Assessment Of Biomass Research Articles

A method for identifying and segmenting branches of Scots pine (Pinus sylvestris L.) trees using terrestrial laser scanning

Abstract Terrestrial laser scanning (TLS) has been adopted as a feasible technique to characterize tree stems while the characterization of trees’ branching architecture has remained less explored. In general, branching architecture refers to the spatial arrangement of branches and their characteristics that are important when exploring the eco-physiological functioning of trees or assessing tree biomass and wood quality. Our aim was to develop a point cloud processing method for identifying and segmenting individual branches from TLS point clouds. We applied a Cartesian-to-cylinder coordinate transformation and a simple morphological filtering for stem surface reconstruction and stem-branch separation. Then branch origins were identified as their intersections with the stem surface, and individual branches were segmented based on their connectivity with the branch origins. The method, implemented in MATLAB and openly available, was validated on a 0.4-ha mature and managed southern boreal forest stand. The branch identification performance was assessed based on visual interpretation of 364 randomly sampled stem sections from 100 Scots pine (Pinus sylvestris (L.)) trees that were inspected for branch identification accuracy. The results showed that the branches could only be identified up to the height where the stem could be reconstructed. For 90% of the trees, this threshold ranged between 59.3% and 81.2% relative tree heights. Branches located below this threshold were identified with a recall of 75%, a precision of 92%, and an F1-score of 0.82. Based on our study, it appears that in a managed Scots pine stand, most of the branches can be identified with the developed method for the most valuable stem part eligible for logwood. The findings obtained in this study promote the feasibility of using TLS in applications requiring detailed characterization of trees. The developed method can be further used in quantifying the characteristics of individual branches, which could be useful for biomass and wood quality assessment, for example.

A Review on Hydrogen Production from Biomass and Commercialization Assessment Through Technology Readiness Levels (TRLs)

A Review on Hydrogen Production from Biomass and Commercialization Assessment Through Technology Readiness Levels (TRLs)

Response of micropropagated tissue culture banana (Musa spp.) to acclimatization using arbuscular mycorrhiza fungi

The production of banana seedlings through tissue culture provides a reliable source of numerous, disease free, quality plantlets. However, the micropropagation process is faced with a number of challenges. In this study we are focusing on the improvement of survival and growth of the resultant plantlets during the acclimatization process. The viability of arbuscular mycorrhiza fungi (AMF) symbiont in the acclimatization process was assessed. Tissue culture bananas (Kienyeji, Kiganda and Ng’ombe local cultivars) were inoculated with single species AMF Rhizophagus irregularis and Funneliformis mosseae as well as commercial AMF Rhizatech. The survival rate was assessed and plant growth evaluated at a two week interval. Destructive harvesting was conducted followed by assessment of root, shoot and total biomass. The results demonstrated that Kiganda treated with Rhisophagus irregularis and Funneliformis mossae recorded better survival rates compared to treatments with NPK fertilizer and commercial AMF (Rhizatech). Kienyeji cultivar however had a better survival rate when treated with commercial AMF (Rhizatech). Ng’ombe cultivar was very resilient having 100 % survival rate when treated with indigenous AMF, commercial AMF (Rhizatech) and NPK. There were significant differences in the shoot dry weight, root dry weight and biomass in the three banana cultivars. Kiganda and Kienyeji cultivars had the highest biomass when treated with Funneliformis mossae of 0.52 g and 0.83 g respectively. The results in this study confirm that the use of AMF in the acclimatization process improves the overall seedling output of the micropropagation process during the nursery stage of production.

