The Effectiveness of Soil Extracts from Selangor Peat Swamp and Pristine Forest Soils on the Growth of Green Microalgae sp.

Yaacob, Nor Suhaila; Ahmad, Mohd Fadzli; Sivam, Ashvini; Hashim, Emi Fazlina; Maniyam, Maegala Nallapan; Sjahrir, Fridelina; Dzulkafli, Noor Fazreen; Zamri, Wan Muhammad Ikram Wan Mohd; Komatsu, Kazuhiro; Kuwahara, Victor S.; Abdullah, Hasdianty

doi:10.3390/f13010079

Cited by 5 publications

(3 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The reserve's topography features undulating terrain interspersed with water bodies and intricate drainage patterns typical of peatland ecosystems. In terms of climate, the RMFR experiences a tropical rainforest climate with relatively high humidity and abundant rainfall throughout the year [18]. These climatic conditions, coupled with the presence of peat soils, contribute to the elevated risk of forest fires within the reserve.…”

Section: Data Preparationmentioning

confidence: 99%

Prediction of Peatlands Forest Fires in Malaysia Using Machine Learning

Sali

Noordin

et al. 2023

Forests

View full text Add to dashboard Cite

The occurrence of fires in tropical peatlands poses significant threats to their ecosystems. An Internet of Things (IoT) system was developed to measure and collect fire risk factors in the Raja Musa Forest Reserve (RMFR) in Selangor, Malaysia, to address this issue. In this paper, neural networks with different layers were employed to predict peatland forests’ Fire Weather Index (FWI). The neural network models used two sets of input parameters, consisting of four and nine fire factors. The predicted FWI values were compared with actual values obtained from the Malaysian meteorological department. The findings revealed that the five-layer neural network outperformed others in both the four-input and nine-input models. Specifically, the nine-input neural network achieved a mean square error (MSE) of 1.116 and a correlation of 0.890, surpassing the performance of the four-input neural network with the MSE of 1.537 and the correlation of 0.852. These results hold significant research and practical implications for precise peatland fire prevention, control, and the formulation of preventive measures.

show abstract

Section: Data Preparationmentioning

confidence: 99%

Prediction of Peatlands Forest Fires in Malaysia Using Machine Learning

Sali

Noordin

et al. 2023

Forests

View full text Add to dashboard Cite

show abstract

“…Research on microalgae has revealed that heavy metals can enter plant cells either through active transportation or endocytosis facilitated by plant chelating proteins, thereby mitigating the toxicity of heavy metals. However, when an excess of heavy metals accumulates, heavy metal ions bind to thiol groups within protein cysteine, disrupting the protein structure or displacing essential elements [64]. The emergence of new shoots indicates healthy growth and robust stress resistance in plants.…”

Section: New Shoot Growthmentioning

confidence: 99%

Enhancement of Phytoremediation of Heavy Metal Pollution Using an Intercropping System in Moso Bamboo Forests: Characteristics of Soil Organic Matter and Bacterial Communities

Bian,

Zhang,

et al. 2023

Forests

View full text Add to dashboard Cite

Heavy metal pollution in soil is a major global issue, and one effective method for addressing it is phytoremediation through bamboo planting. Nevertheless, there is a notable gap in our knowledge as no studies have explored the characteristics of soil organic matter (SOM) and the bacterial communities in bamboo forests during the remediation process. To bridge this knowledge gap, we conducted research to investigate the impact of different bamboo planting patterns on the SOM characteristics and microbial communities in soils contaminated with heavy metals. The contents of SOM and dissolved organic matter (DOM) in rhizosphere and non-rhizosphere soils differed significantly between monocropping and intercropping systems, with DOM accounting for only 1.7%–2.5% of SOM. Fourier transform infrared spectra showed that the contents of SOM polysaccharides C-O, carbonate C-O, aliphatic methyl, and methylene increased, while the aromatic C=C abundance decreased in the intercropping rhizosphere soil. The differences between bamboo cultivation patterns in the rhizosphere and non-rhizosphere soils were elucidated using the biomarkers, including MND1 and Nitrospira (non-rhizosphere), and Sphingomonas (rhizosphere). Heavy metals, DOM, SOM, and refined organic functional groups, especially C-O in polysaccharides and symmetric carboxylate, were the determining factors of soil bacterial communities. Compared to monocropping, intercropping increased the accumulation of Zn and Cd in bamboo shoots by 35% and 40%, respectively, and hence, intercropping soil, with a low toxicity, was suitable for bamboo shoot sprouting. Intercropping can alter the characteristics of SOM and bacterial communities and plays a vital role in phytoremediation and shoot growth in bamboo forests. Future studies on soil carbon dynamics and nutrient status during heavy metal remediation will improve our knowledge of soil transformation and its impact on soil ecosystem health and productivity.

show abstract

“…Also to soil improvement, extra fertilizer containing N, P and K elements is also good and important to give to plants to increase nutrient availability so that optimal biomass production implies increasing carrying capacity [52]. Very acidic soils are followed by very low to low macronutrient deficiencies [53][54][55].…”

Section: Plant Type Minimum Phmentioning

confidence: 99%

Effect of Soil Damage on Carrying Capacity of Biomass Production: A Lesson from Tanjung Selor District – Tanjung Redeb, Indonesia

Darma¹,

Fahrunsyah²

2022

ujar

View full text Add to dashboard Cite

Currently, land use is considered intensive for various purposes that affect the soil as the main series of land and the environment. The other side of the soil in Kalimantan is naturally formed from material that is poor in nutrients so it is not fertile and acidic. This study attempted to evaluate the status of soil damage to the carrying capacity for biomass production in Tanjung Selor District. The overlay analysis of land slope, rainfall, soil type and land cover in the form of a map produces indicative areas of low, medium and high damage. High damage indicative areas were selected for verification, observation and soil sampling to obtain soil damage parameter data, carried out in March 2020. Analysis of the relative frequency score of the damaged parameters aims to determine the status of carrying capacity and soil damage. The results of the study based on 10 soil damage parameters obtained a score of 6 with the status of lightly damaged soil damage, the main factor being soil acidity (R.I-a) with a high carrying capacity of 1,684 ha. The acidity factor with a pH of <4.5 (very acidic) has the most effect, 80% is damaged, but is relatively easy to repair. Efforts to improve cultivated plants are stressed by soil acidity by using soil amendments to raise the pH above the minimum range that is more suitable to increase biomass production and carrying capacity, namely agricultural lime and compost followed by N, P and K fertilization as needed.

show abstract

The Effectiveness of Soil Extracts from Selangor Peat Swamp and Pristine Forest Soils on the Growth of Green Microalgae sp.

Cited by 5 publications

References 67 publications

Prediction of Peatlands Forest Fires in Malaysia Using Machine Learning

Prediction of Peatlands Forest Fires in Malaysia Using Machine Learning

Enhancement of Phytoremediation of Heavy Metal Pollution Using an Intercropping System in Moso Bamboo Forests: Characteristics of Soil Organic Matter and Bacterial Communities

Effect of Soil Damage on Carrying Capacity of Biomass Production: A Lesson from Tanjung Selor District – Tanjung Redeb, Indonesia

Contact Info

Product

Resources

About