Bioenergy Research Research Articles

Very fine roots differ among switchgrass (Panicum virgatum L.) cultivars and differentially affect soil pores and carbon processes

Switchgrass (Panicum virgatum L.) is a promising feedstock for biofuel production, with diverse cultivars representing several ecotypes adapted to different environmental conditions within the contiguous USA. Multiple field studies have demonstrated that monoculture switchgrass cultivation leads to slow to negligible soil carbon (C) gains, an outcome unexpected for such a deep-rooted perennial. We hypothesize that different switchgrass cultivars have disparate impacts on soil C gains, and one of the reasons is variations in physical characteristics of their roots, where roots directly and indirectly influence formation of soil pores. We tested this hypothesis at Great Lakes Bioenergy Research Center's research site in Michigan using two lowland cultivars (Alamo and Kanlow) and four upland cultivars (Southlow, Cave-in-Rock, Blackwell, and Trailblazer). Three types of soil samples were collected: 20 cm diameter (Ø) intact cores used for root analyses; 5 cm Ø intact cores subjected to X-ray computed tomography scanning used for pore characterization; and disturbed soil samples used for microbial biomass C (MBC) and soil C measurements. Path analysis was used to explore interactive relationships among roots, soil pores, and their impact on MBC, and ultimately, on soil C contents across six cultivars. The abundance of very fine roots (<200 μm Ø) was positively associated with fractions of pores in the same size range, but negatively with distances to pores and particulate organic matter. Higher abundance of such roots also led to greater MBC, while greater volumes of medium pores (50–200 μm Ø) and shorter distances to pores increased MBC. Results suggest that the greater proportion of very fine roots is a trait that can potentially stimulate soil C gains, with pore characteristics serving as links for the relationship between such roots and C gains. However, at present, ten years of cultivation generated no differences in soil C among the studied cultivars.

Optimizing the energy values of solid biofuel through acidic pre-treatment: An evolutionary-based neuro-fuzzy modelling and feature importance analysis

The increasing focus on sustainable energy solutions and eco-friendly fuel alternatives has sparked interest in exploring methods to enhance the energy content of solid biofuels through pre-treatment processes. This study investigates the impact of acidic (H2SO4) pretreatment on the energy content of solid biofuel derived from watermelon peel waste using machine learning methods. The biofuel properties, and calorific value (CV) were determined experimentally for both H2SO4-treated and untreated biofuel samples. Subsequently, an Adaptive neuro-fuzzy inference system (ANFIS) model with Genetic Algorithm (GA) and Grid Partitioning (GP) clustering techniques was developed to predict heating value of the biofuel, with performance evaluation based on root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute deviation (MAD), Mean Absolute Error (MAE) and R2-values. The decision tree regressor was employed to evaluate the feature importance, predictive power and impact of each input variable on CV prediction based on Gini importance metrics. To establish its superior performance, the hybrid ANFIS-GA-GP model was compared with ordinary-ANFIS and ANN model using same metrics. Results show that acid-pretreatment increased the CV of the solid biofuel by 3.53 MJ/kg (31.83 % improvement) and reduced ash content by 1.77 %. FTIR analysis revealed surface modifications, and a shift in the C-O vibrational stretch, while SEM micrographs displayed denser surfaces and reduced porosity as indicated by a lesser fiber diameter in treated samples. The GP-clustered ANFIS-GA model with a triangular membership function (tri-MF) exhibited superior performance and higher accuracy (RMSE of 0.1309, MAPE of 9.343, MAD of 0.1036, MAE of 0.1110, and R2-value of 0.9773 at model training). Furthermore, a tree decision regressor identified Fixed carbon as the most significant predictor for CV with a Gini importance of 0.988375. This study demonstrates the substantial enhancement in the energy content of biofuel using acidic pre-treatment and insights into a cutting-edge approach of improving the combustion properties of solid biofuel with machine learning models. This significantly contributes to the field of sustainable bioenergy research.

Bacterial isolate collection from switchgrass rhizosphere.

We provide a collection of 78 bacterial isolates from the rhizosphere of switchgrass (Panicum virgatum L.) at the Lux Arbor Reserve in Delton, MI, a site of the Great Lakes Bioenergy Research Center (GLBRC), Michigan State University, MI, USA. We include information on isolation conditions and full-length 16S rRNA sequences.