Linking soil physical quality to shoot and root biomass production in scenarios of sugarcane straw removal

Understanding how sugarcane straw removal affects soil physical attributes and root development over successive cultivation years is critical for sustainable straw-based bioenergy production. The aim of this study was to evaluate the effects of straw removal on soil physical quality and its relationship with sugarcane root development and crop yield in soils with contrasting textures. Three straw removal rates corresponding to total removal (TR), moderate removal (MR), and no removal (NR) were arranged in a randomized block design with four replicates. Soil was sampled at depths of 0–0.10, 0.10–0.20, and 0.20–0.40 m to determine soil bulk density, macro- and microporosity, soil penetration resistance, and carbon stock. Annual assessments of sugarcane root and stalk dry biomass were conducted. Overall, excessive straw removal rates were detrimental to soil porosity, C stock, and increased bulk density in the surface layer over successive years compared to moderate and no removal rates. Higher soil penetration resistance levels were observed under total removal, reaching values of 2.6 MPa in the 0–0.10 m layer in both soils. Average reductions in root biomass of 23–33% were verified at moderate and total removal rates in both soils, which affected sugarcane stalk yield, with maximum losses of 24% over crop cycles in the clayey soil. In the sandy loam soil, increases in soil C were correlated with reduced soil penetration resistance, which positively influenced root biomass production. Soil compaction over the years was particularly detrimental in the clayey soil, where the biomass production performance of sugarcane roots and stalk yield decreased in response to increased soil bulk density. Our results suggest that reductions in root biomass may occur in response to straw removal, as well as the loss of soil physical quality induced by soil compaction, with negative effects on C accumulation and soil resistance to root penetration.

Evaluating the Transferability of Spectral Variables and Prediction Models for Mapping Forest Aboveground Biomass Using Transfer Learning Methods

Forests, commonly viewed as the Earth’s lungs, play a crucial role in mitigating greenhouse gas emissions, regulating the globe, and maintaining ecological equilibrium. The assessment of aboveground biomass (AGB) serves as a pivotal indicator for evaluating forest quality. By integrating remote sensing images with a small number of ground-measured samples to map, forest AGBs can significantly reduce time and labor costs. Current research mainly focuses on improving the accuracy of mapping forest AGBs, such as integrating multiple-sensors remote sensing data and models. However, due to uncertainties associated with remote sensing images and complexities inherent in forest structures, the accuracy of mapping forest AGBs is constrained by both the quantity and distribution of ground samples available. The development of transfer learning methods can fully utilize ground-based measurement data and enable the application of samples across regions and time. To evaluate the potential of transfer learning methods in mapping forest AGBs, this study conducted a spatial–temporal transfer of spectral variables (SVs) and prediction models (PMs) using a direct-push transfer method, and a new evaluation metric, relative change of R-squared (RCRS), was proposed to assess the transferability of SVs and PMs. The results showed that the transferability of SVs and PMs in the spatial target domain is obviously greater than that in the temporal target domain. Compared to the temporal target domain, the RCRS for transfer SVs in the spatial target domain was lower by 20.89 (oak) and 20.88 (Chinese fir) and for transfer PMs by 24.16 (oak) and 24.79 (Chinese fir). Tree species is also one of the main factors affecting the spatial and temporal transfer of SVs, and it is challenging to transfer SVs between different tree species. The results also show that nonparametric models have better generalization performance, and their transferability is much greater than that of parametric models.

Forest biomass assessment combining field inventorying and remote sensing data

Abstract Forests offer high potential for the fight against climate change. However, forests are faced with increased deforestation. REDD+ is a financial mechanism that offers hope to developing countries for tackling deforestation. Aboveground (AGB) estimation, however, is necessary for such financial mechanisms. Remote sensing methods offer various advantages for AGB estimation. A study, therefore, was conducted for the estimation of AGB using a combination of remote sensing Sentinel-1 (S1) and Sentinel-2 (S2) satellite data and field inventorying. The mean AGB for Sub-tropical Chir Pine Forest was recorded as 146.73 ± 65.11 Mg ha−1, while for Sub-tropical Broadleaved Evergreen Forest it was 33.77 ± 51.63 Mg ha−1. Results revealed weak associations between the S1 and S2 data with the AGB. Nonetheless, S1 and S2 offer advantages such as free data resources that can be utilized by developing countries for forest biomass and carbon monitoring.

