IDENTIFICATION AND ANALYSIS OF WEED VEGETATION AS Ganoderma PRESENCE MARKER ON OIL PALM PLANTATION

Abstract

Weeds on oil palm plantations can also be the host of Basal Stem Rot caused by Ganoderma. This study aims to identify and analyze of weed vegetation using visual estimation and squares method as Ganoderma presence marker on oil palm plantations. This research was conducted in block 17, 16, and 6 of VII afdeling, Rambutan Estate in Serdang Bedagai Regency on December 2017 to March 2018. This research used survey method with visual estimation and squares. The data used is absolute density, relative density, absolute frequency, relative frequency, important value indeks, Summed Dominance Ratio (SDR) and dry weight. Data analysis using IBM SPSS Statistics 20 software. The results showed that different weed species between oil palm was infected and uninfected by Ganoderma with visual estimation method is Cyclosorus aridus (14.78%) where as with squares method are Cyperus rotundus (10.60%), and Stenochlaena palustris (7.76%) with temperature range 28.67 to 30.80oC and moisture amount 60.67 to 77.33%.

Diversity of Forage Species in Oil Palm Plantation Area in Kolaka Regency

“…Protection of plants from pest and disease control is an aspect of technical measures that mostly affects growth and productivity [11]. Weed control is an effort to improve the competitiveness of staple crops and to weaken the competitiveness of weeds [12]. Weeds in oil palm plants such as Mikania micrantha can reduce the production of fresh fruit bunches by 20% [13].…”

The Fourier transform infrared spectroscopy from Diplazium esculentum and Rivina humilis analysis to reveals the existence of necessary components in oil palm plantations of Ganoderma boninense control

“…Only a few methods have been reported to detect this disease before symptoms manifest as fruiting bodies, including enzyme-linked immunosorbent assay (ELISA) (Kayalvizhi and Antony, 2011;Utomo and Niepold, 2000;Kandan et al 2009;Siddiqui et al 2021), polymerase chain reaction (PCR) (Chong et al 2011;Midot et al 2019;Bahari et al 2018;Goh et al 2016), sequencing (Hayati and Basyuni, 2019), laser machine learning (ML) through laser beam scanning (Husin et al 2020), hyperspectral imagery visible near-infrared (VIS-NIR) (Azmi et al 2020;Ahmadi et al 2017;Isha et al 2019), scanning electron microscopy (Alexander et al 2017), and network detection through Ganoderma selective media (GSM) network (Rakib et al 2014;Darus and Seman, 1992;Penido et al 2013). Furthermore, weeds as markers of the organism's presence based on dominant species have also been reported (Saragih and Purba, 2018), with the nutrients in weed leaves compared to infected and uninfected oil palm (Saragih and Purba, 2019). However, this method is expensive and time-consuming for large-scale applications.…”