Preface

The International Conference on Biomass and Bioenergy (ICBB) 2023 was successfully held as a hybrid conference by the Surfactant and Bioenergy Research Center (SBRC)-IPB University, Indonesia in collaboration with the International Society of Biomass and Bioenergy (ISBB); Villanova University, USA; and Hiroshima University, Japan. ICBB 2023 was sponsored by the Oil Palm Plantation Fund Management Agency of the Republic of Indonesia (BPDP Sawit) and the Indonesia Biofuel Producer Association (APROBI). The conference was also supported by the Ministry of Energy and Mineral Resources of the Republic of Indonesia, IPB University, and Indonesian Association of Bioenergy Scientist and Technologist (IKABI). ICBB 2023 with the theme of Global Advancement in Biomass and Bioenergy Research and Development to Achieve Sustainable Energy Transition and Bioeconomy was the 8th international scientific conference on biomass and bioenergy hosted in Indonesia. This annual conference is conducted to discuss current global advancement in biomass and bioenergy fields. The ICBB 2023 was held as the first ICBB hybrid conference on August 7-8, 2023. ICBB 2023 was organized by SBRC-IPB University and hosted at IPB International Convention Center, Bogor, Indonesia and online by Zoom Video Conference. To maintain the continuity of the annual conference for scientists and students to disseminate and publish their research, as well as to facilitate the attendance of more international participants, the ICBB 2023 operation was improved as a hybrid conference. ICBB 2023 main program consisted of a keynote and plenary sessions with seven speakers and four thematic parallel sessions. Seven prominent scientists in biomass and bioenergy sciences from 6 different countries successfully delivered their lectures, i.e., Prof. Dr. Yun Hin Taufiq-Yap (University Putra Malaysia, Malaysia), Dr. Dadan Kusdiana (The Ministry of Energy and Mineral Resources of the Republic of Indonesia), Prof. Dr. Justinus Satrio (Villanova University, USA), Prof. Dr. Yukihiro Matsumura (Hiroshima University, Japan), Assoc. Prof. Dr. Edy Hartulistiyoso (IPB University, Indonesia), Prof. Dr. Navid Moheimani (Murdoch University, Australia), Prof. Dr. David Herak (Czech University of Life Sciences, Czech), and 63 parallel presentations were successfully organized. ICBB 2023 thematically discussed four key topics as follows: 1. Bioenergy and Biomass Utilization, 2. AI/IT Technologies in Biomass/Bioenergy/Agriculture, 3. Environment, Economics, Policy, Management/Business related to Biomass or Bioenergy, 4. Bio-chemicals The paper committee received 85 submissions and finally accepted 42 full papers of over 63 presentations which were delivered in the conference and published in this ICBB 2023 proceedings after the peer reviewing process. Authors of ICBB 2023 proceedings were from 5 countries (Indonesia, Japan, USA, the Netherlands, and the Philippines). There were more than 189 participants who attended online ICBB 2023 from 9 countries (Japan, Czech Republic, Malaysia, USA, Philippines, the Netherlands, Australia, Poland, and Indonesia). The differences in time zones and the quality of the host and participants’ internet networks posed a challenge to the operation of this hybrid conference. However, the technical quality and delivery success of the conference were very good. Acknowledgments and appreciations to the Rector and Vice Rector of IPB University for their support to the conference, to the reviewers and editorial board members, committee members, and event partners who worked hard to make the conference and the publication of this proceedings successful. The conference committee acknowledged the support and sponsorship from the Oil Palm Plantation Fund Management Agency of the Republic of Indonesia (BPDP Sawit) and the Indonesia Biofuel Producer Association (APROBI). The paper committee did their best to complete manuscripts reviewing by following the scientific standards in the IOP Conference Series: Earth and Environmental Science. However, there might be some shortcomings found in this proceedings. Therefore, suggestions from readers are greatly appreciated, so that the quality of the ICBB conference proceedings will continuously be improved in the future. We hope this ICBB 2023 proceedings will improve knowledge and provide benefits to academics, scientists, industrial stakeholders, and policy makers, especially in the field of biomass and bioenergy. Thank you for your kind attention. The list of Committees of the International Conference on Biomass and Bioenergy 2023 Steering Committee and Organizing Committee are available in this pdf.

Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single Anonymous • Conference submission management system: Morressier • Number of submissions received: 74 • Number of submissions sent for review: 45 • Number of submissions accepted: 42 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 56.8 • Average number of reviews per paper: 2.0238095238095237 • Total number of reviewers involved: 6 • Contact person for queries: Name: Ganjar Saefurahman Email: ganjars@apps.ipb.ac.id Affiliation: Bogor Agricultural University - Surfactant and Bioenergy Research Center

Genetic characterization of biohydrogen-producing purple non-sulfur bacteria Rhodobacter johrii MAY2 isolate via whole genome analysis

Purple non-sulfur bacteria (PNSB) are a diverse group of bacteria studied for various possible applications. They are commonly surveyed in bioenergy research as they produce biohydrogen, a candidate for clean alternative energy. This study aimed to assess the biohydrogen production ability and genetically characterize a high biohydrogen-producing PNSB (MAY2) isolated from Los Baños, Laguna, Philippines via whole genome sequencing (WGS). MAY2, when grown in mixed volatile fatty acids, produced biogas with 38% hydrogen. WGS results revealed that the isolate is positively classified under the genus Rhodobacter johrii. Also, 82 genetic hallmarks for biohydrogen production were found in the isolated genome which are involved in the production of key enzymes and proteins relevant to the photofermentative and hydrogen regulation pathways. Its nitrogenase gene cluster is stringently regulated by two genes, nifA and rofN, whose function and expression are easily affected by several environmental factors.

Bio‐innovation for environmental sustainability: Asymmetric nexus between bioenergy technology budgets and ecological footprint

AbstractAs the world grapples with sustainable energy and environmental preservation challenges, budgeting for bio‐resilience emerges as a pivotal step toward environmental sustainability. Our investigation delves into the influence of bioenergy technology budgets on the ecological footprint (ECF) in the top 10 nations that invest in bioenergy research and development (USA, China, Brazil, Germany, Japan, Canada, Sweden, Finland, Denmark, and the Netherlands). Prior research depended on panel data methods to explore the bioenergy technology‐environment nexus, disregarding the specific traits of individual countries. Contrarily, the existing research applies the quantile‐on‐quantile tool to improve the precision of our analysis by delivering a holistic worldwide viewpoint and customized perceptions for every economy. The findings indicate that dedicating budgets to bioenergy technology improves environmental quality by reducing ECF across several quantiles within our sample nations. Moreover, the outcomes uncover unique patterns in these relationships across multiple countries. These results stress the significance of policymakers conducting exhaustive assessments and implementing productive tactics to address bioenergy technology funding and ECF changes.

Microbial-explicit processes and refined perennial plant traits improve modeled ecosystem carbon dynamics

Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, and disturbance regimes. Understanding how soil carbon dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions and policy regarding net ecosystem carbon balance. Soil microbes play a key role in both carbon fluxes and stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated microbial-explicit processes into the DayCent biogeochemical model to better represent large perennial grasses and mechanisms of soil carbon formation and stabilization. We also take advantage of recent model improvements to better represent perennial grass structural complexity and life-history traits. Specifically, this study focuses on: 1) a plant sub-model that represents perennial phenology and more refined plant chemistry with downstream implications for soil organic matter (SOM) cycling though litter inputs, 2) live and dead soil microbe pools that influence routing of carbon to physically protected and unprotected pools, 3) Michaelis-Menten kinetics rather than first-order kinetics in the soil decomposition calculations, and 4) feedbacks between decomposition and live microbial pools. We evaluated the performance of the plant sub-model and two SOM cycling sub-models, Michaelis-Menten (MM) and first-order (FO), using observations of net ecosystem production, ecosystem respiration, soil respiration, microbial biomass, and soil carbon from long-term bioenergy research plots in the mid-western United States. The MM sub-model represented seasonal dynamics of soil carbon fluxes better than the FO sub-model which consistently overestimated winter soil respiration. While both SOM sub-models were similarly calibrated to total, physically protected, and physically unprotected soil carbon measurements, the models differed in future soil carbon response to disturbance and climate, most notably in the protected pools. Adding microbial-explicit mechanisms of soil processes to ecosystem models will improve model predictions of ecosystem carbon balances but more data and research are necessary to validate disturbance and climate change responses and soil pool allocation.