Assessment of occurrence, diversity, and biomass of macroinvertebrates in Swiss groundwater systems using citizen science data

Groundwater is a vast ecosystem harboring a high diversity of specialized taxa. Despite its diversity, groundwater is a still relatively unexplored and threatened ecosystem. Especially the linkage of groundwater with other ecosystems remains largely unknown from the perspective of groundwater fauna. Here, we used citizen science data to get a first baseline knowledge of the occurrence, diversity, and biomass of major macroinvertebrate groups found in shallow groundwater systems of Switzerland. We investigated all organisms collected from the groundwater in 346 spring catchment boxes of municipal drinking water providers. We morphologically identified the organisms on a broad taxonomic level and estimated their biomass and pigmentation using automated image processing. Crustaceans, particularly Niphargus and groundwater isopods, were the most common taxa of obligate groundwater organisms. We also found a surprisingly high number of macroinvertebrates associated with surface and subsurface ecosystems. These taxa might be accidentally entering the groundwater or use it as temporary habitat. In both cases they possibly contribute essential allochthonous energy imports from the surface. We found a positive relationship between the estimated biomass of macroinvertebrates in the samples and the occurrence and abundance of Niphargus. Owing to the widespread occurrences of surface and subsurface macroinvertebrates in our groundwater samples, our study provides evidence for common interactions between groundwater, soil, and surface ecosystems.

Multivariate combined optimization strategy and comparative life-cycle assessment of biomass and plastic residues via microwave co-pyrolysis approach towards a sustainable synthesis of renewable hydrocarbon fuel

The present study revealed the optimum co-pyrolysis process condition and simultaneously evaluated the environmental impact potential during co-valorisation of electronic plastic waste (WEEP) with Hydnocarpus de-oiled seed cake (HDSC) to produce renewable hydrocarbon fuel. In this work, the primary co-pyrolysis process parameters such as operating temperature, mixture ratio, and catalyst loading were modeled and optimized using a combined approach of both Response Surface Methodology (RSM) and Artificial Neural Network (ANN). In the optimized condition, a maximum pyrolysis oil yield of 30.79 wt% was achieved at an operating temperature of 530 °C, a mixture ratio of 0.49, and catalyst loading of 20 wt%. The obtained co-pyrolysis products were characterized to evaluate their physiochemical properties. Finally, a detailed life cycle assessment (LCA) of the scaled-up microwave-assisted co-pyrolysis plant has been modeled, and the result revealed that the emission levels of 771.95 kg CO2 eq, 3.11 kg SO2 eq, 1.69 kg PO4 eq, 338.59 DCB eq, and 0.11 kg C2H4 eq were projected for processing 1 tonne of feedstock. Further, sensitivity analysis revealed that a decrease of 15% in electricity consumption results in a reduction of the overall environmental impact by 13.69%. Above results demonstrate that microwave co-pyrolysis of biomass with plastic waste holds great potential for positive energy production and negative emission technology when compared to other waste management methods. Hence, this investigation paves the way for the sustainable conversion of e-waste plastic and biomass residue into renewable fuel and helps to achieve the sustainability goal of reducing GWP emissions.

Assessment of Cu(II) impact on aerobic sludge biomass and its post-exposure self-recovery potential

Heavy metals are released from various sources, including metal plating, potentially at a small-scale industrial level, and from automobile service and repair workshops, paint works, etc., spread across the city. Being part and parcel of the city, the wastewater from these metallic sources finds its way into the sewage system and can potentially disrupt biological sewage treatment plants. Therefore, conducting health and quality assessments of the sludge biomass becomes crucial to ensure the effective operation of these treatment plants and to maintain environmental and public health standards. In this study, impacts of Cu(II) (10, 20, 40, and 80 mg/L) exposure on sludge biomass have been investigated, and the potential of self-recovery of sludge biomass was explored when Cu(II) exposure is stopped. Reactors have been operated for 0–25 d with Cu(II) (termed as stressed phase) and then another 29 d without Cu(II) (termed as recovery phase) in the feed. During stressed phase operation, Cu(II) stressed reactors have shown 39–75 % chemical oxygen demand (COD) removal, compared to 91 % for control. Biomass activity and ECatalase activity have been inhibited under Cu(II) stress with changes in microbial community structure. During the recovery phase, Cu(II) stressed reactors have shown 41–82 % COD removal, whereas the control reactor has shown 91 % COD removal. A low sludge volume index (SVI) and high biomass interface settling velocity (ISV) with increased biomass activity have been obtained for biomass exposed to 10 and 20 mg/L of Cu(II). Lower Cu(II) doses have led to partial recovery of enzyme activity and microbial community structure, but higher doses have shown incomplete recovery. The study shows the impact caused by Cu(II) metal in a biological wastewater treatment reactor. Through comprehensive analysis of basic and advanced physico-chemical and biological parameters, the study recommends preliminary and confirmatory tests to know metallic ingress through wastewater influent in a treatment system. Advanced knowledge about metallic ingress will be useful for operators to take necessary steps for the sustainable operation of wastewater treatment systems.

