Effects of Moisture Level on Nitrogen Availability in Tropical Peat Soil Cultivated with Oil Palm (Elaeis guineensis Jacq.)

Ariffin, Mohd Rizal; Ahmed, Osumanu Haruna; Isa, Isharudin Md; Khairuddin, Mohd Nizar

doi:10.17503/agrivita.v41i1.2007

Cited by 3 publications

(4 citation statements)

References 20 publications

(23 reference statements)

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“…Moisture content change in fertilizer pellet might happen during densification process, where it involves pressure and heat in pellet mill dies (Widyowanti et al, 2019). According to Arifin et al, (2019), moisture content has important role in nitrogen release control, and high moisture content decreases nitrate (NO 3 ) as much as 28 -50% from total availability, so it is suggested to apply N fertilizer with low moisture content.…”

Section: Resultsmentioning

confidence: 99%

The Potential of Biogas Slurry and Palm Oil Mill Effluent Slurry as Slow-Release Fertilizer Pellet Through Densification

2021

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Organic fertilizer can yield higher production compared to regular fertilizer if properly applied. Thus, it can be a solution to improve nutrient content of soil. The biggest source of bio slurry in plantation is from Palm Oil Mill Effluent (POME) and cow dung biogas. This research aimed to analyze the residue’s potential from the result of biogas processing and bio slurry from POME as slow-release fertilizer pellet. Bio slurry was processed into pellet through densification process using pellet mill. The research was arranged in a Randomized Block Design method with five slurry compositions as treatments, including 70:30, 60:40, 50:50, 40:60, and 30:70 (ratio of biogas slurry and POME slurry), each consisted of three replications. According to the data obtained, fertilizer pellets had characteristics of 25 – 29 mm of length, 5.23 – 5.85 mm of diameter, 0.44 – 0.53 g/cm3 of density, 54.78% - 81.96% of durability, and 7.81% - 8.57% of moisture content. Based on density and durability aspects, 30:70 composition was the higher. Macronutrient content of the five compositions were 1.88% - 2.72%, in which on day 22, N, P, and K release was 0.36 – 1.01%, 73.51 – 97.48%, and 3.19 – 7.85%, respectively. Meanwhile, on day 17, the nutrition solution conductivity of all compositions had already reached 0.80 – 1 mS/cm.

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Section: Resultsmentioning

confidence: 99%

The Potential of Biogas Slurry and Palm Oil Mill Effluent Slurry as Slow-Release Fertilizer Pellet Through Densification

2021

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“…Meanwhile, the fertilization package treatment significantly affected the weight of 100 seeds where the recommended fertilization package had the highest weight of 100 seeds 16.39 g. Salimi et al [25] reported that the character of seed weight per plant and weight of 100 seeds gave a greater contribution than other characters to the total diversity of soybeans. Exposure that is too short or too long will have an impact on decreasing production [26]. The results of the analysis of variance on yield showed that the treatment of various levels of shade on the Dena variety did not affected the yield (t ha -1 ), while the recommended fertilization package had a significant effect on the yield, where the highest yield was 1.82 tons.…”

Section: Seed Weight Weight Of 100 Seeds and Yield (T Ha -1 )mentioning

confidence: 96%

Adaptation test of shade-tolerant soybean to fertilization technology in coconut plantations, Aceh Province

Asis¹,

Ferayanti²,

Idawanni³

et al. 2021

E3S Web Conf.

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Soybean is an important commodity needed by people in Indonesian. Soybean production is currently decreasing every year because off decreasing land area. The available land in Indonesia is mostly used by farmers to cultivate crops that have the potential to meet their economic needs, so that very few farmers use their land for soybean crops. This study aimed to determine the adaptation of shade-tolerant soybean varieties to fertilization technology at various levels of shade coconut plant. The research was conducted at Bandar Baru District, Pidie Jaya Regency, Aceh Province on July to October 2019, with split plot design. The main plot is shade (N), namely N1: 0% shade (without shade); N2: 25% shade and N3: 50% shade, and subplot is the fertilizer package (P) namely P1: recommendation (NPK 150 kg ha-1, organic fertilizer 2 t ha-1); P2: specific location (urea 75 kg ha-1, SP-36 100 kg ha-1, KCl 100 kg ha-1). The results showed that the level of shade had no effect on soybean production, while the fertilization factor showed that the highest production was found in the recommended fertilizer package 1.82 t ha-1, different with the specific location fertilizer package.

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“…The parent material of peats contained less P and K contents than mineral soils. Owing to a slower release of peat mineralization process, available N in peat is under the OP sufficiency levels for producing high yields, which requires an additional N fertilization (Mutert et al, 1999;Ariffin et al, 2019). Consequently, under-fertilized OP often undergoes a hidden hunger and yield below the average.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, amelioration and fertilization are carried out in the fertilization/weeded cycle, whereas pruned fronds are stacked in the row between the OP tree. Moreover, the interrows and stacked fronds are often left overgrown by the understory's fast-growing weeds or planted with leguminous land cover crops (Ariffin et al, 2019;Luke et al, 2019;Agus et al, 2019). Based on that, total N, P, and K at the surface peat near oil palm tree were likely higher than the farther distance or deeper layer due to fertilizer addition and peat mineralization in the fertilization circle.…”

Section: Introductionmentioning

confidence: 99%

Identifying the Underlying Factors and Variables Governing Macronutrients in Cultivated Tropical Peatland Using Regression Tree Approach

Pulunggono¹,

Madani²,

Zulfajrin³

2022

CELEBES Agricultural

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The capability of machine learning/ML algorithms to analyze the effect of human and environmental factors and variables in controlling soil nutrients has been profoundly studied over the last decades. Unfortunately, ML utilization to estimate macronutrients and their governing factors in cultivated tropical peat soil are extremely scarce. In this study, we trained regression tree/RT, ML-based pedotransfer models to predict total N, P, and K in peat soils based on oil palm/OP and OP+bush datasets. Our results indicated that the dataset might contain outliers, non-linear relationships, and heteroscedasticity, allowing RT-based models to perform better compared to multiple linear regression/MLR models (as a benchmark) in estimating total N and P in both datasets, contrastingly, not in K. The difference of important variables in each RT-based model partially showed the vital role of land use in nutrient modeling in peat. The depth of sample collection, organic C, and ash content became the prominent factor and variables in regulating the entire predicted nutrients. Meanwhile, the distance from the oil palm tree and pH were the salient features of total P prediction models in OP and OP+bush sites, respectively. This study proposed employing ML-based pedotransfer models in analyzing and interpreting complex tropical peat data as an alternative to linear-based regression. Our initial study also shed more light on the development possibility of the pedotransfer models that agricultural practician, researchers, companies, and farmers can use to predict macronutrients, both in tabular and spatial terms, in cultivated tropical peatlands

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Effects of Moisture Level on Nitrogen Availability in Tropical Peat Soil Cultivated with Oil Palm (Elaeis guineensis Jacq.)

Cited by 3 publications

References 20 publications

The Potential of Biogas Slurry and Palm Oil Mill Effluent Slurry as Slow-Release Fertilizer Pellet Through Densification

The Potential of Biogas Slurry and Palm Oil Mill Effluent Slurry as Slow-Release Fertilizer Pellet Through Densification

Adaptation test of shade-tolerant soybean to fertilization technology in coconut plantations, Aceh Province

Identifying the Underlying Factors and Variables Governing Macronutrients in Cultivated Tropical Peatland Using Regression Tree Approach

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