Abstract

Environmental concerns are growing about excessive applying nitrogen (N) fertilizers, especially in oil palm. Some conventional methods which are used to assess the amount of nutrient in oil palm are time-consuming, expensive, and involve frond destruction. Remote sensing as a non-destructive, affordable, and efficient method is widely used to detect the concentration of chlorophyll (Chl) from canopy plants using several vegetation indices (VIs) because there is an influential relation between the concentration of N in the leaves and canopy Chl content. The objectives of this research are to (i) evaluate and compare the performance of various vegetation indices (VIs) for measuring N status in oil palm canopy using SPOT-7 imagery (AIRBUS Defence & Space, Ottobrunn, Germany) to (ii) develop a regression formula that can predict the N content using satellite data to (iii) assess the regression formula performance on testing datasets by testing the coefficient of determination between the predicted and measured N contents. SPOT-7 was acquired in a 6-ha oil palm planted area in Pahang, Malaysia. To predict N content, 28 VIs based on the spectral range of SPOT-7 satellite images were evaluated. Several regression models were applied to determine the highest coefficient of determination between VIs and actual N content from leaf sampling. The modified soil-adjusted vegetation index (MSAVI) generated the highest coefficient of determination (R2 = 0.93). MTVI1 and triangular VI had the highest second and third coefficient of determination with N content (R2 = 0.926 and 0.923, respectively). The classification accuracy assessment of the developed model was evaluated using several statistical parameters such as the independent t-test, and p-value. The accuracy assessment of the developed model was more than 77%.

Highlights

  • Oil palm (Elaeis guineensis) is a species of palm that provides one of the leading vegetable oils produced globally, accounting for one quarter of global consumption and approximately 60% of international trade in vegetable oils [1]

  • The results showed that modified soil-adjusted vegetation index (MSAVI) had the highest coefficient of determination between the satellite data and the ground data

  • It is used to find any imbalanced interactions or antagonisms and to check whether the amount of fertilizers applied is suitable for the plants or not [67]

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Summary

Introduction

Oil palm (Elaeis guineensis) is a species of palm that provides one of the leading vegetable oils produced globally, accounting for one quarter of global consumption and approximately 60% of international trade in vegetable oils [1]. Malaysia and Indonesia are the main key players in the palm oil sector, and these two countries together account for about 90% of the global palm oil export. The oil palm industry is considered a very profitable one in Malaysia; the plantation of oil palm has increased significantly over the years [2]. From 2005 to 2015, the oil palm planted area has increased by 42% in the country. Malaysia has the second largest area under oil palm cultivation after Indonesia. The export trends of oil palm by-products increased by Agriculture 2020, 10, 133; doi:10.3390/agriculture10040133 www.mdpi.com/journal/agriculture

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