to grocers, as well as packaging manufacturers. Thematic analysis of these interviews uncovers crucial insights. Key drivers, including consumer requirements, food quality monitoring, efficiency, and sustainability emerged alongside barriers such as cost, consumer perception, technological complexities, and regulatory uncertainties. The findings highlight the potential to reduce food waste and enhance efficiency and visibility through IoT-enhanced Smart Packaging. Additionally, they highlight the need for stakeholder collaboration, governmental support, and effective education to expedite adoption and achieve sustainable outcomes within the FSC. This research offers a unique perspective on the evolving landscape of IoT-enhanced Smart Packaging adoption, its transformative potential, and the challenges it aims to address.

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    Authors: Scott, Ashlyn;

    While abrupt weaning is a common practice in commercial swine barns, it subjects piglets to numerous changes at once which is often associated with negative welfare. Our objective was to study the effects of pre-weaning socialization (starting at 1 to 3 days of age) in multi-litter groups as well as object enrichment (burlap sheet) in the pre- and post-weaning environment. We compared piglet performance, behaviour, and welfare across 6 treatments that combined group size (1 vs. 2 vs. 4 litters mixed pre-weaning) and burlap provision (yes vs. no). We recorded piglet behaviour, piglet body weights, and sow and piglet lesion scores. An ANOVA linear model was run on all normal conforming data, while data that did not meet the normality criteria were transformed or analyzed using a non-parametric test. SOCIAL ENRICHMENT (PRE-WEANING MIXING): Increased burlap use and cross-sucking with group size (P 0.10). Overall, social and object enrichment allow piglets to socialize with others at a younger age and redirect their attention and aggression toward objects such as burlap, which does not negatively impact piglet performance and can improve piglet behaviour and welfare around weaning.

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    Authors: Smith, Jaime;
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    Authors: Doderai, Anaïs;
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    Authors: Mendoza, Paulene;
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    Authors: Lakshmi, Vijaya; Corbett, Jacqueline;

    The world is confronted with the grand challenge of food insecurity amidst growing populations and the climate crisis. Artificial intelligence (AI) deployed in agricultural decision support systems (AgriDSS) raises both hopes and concerns for increasing agricultural productivity in sustainable ways. We conduct a scoping review to uncover the roadblocks to the use of AI-supported AgriDSS in sustainable agriculture. Based on the corpus of 121 articles, we find that the effective use of AI-supported AgriDSS is hindered at technical, social, ethical, and ecological levels. Then, drawing on the experiential learning perspective, we propose how conjoint experiential learning (CEL) can enhance sustainable agricultural practices by enhancing both AI and human learning and overcoming roadblocks in using AgriDSS. Based on this conceptual framework, we build a research agenda that suggests blind spots and possible directions for future research.

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    Authors: Pérez Maldonado, Manuel Alejandro; Ofori-Darko, Daniel; Nichols, Vanessa; Reid-Smith, Richard; +1 Authors
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    Authors: Good, Kenton; Severson, Sarah;

    The University of Alberta Library has been actively expanding its use of the Internet Archive platform to consolidate its already-digitized collections and upload newly digitized materials. In this presentation, they will discuss some of the tools they use to better manage those digital collections.

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    https://doi.org/10.7939/r3-5cf...
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    Authors: Encabo, Jan Bryan;

    Understanding the carrying capacity and the stocking rates of crown lands is critical for the beef industry in the Prairies that relies heavily on these lands for grazing. The overall goal of this study was to examine the current carrying capacities and stocking rates of the crown lands in Manitoba. The main objectives of this study were to i) classify each crown land parcel in the province by land cover type or vegetation type and ii) estimate the carrying capacities and stocking rates of each parcel and compare these to the current stocking rates allowed by the provincial crown land leases. This study used remote sensing and geographic information system (GIS) technologies for land cover monitoring and estimation of carrying capacities and stocking rates. Based on the assessment of remotely sensed land cover inventories, forest and shrubland were found to be the dominant land cover types in the crown lands compared to native and tame grasslands, which are more desirable for grazing due to higher forage quality and palatability. Then, the carrying capacities were estimated from past field surveys that measured forage productivity in different ecoregions of Manitoba. The carrying capacities were used to calculate the stocking rates based on the delineated land cover types within each crown land parcel. Results show that the current stocking rates of the majority of the crown lands were lower than the estimated stocking rates. This suggests that these parcels were being undergrazed compared to the current grazing intensities permitted by the lease contracts. Overall, the forage resources of the crown lands in Manitoba were being undergrazed by -44.64%. This study can contribute to the existing management of crown lands and it also demonstrated the potential of remote sensing technology to improve and expedite land cover monitoring and stocking rate estimation for crown land managers in the future.

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    Authors: Miralda, Shania;

    This research includes two studies on estimating crop yield using satellite-based vegetation indices. For the first study, the objective is to compare eight different functional forms for estimating U.S crop yield using satellite based NDVI. For the second study, the objective is to examine 10 satellite-based vegetation indices for estimating U.S crop yield. For both studies, corn, soybeans, spring wheat, and winter wheat data for crop yield (bushel/acre) were obtained from the USDA NASS from 2008 to 2019 for a total of 12 years covering all 48 states in the United States except Hawaii and Alaska (though different states are included, based on where the crops are grown). Data for the vegetation indices were obtained from the MODIS satellite using 250m resolution level and selecting for maximum Vegetation Index values. The methodology used regression with crop yield as the dependent variable. The main independent variable is the selected vegetation index (e.g NDVI, GOSAVI, etc). A time trend variable is also included, and dummy variables for U.S States. Results for the first study indicated that relationship between NDVI and crop yield was mostly nonlinear, and piecewise regression was generally found to be the most suitable functional form. Results for the second study showed that for all 10 indices analyzed, that RDVI, GOSAVI, and GSAVI provided better estimates of crop yield than the commonly used NDVI. These results should be useful in providing a better understanding of various functional forms and various satellite based vegetation indices for improving crop yield estimation.

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