Biomass and Operational Initiatives for Sustainable Bioenergy Generation

The global shift towards sustainable energy resources highlights the importance of biomass as a promising path for generating green, renewable energy. This study synthesizes modern research and technological improvements in biomass feedstocks, bioenergy conversion approaches, and integrated biorefinery systems. It explores the multifaceted position of biomass in addressing power safety, mitigating climate change, and fostering financial improvement, in particular in emerging economies. The paper evaluates diverse biomass resources, along with lignocellulosic materials, dairy waste, and microalgae, and discusses their conversion into biofuels and biochemicals via tactics including fermentation, anaerobic digestion, and biochemical conversion. It similarly delves into the environmental and monetary implications of biomass usage, highlighting the challenges and opportunities in enhancing efficiency, reducing fees, and making sure sustainability. By supplying a comprehensive evaluate of the modern country and future instructions of bioenergy research, this paper pursuit to make contributions to the development of low-carbon, renewable fuel options and advance the global transition towards a more sustainable and varied energy portfolio.

Spatial disparities altered the determinants of biomass supply intention for clean energy: policy implications

Understanding the spatial variation of factors driving interest in bioenergy is important for designing effective energy policies. Although previous authors have broadly explored the determinants of biomass supply intentions in the field of bioenergy, the potential spatial variation of these factors has received limited consideration from bioenergy research. We performed a structural equation modeling based on the theory of planned behavior to investigate the impact of spatial disparities on factors determining people’s intentions to supply forestry residues for clean energy. Our data were generated through a survey of 247 participants randomly sampled from two contrasting geographic regions (north and south) of the Republic of Benin. We found that spatial disparities altered the effects of attitude and knowledge of renewable energy while income and perceived behavioral control exhibited consistent positive effects across geographical regions. Our findings imply that ignoring spatial disparities when analyzing bioenergy acceptance can lead to distorted inferences. These findings can be used as a baseline information by policymakers to develop region-specific actions for achieving local transition toward clean energy in the Republic of Benin.

Genome-sequenced bacterial collection from sorghum aerial root mucilage.

A collection of 47 bacteria isolated from the mucilage of aerial roots of energy sorghum is available at the Great Lakes Bioenergy Research Center, Michigan State University, Michigan, USA. We enriched bacteria with putative plant-beneficial phenotypes and included information on phenotypic diversity, taxonomy, and whole genome sequences.

Preface

Preface

Applicability and Trend of the Artificial Intelligence (AI) on Bioenergy Research between 1991–2021: A Bibliometric Analysis

The bibliometric analysis investigated the impact of publications on trends in the literature and bioenergy research using artificial intelligence (AI) from 1991 to 2021. In this study, 1721 publications were extracted from the Web of Science, and an analysis of the countries, authorship, institutions, journals, and keywords was visualised. In the recent decades, this field has entered an outbreak phase. India was the most productive country in this area, followed by China, Iran, and the US. It also noted several notable differences between trends and subjects in developed and developing countries. The former led this field at the initial stage and later attached importance to using AI for research feedstock and impact assessment. Developing countries encouraged the advancement of this area and emphasised the feedstock usage of phase treatment and process optimisation. In addition, a co-authorship and institutes study revealed that authors and institutes in distant regions rarely collaborated. The journal analysis shows strong links between Energy, Fuel, and Energy Conversion and Management. Machine learning is by far the most common application of artificial intelligence (AI) technology in bioenergy research, with 53% of the articles using it. In these AI-related publications, the keyword artificial neural network (ANN) appeared most frequently in the articles.