Comprehensive environmental and techno-economic feasibility assessment of biomass- solar on grid hybrid power generation system for Burdur Mehmet Akif Ersoy University Istiklal Campus

The worldwide use of clean and environmentally friendly renewable energy sources, has been increasing to prevent global warming and climate change. In this study, a hybrid renewable energy system (HRES) including biomass and solar as the source, has been investigated for Mehmet Akif Ersoy University Istiklal Campus in Burdur, Türkiye. The campus has an animal farm consisting of 300 cattle and 200 sheep. Therefore, manure of the animals will be used as the resource for biomass generation. HOMER software is used to simulate the system and to find the size and the quantity of the equipment according to the meteorological and biomass capacity of the campus. The optimum system is determined by means of net present cost (NPC) and the cost of energy (COE). In the simulation, wind energy is also investigated but since the wind speed is not sufficient to produce energy in the region, it is not considered in the optimum system. The optimum system is determined to be grid connected biomass-solar system with 5000 kW PV panels and a 1500 kW biomass generator assisted by the grid of 3000 kW. Also, the NPC of the system is estimated to be USD 18.800.000 and the COE for the system is calculated as 0,107 USD/kWh. The system also reduces the emissions causing the global warming.

Energy recovery and GHG impact assessment of biomass, polymers, and coal

In recent decades, rising energy consumption, population growth, and material production have contributed to environmental degradation. Harnessing the chemical energy in these materials in a circular economy can mitigate these issues. While recycling processes recover valuable constituents, significant post-recycling fractions remain viable for energy recovery. This study investigates the energy recovery potential from biomass materials via combustion, gasification, and anaerobic treatment, and from polymers and coal through combustion and gasification. Some materials not typically considered for combustion, such as food and green waste, are included due to their potential processing in combustion plants. Using thermodynamic principles, we assess the limits and opportunities for sustainable energy recovery across 200 materials, identifying correlations between the heating value and compositional analyses. The study also estimates the potential products and environmental impacts of energy production from these materials. Despite their lower heating value, biomass materials offer considerable net carbon reductions, but land use, water consumption, public health issues, and feedstock supply risks warrant consideration. Biomass combustion yields lower carbon emissions than polymer or coal combustion. Biomass and polymer gasification show high potential due to their higher H2/CO ratios. Anaerobic treatment of biomass materials generates significant methane, offering modest energy output. Synthetic polymers possess high heating values, comparable to fossil fuels, and provide net CO2 emission benefits, although substantially lower than those of biomass materials. Biomass combustion or gasification results in significantly lower NOx and SOx emissions compared to polymers and coal. Accounting for energy output, biomass gasification generates the lowest emissions per MJ.

Biomass Assessment and Optimization of Alcaligenes faecalis Isolated from some Nigerian Mining Sites for Heavy Metal Uptake Using Response Surface Methodology Model

