Browsing by Subject "agriculture"

Now showing 1 - 7 of 7
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    Deep Learning based Crop Row Detection with Online Domain Adaptation
    (ACM, 2021-08) Doha, Rashed; Al Hasan, Mohammad; Anwar, Sohel; Rajendran, Veera; Computer and Information Science, School of Science
    Detecting crop rows from video frames in real time is a fundamental challenge in the field of precision agriculture. Deep learning based semantic segmentation method, namely U-net, although successful in many tasks related to precision agriculture, performs poorly for solving this task. The reasons include paucity of large scale labeled datasets in this domain, diversity in crops, and the diversity of appearance of the same crops at various stages of their growth. In this work, we discuss the development of a practical real-life crop row detection system in collaboration with an agricultural sprayer company. Our proposed method takes the output of semantic segmentation using U-net, and then apply a clustering based probabilistic temporal calibration which can adapt to different fields and crops without the need for retraining the network. Experimental results validate that our method can be used for both refining the results of the U-net to reduce errors and also for frame interpolation of the input video stream.
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    Designing Sustainable Food Systems
    (ACM, 2017-05) Raturi, Ankita; Norton, Juliet; Tomlinson, Bill; Blevis, Eli; Dombrowski, Lynn; Human-Centered Computing, School of Informatics and Computing
    There is significant interest in designing technologies for the food system, from agricultural modeling tools to apps enabling humans to assess nutritional value of various food choices to drones for pest detection. However, a good food system must be a sustainable one. There is an urgent need for deliberation and thoughtfulness in designing for both technologies that support existing food systems and new modalities that work towards more sustainable food systems. This workshop will bring together HCI researchers, designers, and practitioners with an interest in exploring what constitutes a sustainable food system, as well as defining the role of HCI in this domain. Our key objectives for this workshop will be to identify what opportunities for design and collaboration exist and to lay the foundation for an active foodCHI community.
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    Feeding the World with Data: Visions of Data-Driven Farming
    (ACM, 2019-06) Steup, Rosemary; Dombrowski, Lynn; Su, Norman Makoto; Human-Centered Computing, School of Informatics and Computing
    Recent years have seen increased investment in data-driven farming through the use of sensors (hardware), algorithms (software), and networking technologies to guide decision making. By analyzing the discourse of 34 startup company websites, we identify four future visions promoted by data-driven farming startups: the vigilant farmer who controls all aspects of her farm through data; the efficient farmer who has optimized his farm operations to be profitable and sustainable; the enlightened farmer who achieves harmony with nature via data-driven insights; and the empowered farmer who asserts ownership of her farm's data, and uses it to benefit herself and her fellow farmers. We describe each of these visions and how startups propose to achieve them. We then consider some consequences of these visions; in particular, how they might affect power relations between the farmer and other stakeholders in agriculture--farm workers, nonhumans, and the technology providers themselves.
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    A Grand Challenge for HCI: Food + Sustainability
    (ACM, 2017-11) Norton, Juliet; Raturi, Ankita; Nardi, Bonnie; Prost, Sebastian; McDonald, Samantha; Pargman, Daniel; Bates, Oliver; Normark, Maria; Tomlinson, Bill; Herbig, Nico; Dombrowski, Lynn; Human-Centered Computing, School of Informatics and Computing
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    Hydrologic connectivity and land cover affect floodplain lake water quality, fish abundance, and fish diversity in floodplain lakes of the Wabash-White River basin
    (Wiley, 2022) Carlson Mazur, Martha L.; Smith, Bradley; Bird, Broxton W.; McMillan, Sara; Pyron, Mark; Hauswald, Cassie; Earth Sciences, School of Science
    Floodplain lakes are important aquatic resources for supporting ecosystem services, such as organismal habitat, biodiversity, and the retention of nutrients and sediment. Due to geomorphic alteration of river channels and land-cover change, degradation to floodplain lakes in the Ohio River basin is occurring at a rate that will escalate as climate change causes increased flood intensity and the seasonal redistribution of rainfall. A better understanding of the local drivers that affect oxbow lakes is needed for targeted floodplain restoration efforts designed to slow degradation. We examined the effects of land cover, topography, and hydrologic connectivity on water quality and fish diversity and abundance in nine floodplain lakes with potentially high remnant ecological function in the Wabash-White watershed (Indiana, Ohio, and Illinois). Data collection included water-quality parameters; stable water isotopes; total phosphorus, total nitrogen, and chlorophyll-a; and fish community diversity and abundance. Results indicate that hay/pasture land cover and decreased topographic relief in the local oxbow watersheds, along with reduced river hydrologic connectivity, were related to an increase in total phosphorus, total nitrogen, and chlorophyll-a. Greater biodiversity and abundance in fish assemblages were evident in oxbow lakes that were more disconnected from the main channel. The results of this study suggest that hydrologic connectivity of oxbow lakes with the contributing drainage area and the main channel influence nutrients and fish communities. Knowing the influencing factors can help ecosystem managers better protect these valuable floodplain lake ecosystems and prioritize restoration efforts amidst increasing stressors due to climate and land-use changes.
