Author
Listed:
- Bitopi Biswas
(Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh)
- Mohammad Tariful Alam Khan
(Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh)
- Mohammad Billal Hossain Momen
(Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh)
- Mohammad. Rashedur Rahman Tanvir
(Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh)
- Abu Mohammad Shahidul Alam
(Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh)
- M Robiul Islam Islam
(Precision and Automated Agriculture Laboratory, Department of Agronomy and Agricultural Extension, Rajshahi University, Rajshahi, Bangladesh)
Abstract
The research was conducted at the Department of Agronomy and Agricultural Extension, Rajshahi University, from December 2021 to April 2022. The objective was to develop a fuzzy expert system for site-specific N fertilisation using leaf colour code (RGB) and irrigation frequencies for maize yield. The experiment encompassed two primary factors: nitrogen fertiliser application rates (N1: 100%, N2: 75%, N3: 50% of conventional rates) and irrigation frequencies (I1: 100%, I2: 75%, I3: 50% of pan evaporation). A completely randomised design (CRD) with three replications was used to arrange the experimental pots, each receiving recommended doses of phosphorus, potassium, and sulfur, with urea applied per treatment instructions. Results revealed significant chlorophyll content and grain yield differences among the various nitrogen fertiliser rates. The highest grain yield (219.27 g.pot-1) was observed with N1, whereas the lowest (186.6 g.pot-1) was with N3. Similarly, irrigation frequencies significantly influenced chlorophyll content and cob characteristics, with I1 resulting in the highest grain yield (211.27 g.pot-1) and I3 the lowest (184.6 g.pot-1). Furthermore, the interaction between fertiliser application rates and irrigation frequencies had notable effects on various parameters, leading to the highest grain yield of 227.62 g.pot-1 with the combination of N1 and I1 and the lowest (168.00 g.pot-1) with N3 I3. The agricultural experiments were facilitated using the Matlab fuzzy toolbox, employing the Mamdani inference method. Fuzzy rules were delineated for nitrogen application rates and irrigation frequencies, with three fuzzy sets each. Membership functions were developed utilising Matlab's fuzzy interface system (FIS) editor and membership function editor, optimising leaf chlorophyll content, evaporation rate as input tiger N fertilisation, and irrigation frequencies as output for precise maize production in Bangladesh.
Suggested Citation
Bitopi Biswas & Mohammad Tariful Alam Khan & Mohammad Billal Hossain Momen & Mohammad. Rashedur Rahman Tanvir & Abu Mohammad Shahidul Alam & M Robiul Islam Islam, 2024.
"Advancements in fuzzy expert systems for site-specific nitrogen fertilisation: Incorporating RGB colour codes and irrigation schedules for precision maize production in Bangladesh,"
Research in Agricultural Engineering, Czech Academy of Agricultural Sciences, vol. 70(3), pages 155-166.
Handle:
RePEc:caa:jnlrae:v:70:y:2024:i:3:id:35-2024-rae
DOI: 10.17221/35/2024-RAE
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
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:caa:jnlrae:v:70:y:2024:i:3:id:35-2024-rae. 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.
We have no bibliographic references for this item. You can help adding them by using 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: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.