In this study, we investigated the heavy metal absorption of Alcaligenes faecalis strain U.B.I., a bacteria isolated from a mining site, under different environmental conditions. We utilized both conventional and molecular techniques to identify the bacteria and employed response surface methodology (R.S.M.) to determine optimal environmental conditions for heavy metal absorption. Our analysis revealed that the heavy metal-tolerant bacteria belong to the Proteobacteria, specifically the Betaproteobacteria order in the Burkholderiales family. Additionally, the bacteria’s phylogenetic characteristics indicated a close relationship between the Aeromonas sp. cluster and members of the Aeromonadaceae family. Our results showed that the biomass A. faecalis strain U.B.I. had an optimal potential for chromium (Cr+) absorption at 93.0%. We also conducted tests on the biomass under optimized conditions for lead (Pb2+) absorption using R.S.M., resulting in a mean heavy metal uptake of 89.99%. Furthermore, we analyzed the surface functional groups after interaction with heavy metals and observed a significant shift in position of the functional groups. The O-H stretch and H-bonded at the 3268 cm1 position, while C=C stretch and N-O asymmetrical stretch/C-O stretch occurred at positions 2195 cm-1 and 1629 cm-1 of the spectra, respectively. Our findings suggest that the biomass of A. faecalis strain U.B.I. has potential for heavy metal bioremediation and can be used for heavy metal biosorption under various environmental conditions.

Seasonal Assessment of Biomass and Carbon Sequestration of Herbaceous Vegetation and Litter Layer in Homegarden Agroforestry System of Sam Higginbottom University of Agriculture, Technology and Sciences Campus, Prayagraj, India

An increase in greenhouse gases (GHGs) in the atmosphere, such as CO2, is what drives global warming. Strong carbon management is the first step in helping to stop climate change, safeguard human health, and create profitable businesses. A key strategy for lowering greenhouse gases emissions is carbon capture and storage. The study aimed to investigate the carbon sequestration potential of the herbaceous vegetation and litter layer in home garden agroforestry systems during the rainy season, winter season, and summer seasons in the SHUATS (Sam Higginbottom University of Agriculture, Technology and Sciences) Campus, Prayagraj. The total dry weight of the herbaceous layer and litter layer was measured, and the corresponding carbon sequestration values were calculated. During the rainy season, the herbaceous layer exhibited a total dry weight ranging from 0.31 kg m-2 to 0.36 kg m-2, resulting in carbon sequestration values ranging from 1.83 Mg C ha-1 to 2.13 Mg C ha-1. The litter layer had a total dry weight ranging from 0.13 kg m-2 to 0.16 kg m-2, contributing to carbon sequestration values ranging from 0.76 Mg C ha-1 to 0.92 Mg C ha-1.In the winter season, the herbaceous layer demonstrated a total dry weight ranging from 0.22 kg m-2 to 0.28 kg m-2, resulting in carbon sequestration values ranging from 1.29 Mg C ha-1 to 1.65 Mg C ha-1. Similarly, the litter layer exhibited a total dry weight ranging from 0.18 kg m-2 to 0.216 kg m-2, contributing to carbon sequestration values ranging from 1.05 Mg C ha-1 to 1.25 Mg C ha-1.During the summer season, the herbaceous layer displayed a total dry weight ranging from 0.303 kg m-2 to 0.361 kg m-2, resulting in carbon sequestration values ranging from 1.76 Mg C ha-1 to 2.10 Mg C ha-1. The litter layer had a total dry weight ranging from 0.16 kg m-2 to 0.24 kg m-2, contributing to carbon sequestration values ranging from 1.00 Mg C ha-1 to 1.32 Mg C ha-1. The results indicate that the herbaceous layer and litter layer of home garden agroforestry systems in the SHUATS Campus, Prayagraj, have the potential to sequester significant amounts of carbon during different seasons. This highlights the importance of home gardens in mitigating climate change and promoting sustainable land management practices.

Overexploitation of round sardinella may lead to the collapse of flat sardinella: What lessons can be drawn for shared stocks