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    Multiple Methods to Partition Evapotranspiration in a Maize Field
    (2017-01) Wu, Youjie; Du, Taisheng; Ding, Risheng; Tong, Ling; Li, Sien; Wang, Lixin; Department of Earth Sciences, School of Science
    Partitioning evapotranspiration (ET) into soil evaporation E and plant transpiration T is important, but it is still a theoretical and technical challenge. The isotopic technique is considered to be an effective method, but it is difficult to quantify the isotopic composition of transpiration δT and evaporation δE directly and continuously; few previous studies determined δT successfully under a non-steady state (NSS). Here, multiple methods were used to partition ET in a maize field and a new flow-through chamber system was refined to provide direct and continuous measurement of δT and δE. An eddy covariance and lysimeter (EC-L)-based method and two isotope-based methods [isotope combined with the Craig–Gordon model (Iso-CG) and isotope using chamber measurement (Iso-M)] were applied to partition ET. Results showed the transpiration fraction FT in Iso-CG was consistent with EC-L at both diurnal and growing season time scales, but FT calculated by Iso-M was less than Iso-CG and EC-L. The chamber system method presented here to determine δT under NSS and isotope steady state (ISS) was robust, but there could be some deviation in measuring δE. The FT varied from 52% to 91%, with a mean of 78% during the entire growing season, and it was well described by a function of LAI, with a nonlinear relationship of FT = 0.71LAI0.14. The results demonstrated the feasibility of the isotope-based chamber system to partition ET. This technique and its further development may enable field ET partitioning accurately and continuously and improve understanding of water cycling through the soil–plant–atmosphere continuum.
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    Quantitative synthesis on the ecosystem services of cover crops
    (Elsevier, 2018-10) Daryanto, Stefani; Fu, Bojie; Wang, Lixin; Jacinthe, Pierre-André; Zhao, Wenwu; Earth Sciences, School of Science
    The maintenance of soil health in agro-ecosystems is essential for sustaining agricultural productivity. Through its positive impacts on various soil physical and biological processes, cover cropping can be an important component of sustainable agricultural production systems. However, the practice of cover cropping can be complex, and possible trade-offs between the benefits and side effects of cover crops have not been examined. To evaluate these benefits and potential trade-offs, we quantitatively synthesized different ecosystem services provided by cover crops (e.g., erosion control, water quality regulation, soil moisture retention, accumulation of soil organic matter and microbial biomass, greenhouse gas (GHG) emission, weed and pest control, as well as yield of the subsequent cash crop) using data from previous publications. We used a simple indicator (δ), defined as the ratio of an observed variable (i.e., ecosystem service) under cover crop and under fallow condition, to evaluate the impacts of cover crops on a given ecosystem service. Our results showed that cover crops provided beneficial ecosystem services in most cases, except for an increase in GHG emission (δCO2 = 1.46 ± 0.47 and δN2 O = 1.49 ± 1.22;  ± SD) and in pest (nematode) incidence (δnematode abundance = 1.29 ± 1.61). It is also important to highlight that, in some cases, tillage could offset the extent of ecosystem service benefits provided by cover crops. Based on this synthesis, we argue that cover crops should be incorporated into modern agricultural practices because of the many environmental benefits they offer, particularly the maintenance of soil and ecosystem health. More importantly, there was generally an increase in cash crop yield with cover cropping (δyield = 1.15 ± 0.75), likely due to improvement in various soil processes. Despite its benefits, the complexity of cover crop management should not be overlooked, and site-specific factors such as climate, soil type, cover crop species and tillage practices must be considered in order to optimize the benefits of cover cropping. In addition to crop yield, detailed economic analyses are needed to calculate the direct (e.g., reduction in the amount of chemical fertilizer) and indirect monetary benefits (e.g., the improvement of soil quality) of cover crops. Such a comprehensive analysis could serve as incentive for producers to integrate cover crops into their management practices.