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INDONESIA
Jurnal Pertanian Agros
Published by Universitas Janabadra
ISSN : 25273655     EISSN : 25798782     DOI : https://doi.org/10.37159/jpa.v27i2.61
Core Subject : Agriculture,
Agriculture, Biological Sciences & Forestry
Melakukan evaluasi pengaruh pupuk kandang ayam dan NPKMg terhadap produktivitas tanaman aren. Sugar palm (Arenga pinnata Merr.) is a plantation commodity that is very beneficial ecologically and financially because it can adapt to various geographical conditions such as mountains, valleys, riverbanks, and undulating land. However, the development of this plant is still constrained by low cultivation intensification, unstructured planting patterns, and optimal land use, resulting in low productivity. Increasing the productivity of sugar palm plants can be achieved through intensive cultivation. The purpose of this study was to study how chicken manure and NPKMg fertilizer affect the growth of sugar palm plants and determine the best fertilizer dosage.
Arjuna Subject : Ilmu Pertanian dan Biologi (Semua) - Agronomi dan Ilmu Tanaman
Articles 41 Documents
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ANALISIS NILAI KONSTANTA DAUN TANAMAN BELIMBING DAN SAWO BERBASIS PENGOLAHAN CITRA DIGITAL Sadewa, Dzulkarnaen; Al Ramadhani, Farchan Mushaf; Sajuri
Jurnal Pertanian Agros Vol 27 No 3 (2025): EDISI JULI
Publisher : Fakultas Pertanian Universitas Janabadra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37159/jpa.v27i3.113

Abstract

Leaf area is an important parameter in plant physiology studies because it is directly related to photosynthetic activity and plant productivity. However, conventional methods for measuring leaf area still face limitations in terms of cost, equipment, and efficiency. This study aimed to analyze the leaf constant values of starfruit and sapodilla plants based on digital image processing as a foundation for applying the Montgomery method. A total of 40 leaf samples from each species were analyzed using digital imagery via ImageJ software to obtain the measured leaf area, which was then compared to the predicted leaf area using the Montgomery equation. The resulting leaf constants were 0.520 for starfruit and 0.642 for sapodilla, with a stable and consistent value distribution. Prediction accuracy evaluation using R², RMSE, NRMSE, NSE, and Willmott’s index showed low error rates and very high model efficiency. These findings suggest that the obtained leaf constants are reliable for rapid and non-destructive estimation of leaf area. This method has the potential for broader application in supporting precision agriculture and efficient monitoring of tropical plant growth.

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