Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content
This study developed a linear regression model to predict coconut stem diameter (D), height (H), and chlorophyll content (SPAD) based on environmental and treatment factors during two cultivation seasons (January-June 2023 and July-December 2023) at the Faculty of Engineering, Universiti Putra Malay...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Unique Scientific Publishers
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/118357/ http://psasir.upm.edu.my/id/eprint/118357/1/118357.pdf |
| _version_ | 1848867497598517248 |
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| author | Wayayok, Aimrun Wong, Mui Yun Sulaiman, Ahmad Syafik Suraidi Guo, Leifeng |
| author_facet | Wayayok, Aimrun Wong, Mui Yun Sulaiman, Ahmad Syafik Suraidi Guo, Leifeng |
| author_sort | Wayayok, Aimrun |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This study developed a linear regression model to predict coconut stem diameter (D), height (H), and chlorophyll content (SPAD) based on environmental and treatment factors during two cultivation seasons (January-June 2023 and July-December 2023) at the Faculty of Engineering, Universiti Putra Malaysia, Selangor, Malaysia. The experiment utilized a growing media treatment (M3) composed of 50% soil, 30% cocopeat, and 20% perlite. Key predictor variables included time (W), nitrogen (N), potassium (K), moisture content (MC), wind speed (WS), and electrical conductivity (EC). Regression analysis revealed significant relationships: time (W) positively influenced stem diameter (0.3875) and height (0.3329), while nitrogen (N) had a positive effect on diameter (0.08827). In contrast, potassium (K) negatively impacted both stem diameter (-0.03461) and height (-0.0505), as did moisture content (-0.01561) and wind speed (-0.3872). For chlorophyll content, time (W) (2.399) and electrical conductivity (EC) (0.0193) were positive predictors, while potassium (-0.3063) and wind speed (-3.416) exerted negative influences. ANOVA confirmed the significance of time, potassium, moisture content, and wind speed on growth parameters. Time emerged as a critical factor for coconut development, highlighting the necessity of managing these variables to optimize growth and chlorophyll content. These findings provide valuable insights for enhancing coconut cultivation strategies. |
| first_indexed | 2025-11-15T14:37:26Z |
| format | Article |
| id | upm-118357 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:37:26Z |
| publishDate | 2024 |
| publisher | Unique Scientific Publishers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1183572025-07-10T02:57:17Z http://psasir.upm.edu.my/id/eprint/118357/ Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content Wayayok, Aimrun Wong, Mui Yun Sulaiman, Ahmad Syafik Suraidi Guo, Leifeng This study developed a linear regression model to predict coconut stem diameter (D), height (H), and chlorophyll content (SPAD) based on environmental and treatment factors during two cultivation seasons (January-June 2023 and July-December 2023) at the Faculty of Engineering, Universiti Putra Malaysia, Selangor, Malaysia. The experiment utilized a growing media treatment (M3) composed of 50% soil, 30% cocopeat, and 20% perlite. Key predictor variables included time (W), nitrogen (N), potassium (K), moisture content (MC), wind speed (WS), and electrical conductivity (EC). Regression analysis revealed significant relationships: time (W) positively influenced stem diameter (0.3875) and height (0.3329), while nitrogen (N) had a positive effect on diameter (0.08827). In contrast, potassium (K) negatively impacted both stem diameter (-0.03461) and height (-0.0505), as did moisture content (-0.01561) and wind speed (-0.3872). For chlorophyll content, time (W) (2.399) and electrical conductivity (EC) (0.0193) were positive predictors, while potassium (-0.3063) and wind speed (-3.416) exerted negative influences. ANOVA confirmed the significance of time, potassium, moisture content, and wind speed on growth parameters. Time emerged as a critical factor for coconut development, highlighting the necessity of managing these variables to optimize growth and chlorophyll content. These findings provide valuable insights for enhancing coconut cultivation strategies. Unique Scientific Publishers 2024 Article PeerReviewed text en cc_by_nc_nd_4 http://psasir.upm.edu.my/id/eprint/118357/1/118357.pdf Wayayok, Aimrun and Wong, Mui Yun and Sulaiman, Ahmad Syafik Suraidi and Guo, Leifeng (2024) Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content. International Journal of Agriculture and Biosciences, 14 (3). pp. 507-517. ISSN 2305-6622; eISSN: 2306-3599 https://www.ijagbio.com/pdf-files/24-897.pdf 10.47278/journal.ijab/2025.037 |
| spellingShingle | Wayayok, Aimrun Wong, Mui Yun Sulaiman, Ahmad Syafik Suraidi Guo, Leifeng Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content |
| title | Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content |
| title_full | Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content |
| title_fullStr | Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content |
| title_full_unstemmed | Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content |
| title_short | Predictive modelling of coconut (Cocos nucifera L) growth parameters using linear regression: Insights into stem diameter, height, and chlorophyll content |
| title_sort | predictive modelling of coconut (cocos nucifera l) growth parameters using linear regression: insights into stem diameter, height, and chlorophyll content |
| url | http://psasir.upm.edu.my/id/eprint/118357/ http://psasir.upm.edu.my/id/eprint/118357/ http://psasir.upm.edu.my/id/eprint/118357/ http://psasir.upm.edu.my/id/eprint/118357/1/118357.pdf |