This paper describes the fisheries and presents quantitative stock assessments for two stocks of Sardinella in the waters of NW Africa. More robust stock assessments are now possible because of improved sampling in Mauritania and Senegal. Round sardinella (S. aurita), which has a wider distribution than flat sardinella (S. maderensis), is the most important species targeted by the different artisanal and industrial fleets. The industrial fleet is located beyond 13 miles from the coast, taking mainly adults. The average size in the offshore fishery, although it has decreased, remains above 26 cm. The species is also exploited by an artisanal fleet using small purse seiners. Two types of assessment model were applied: a production model and size-based model. The abundance indices were consistent, and showed a continuous decline, increasing in rate in recent years. The Just Another Bayesian Biomass Assessment (JABBA) model (applied for the first time) appeared to be appropriate for the abundance indices (Root Mean Squared Error (RMSE) 18.3–19.2 % for the two models). The results of the two models are consistent in showing increasing fishing mortality and declining biomass for both stocks over the time series. According to the JABBA model, the situation for the round sardinella stock is now critical (biomass at approximately 5 % of unexploited biomass (B0) and 10 % of biomass capable of producing maximum sustainable yields (Bmsy), with fishing mortality 2.5 times above Fmsy), and the flat sardinella is also overfished and suffering massive overfishing (B estimated at 18 %B0 and 25 %Bmsy, with fishing mortality more than 11 times above Fmsy). The results of the Length-based Bayesian Biomass (LBB) model are much more optimistic. It still concludes that both stocks are suffering overfishing (round sardinella F at ∼1.4 times Fmsy proxy, flat sardinella ∼2.2 times Fmsy proxy), but estimates that only the flat sardinella is overfished (B 28%B0 and 80 %Bmsy), while the round sardinella stock is not overfished (B 40 %B0 and 120 %Bmsy). However, these results are not consistent with the abundance index from acoustic surveys (used in the JABBA model) and overall are thought to be less robust. Signs of heavy exploitation have been observed for round sardinella for several years. This situation has been exacerbated since the arrival in late 2016 in the Mauritanian zone of efficient semi-industrial purse seiners targeting small pelagics. The various indirect assessment models used show a difficult stock situation for the round sardinella, on which many fishing communities in the area depend. Abundance indices from acoustic survey confirm the state of overexploitation of this resource. This situation has directed effort towards the flat sardinella, which is characterized by a more coastal distribution and limited migration. This species has been showing signs of overexploitation since 2019. We highlight this result for flat sardinella, which was previously not thought to be overexploited, and propose that managers should also consider how the estimated maximum sustainable catch and fishing mortality can be appropriately distributed between the different fleets in different countries, to ensure that future industry planning in the countries of the region is compatible with the sustainability of these critical stocks. This is a very complex task, as it involves not only discussions between neighboring countries, but also difficult decisions within countries about the economic and socio-economic importance of different fisheries sectors. It is essential that these reflections start immediately.

Species-Specific Allometric Equations, Biomass Expansion Factor, and Wood Density of Native Tree Species in the Dry Afromontane Forest of Ethiopia

A forest is a storehouse of carbon released from different sources when the activities of sustainable forest management, planting, and rehabilitation exist. However, few allometric equations are present to determine its contribution to carbon reduction. The target of the study was to develop species-specific allometric equations and establish a database for biomass expansion factor and wood density for five tree species grown in the dry Afromontane forest of Ethiopia. A direct or destructive sampling method was used on 62 trees from different diameter classes. The diameter at breast height and the total height of selected trees ranged from 7 to 48 cm and 6.7 to 23.4 m, respectively. Trees were felled and divided into various biomass sections. Stem and big branch discs were sampled to determine the wood density and volume of the trees. Sample wood and foliage were oven-dried for three days and two days at 105°C and 70°C, respectively, to get their dry weight. Total above-ground biomass was regressed using diameter at breast height, total height, wood density, and average crown diameter as independent variables. R software version 4.0.1 was used to fit the biomass equations. The best biomass models were determined to have lower AIC and RSE and highest adj. R2. The biomass expansion factor and wood density of five tree species ranged from 1.19 to 1.40 and 0.53 to 0.74 g/cm−3, respectively. Species-specific allometric equations were better than both mixed species and pan tropical models for the assessment of above-ground biomass in the Chilimo dry Afromontane forest of Ethiopia.

