IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i6p1113-d1154218.html
   My bibliography  Save this article

Using Image Texture Analysis to Evaluate Soil–Compost Mechanical Mixing in Organic Farms

Author

Listed:
  • Elio Romano

    (Council for Agricultural Research and Economics (CREA), Research Centre for Engineering and Agro-Food Processing, Via Milano 43, 24047 Treviglio, BG, Italy)

  • Massimo Brambilla

    (Council for Agricultural Research and Economics (CREA), Research Centre for Engineering and Agro-Food Processing, Via Milano 43, 24047 Treviglio, BG, Italy)

  • Carlo Bisaglia

    (Council for Agricultural Research and Economics (CREA), Research Centre for Engineering and Agro-Food Processing, Via Milano 43, 24047 Treviglio, BG, Italy)

  • Alberto Assirelli

    (Council for Agricultural Research and Economics (CREA), Research Centre for Engineering and Agro-Food Processing, Via Milano 43, 24047 Treviglio, BG, Italy)

Abstract

Soil amendments (e.g., compost) require uniform incorporation in the soil profile to benefit plants. However, machines may not mix them uniformly throughout the upper soil layer commonly explored by plant roots. The study focuses on using image texture analysis to determine the level of mixing uniformity in the soil following the passage of two kinds of harrows. A 12.3-megapixel DX-format digital camera acquired images of soil/expanded polystyrene (in the laboratory) and soil/compost mixtures (in field conditions). In the laboratory, pictures captured the soil before and during the simulated progressive mixing of expanded polystyrene particles. In field conditions, images captured the exposed superficial horizons of compost-amended soil after the passage of a combined spike-tooth–disc harrow and a disc harrow. Image texture analysis based on the gray-level co-occurrence matrix calculated the sums of dissimilarity, contrast, entropy, and uniformity metrics. In the laboratory conditions, the progressive mixing resulted in increased image dissimilarity (from 1.15 ± 0.74 × 10 6 to 1.65 ± 0.52 × 10 6 ) and contrast values (from 2.69 ± 2.06 × 10 6 to 5.67 ± × 1.93 10 6 ), almost constant entropy (3.50 ± 0.25 × 10 6 ), and decreased image uniformity (from 6.65 ± 0.31 × 10 5 to 4.49 ± 1.36 × 10 5 ). Using a tooth-disc harrow in the open field resulted in higher dissimilarity, contrast, entropy (+73.3%, +62.8%, +16.3%), and lower image uniformity (−50.6%) than the disc harrow, suggesting enhanced mixing in the superficial layer.

Suggested Citation

  • Elio Romano & Massimo Brambilla & Carlo Bisaglia & Alberto Assirelli, 2023. "Using Image Texture Analysis to Evaluate Soil–Compost Mechanical Mixing in Organic Farms," Agriculture, MDPI, vol. 13(6), pages 1-13, May.
  • Handle: RePEc:gam:jagris:v:13:y:2023:i:6:p:1113-:d:1154218
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/6/1113/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/13/6/1113/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yue Zhao & Zhuopeng Zhang & Honglei Zhu & Jianhua Ren, 2022. "Quantitative Response of Gray-Level Co-Occurrence Matrix Texture Features to the Salinity of Cracked Soda Saline–Alkali Soil," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kailin Ren & Lide Su & Yong Zhang & Xiang He & Xuyang Cai, 2023. "Optimization and Experiment of Livestock and Poultry Manure Composting Equipment with Vented Heating," Sustainability, MDPI, vol. 15(14), pages 1-22, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:6:p:1113-:d:1154218. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.