E-ISSN 3041-4180
 

Original Article
Online Published: 11 Apr 2025


Apple tree intercropping planner application utilizing fuzzy logic

Adnan Shaout, Emma Hetrick, Matthew Keenan.


Abstract
Aim/Background:
Intercropping and agroforestry have become key components of modern land management systems, aimed at optimizing crop yields and strengthening ecosystems against climate change and unpredictable weather. Traditionally, developing intercropping methods has been limited to controlled environments with a narrow range of plant combinations or specific regional focus.

Methods:
This paper proposes a novel approach that utilizes fuzzy logic and geospatial mapping techniques to autonomously generate optimal intercropping layouts tailored to specific environments. Users can select various trees, plants, and shrubs, and the system will consider multiple environmental factors.

Results:
Membership functions are developed based on the attributes each selected plant contributes to the environment—such as shade provision, nitrogen fixation, nitrogen uptake, and pest prevention—drawing on expert insights and statistical analyses.

Conclusion:
Using these membership functions, the system calculates and displays a 2D optimized layout, ensuring the selected plants are arranged efficiently to meet each plant's needs and thrive in the given ecosystem.

Key words: Apple Tree Intercropping Planner Application; Agroforestry; Fuzzy Logic; Intercropping; Food Forest; Fuzzy Inference System (FIS)


 
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How to Cite this Article
Pubmed Style

Shaout A, Hetrick E, Keenan M. Apple tree intercropping planner application utilizing fuzzy logic. J Res Agric Food Sci. 2025; 2(2): 141-155. doi:10.5455/JRAFS.20250320110701


Web Style

Shaout A, Hetrick E, Keenan M. Apple tree intercropping planner application utilizing fuzzy logic. https://www.jrafs.com/?mno=248561 [Access: May 03, 2025]. doi:10.5455/JRAFS.20250320110701


AMA (American Medical Association) Style

Shaout A, Hetrick E, Keenan M. Apple tree intercropping planner application utilizing fuzzy logic. J Res Agric Food Sci. 2025; 2(2): 141-155. doi:10.5455/JRAFS.20250320110701



Vancouver/ICMJE Style

Shaout A, Hetrick E, Keenan M. Apple tree intercropping planner application utilizing fuzzy logic. J Res Agric Food Sci. (2025), [cited May 03, 2025]; 2(2): 141-155. doi:10.5455/JRAFS.20250320110701



Harvard Style

Shaout, A., Hetrick, . E. & Keenan, . M. (2025) Apple tree intercropping planner application utilizing fuzzy logic. J Res Agric Food Sci, 2 (2), 141-155. doi:10.5455/JRAFS.20250320110701



Turabian Style

Shaout, Adnan, Emma Hetrick, and Matthew Keenan. 2025. Apple tree intercropping planner application utilizing fuzzy logic. Journal of Research in Agriculture and Food Sciences, 2 (2), 141-155. doi:10.5455/JRAFS.20250320110701



Chicago Style

Shaout, Adnan, Emma Hetrick, and Matthew Keenan. "Apple tree intercropping planner application utilizing fuzzy logic." Journal of Research in Agriculture and Food Sciences 2 (2025), 141-155. doi:10.5455/JRAFS.20250320110701



MLA (The Modern Language Association) Style

Shaout, Adnan, Emma Hetrick, and Matthew Keenan. "Apple tree intercropping planner application utilizing fuzzy logic." Journal of Research in Agriculture and Food Sciences 2.2 (2025), 141-155. Print. doi:10.5455/JRAFS.20250320110701



APA (American Psychological Association) Style

Shaout, A., Hetrick, . E. & Keenan, . M. (2025) Apple tree intercropping planner application utilizing fuzzy logic. Journal of Research in Agriculture and Food Sciences, 2 (2), 141-155. doi:10.5455/JRAFS.20250320110701