Integrated application of morphological, anatomical, biochemical and physico-chemical methods to identify superior, lignocellulosic grass feedstocks for bioenergy purposes

Grasses have sufficient potential to be used in the biofuel industry due to many reasons. Hence, systematic assessments of the lignocellulosic biomass obtained from six grasses namely Arundo donax, Chrysopogon zizanioides, Coix lacryma-jobi, Pennisetum purpureum, Saccharum spontaneum, and Sorghum bicolor have been performed to assess their potential for bioethanol production. Selected morphological (height, internode diameter, number of internodes, fresh biomass, dry biomass, total volatile matter), anatomical (vascular bundle, stain intensity), analytical (crystallinity index of cellulose, thermal stability, hemicellulose, moisture content) and biochemical (α-cellulose, acid insoluble lignin) parameters were investigated and statistically analysed to detect the superior grass species. The study indicates that S. spontaneum harbours promising biofuel potential by having high dry biomass (56.33 g), α-cellulose (55.88–67.76%), but lower thermal stability (Tmax: 344.37 °C). Comparable ligno-cellulose properties with respect to dry biomass (54.60 g), α-cellulose content (45.95–64.14%), Tmax (360.51 °C) have been observed for A. donax. However, relatively higher lignin contents (∼17–23%) and crystalline cellulose (43.63%–46.96%) in S. spontaneum and A. donax might have resulted into lesser saccharification yield (216.04–230.08 mg/g). On that aspect, S. bicolor and C. lacryma-jobi might be useful since they possessed lower lignin (14.03–16.56%) and crystalline cellulose (32.51–33.02%) leading to higher glucose yield (263–420.06 mg/g). Taken together, this study indicates that integration of morphological, biochemical, and analytical properties of biomasses are complex, yet useful to predict a ‘superior donor plant’ for bioenergy purposes.

Semi-empirical SAR vegetation index for crop discrimination based on biomass in semi-arid region: A case study in Perambalur district, India

Crop discrimination helps monitor crops and strengthen the agricultural industry to secure food supplies. From existing crop-related studies and observations, found that vegetative Empirical models were limited in crop classification for Kharif and Rabi season crops based on biomass. To improve biomass assessment, this study proposes a modified Vegetation Index using the deviation factor from the plot between the Dual Polarization SAR Vegetation Index (DPSVI) and the Dual Polarimetric Radar Vegetation Index (DpRVI). The deviation factor corrects the difficulties in the lower and higher ranges and is found to be 0.5 for Kharif and Rabi at the harvest stage. Performance of Integrated SAR Vegetation Index carried out to both seasons and shows Kharif (R2 = 0.83), Rabi (R2 = 0.87). In addition, cross-validation with Sentinel-2 derived Normalized Difference Vegetation Index, which has R2 values of 0.84 and 0.86 for Kharif and Rabi seasonal crops respectively. A correlation was performed to assess the capability of the proposed model for individual crops and found that good correlation with vertically grown Kharif and rabi crops except for Sesamum Indicum. A classification capability of the Kharif (76%) and Rabi (84%) crops and variation shows crops are healthy and have more greenery. From the results, a modified measure outperformed than DPSVI and DpRVI at the harvest stage for a selected crop in the above season and proved an alternate.

Estimation of cellular carbon content based on the cell biovolume of microalgae from a eutrophic estuary (Sea of Marmara, Türkiye).

The cellular carbon content based on the cell biovolume of a total of 61 microalgal species determined in a eutrophic estuary (Golden Horn, Sea of Marmara) was estimated in seawater samples taken during two different sampling periods. Cell biovolume according to geometric dimensions of the cells was then converted to phytoplankton carbon using an appropriate conversion factor. The range of diatom biovolume, in which the majority had small cell sizes (<50μm), was much wider than that of dinoflagellate biovolume, in which the majority had large cell sizes (>50μm). The cell biovolume and carbon content ranged from 35 to 4.88 × 105μm3 and 5 to 1.18 × 104 pgC cell-1 for diatoms and from 3.66 × 102 to 8.68 × 105μm3 and 55 to 8.14 × 104 pgC cell-1 for dinoflagellates, respectively. The mean carbon density for diatoms and dinoflagellates (excl. Noctiluca scintillans) varied between 0.027 and 0.099 pgC μm-3 0.096 and 0.136 pgC μm-3, respectively. The mean cell carbon content and carbon density of dinoflagellates (6.73 × 103 pgC cell-1 and 0.115 pgC μm-3) were approximately 10 and 2 times greater than those of diatoms, respectively. The carbon content of the other phytoflagellates was lower, whereas their carbon density was higher. As a result, the findings from this study will provide a significant contribution to the assessment and estimation of carbon biomass during algal blooms in this study area.

Allometric models for biomass prediction of Hevea brasilliensis

AbstractTrees contribute to combating global warming by absorbing CO2, thus enhancing the quality of the environment. Sri Lanka maintains about 112,000 ha of Hevea brasiliensis (rubber) plantations, where 85.7% is in the wet zone. When rubber trees decline in latex production, after 30–33 years of planting, they are harvested to regenerate the next cycle. Rubber timber in Sri Lanka is used mainly for manufacturing interior parts of furniture, tool handles, and toys, leaving minimal chances for the emission of CO2 by combustion. Therefore, rubber is a good source of carbon sequestration, which can be used to earn additional benefits for the farmers. Estimating tree biomass helps to assess the carbon sequestration of those trees. Therefore this study aimed to build allometric models to predict the biomass using diameter at breast height (dbh) and total tree height (h). Since uprooting rubber trees is not allowed till maturity, whole‐tree, above‐ground, and stem biomass prediction models were built by uprooting ten 30‐ and 31‐year‐old trees from two rubber estates of the low country wet zone of Sri Lanka. For the rest of the ages, dbh and h prediction models were built by age using data collected from six age classes of rubber trees from the same two estates so those variables could be used as inputs to the biomass prediction models. For dbh and h models, Michaelis–Menten functions performed better than power‐law functions. Biomass was estimated for the stem and large branches by converting respective volumes to weights. Weight measurements were taken directly for biomass assessment for small branches, foliage, and roots. The quality of models was determined based on both qualitative and quantitative evaluations. The finding proved that the biomass of rubber plantations could effectively be estimated by dbh and h over time.

Two decades of carbon dynamics in an actively-managed, naturally-regenerated longleaf/slash pine forest

Naturally regenerated pine ecosystems cover 11.7 Mha of the southeastern United States, comprising 13.8% of the forested land, and represent an important component in the carbon balance for the region. These forests are exposed to strong climatic variability from extreme multiyear droughts to above average precipitation years, many are actively managed with prescribed fire and some modification of tree density by cutting. This study is unique in assessing the effects of management and climatic variability for two decades on the carbon (C) dynamics and long-term net ecosystem C balance (NECB) for an actively-managed naturally regenerated pine ecosystem. We used 21 years of eddy covariance estimates of net ecosystem C production (NEP), combined with periodic tree inventories, understory biomass and forest floor assessments. Forest management included six prescribed fire cycles on a three-year rotation beginning in the third year of the study, and a preparatory cut which reduced basal area by 20% from 17.05 ± 0.66 m2/ha during the spring of 2016. The mean annual NEP was 3.32 ± 1.37 Mg C/ha yr−1, with a range of 5.35 Mg C/ha (1.30 to 6.65 Mg C ha/yr), was not significantly affected by fire and was mainly controlled by water availability. A combination of aboveground C assessments (tree and understory) and NEP indicates that C stored belowground accounted for 23% of NEP, with part of this used to support aboveground understory growth after fire. Net ecosystem carbon balance (NECB, integrated NEP and C losses from management) fluctuated in a range of 15.5 Mg Cha−1 (6.7 to −8.8 Mg C ha -1) and was sensitive to management. However, a higher NECB during the second decade than in the first (15.3 Mg C/ha vs. 2.7 Mg C/ha) reflected increased NEP (40 Mg C/ha vs. 25.4 Mg C/ha) as it responded to a greater water availability, despite similar amounts of C lost from management activities during both decades. At the end of the 21 years study, the ecosystem had incorporated 22.6 Mg C ha -1, indicating that actively managed naturally regenerated pine ecosystems in the region can mitigate C dioxide emissions under a broad range of climatic conditions, reduce wildfire risks, while providing numerous ecosystem services.