Bioenergy research in Brazil: A bibliometric evaluation of the BIOEN research program

AbstractThis article discusses the scientific production carried out by the largest bioenergy research program in Brazil, the São Paulo Research Foundation Bioenergy Research Program (BIOEN‐FAPESP), in the period from 2008 to 2019. The study draws on a list of BIOEN publications on the Web of Science (WoS) platform, containing over 1000 articles, grouped under ResearcherID H‐6149‐2012. The methods applied in the study were based on the information specific to each article and involved the construction of networks including authors, countries, research subjects, and direct citations. Communities were built based on network properties and their content was extracted from articles abstracts, titles and keywords, using text mining techniques. We also obtained quantitative measures for BIOEN scientific output. The analysis found that BIOEN produced relevant knowledge, and contributed to the emergence of new research areas in the bioenergy sector. Overall, BIOEN was decisive for the advancement of bioenergy research in Brazil, and resulted in the expansion of the knowledge base for ethanol production. © 2022 Society of Chemical Industry and John Wiley &amp; Sons, Ltd.

Quorum quenching of autoinducer 2 increases methane production in anaerobic digestion of waste activated sludge.

The ubiquitous signaling molecule autoinducer 2 (AI-2) is involved in intra- and interspecies communication, most notably between Gram-negative and Gram-positive bacteria. AI-2 accumulates during the exponential phase of the Escherichia coli (E. coli) monoculture and then rapidly decreases upon entry into the stationary phase. However, deleting both the genes encoding AI-2 synthase (LuxS) and the lsr operon regulator (LsrR) in the E. coli genome causes impaired AI-2 production and continuous AI-2 scavenging from the environment. This genetically-engineered E. coli mutant capable of quenching AI-2 quorum sensing (QS) system was utilized to evaluate the effect of AI-2 quenching on the anaerobic digestion of waste activated sludge (WAS) because the role of QS system via AI-2 in the process remains obscure. In this study, E. coli ∆luxS lsrR mutant cells were microencapsulated in sodium alginate beads and incubated with WAS anaerobically. After 15days of anaerobic fermentation, the WAS containing double mutant cells produced significantly more methane than that of the parent E. coli cells. AI-2 quenching occurred concurrently with a shift of microbial communities that contribute to increasing acetate consumption by the Methanosarcina spp. resulting in an increase in methane production. KEY POINTS: • Impact of autoinducer 2 quenching in complex bacterial populations were determined. • Keymicroorganisms contributing to the increase of methane in WAS anaerobic digestion were found. • The AI-2 quenching is a potential regulatory in wastewater treatment and bioenergy research.

Preface

The International Conference on Biomass and Bioenergy (ICBB) 2021 was successfully conducted as a fully online conference by the Surfactant and Bioenergy Research Center (SBRC)-IPB University, Indonesia in cooperation with the International Society of Biomass and Bioenergy (ISBB); College of Engineering, Villanova University, USA; and Biomass Project Research Center, Hiroshima University, Japan. ICBB 2021 was sponsored by The Palm Oil Fund Management Agency (BPDP Sawit) and IPB University. ICBB 2021 with the theme of Challenges in Biomass, Bioenergy, and Biomaterials Research and Development in a Rapidly Changing World was the sixth international scientific conference on biomass and bioenergy hosted in Indonesia. This conference is conducted annually to raise current global issues in biomass and bioenergy fields.Due to COVID-19 related real conference and travel restrictions, ICBB 2021 was held as an online conference on 9-10 August 2021 by Zoom Video Conference platform. ICBB 2021 was organized by SBRC-IPB University and hosted from IPB International Convention Center, Bogor, Indonesia. To maintain the continuity of the annual conference and the intention of scientists to disseminate and publish their research, as well as the uncertainty of the end time for COVID-19, the ICBB 2021 associates and stakeholders decided to hold a virtual conference and not postpone the conference.The list of Committees of the International Conference of Biomass and Bioenergy 2020, Steering Committee, Organizing Committee, ICBB 2021 was proudly and logos are available in the pdf

Anaerobic co-digestion of food waste, algae, and cow dung for biogas yield enhancement as a prospective approach for environmental sustainability

The enduring economic and environmental concerns have prompted extensive research in bioenergy in recent decades. Biogas is an effective carbon-free, sustainable energy source generated by the anaerobic digestion of biological wastes. Biogas production is promoted globally to decrease carbon emissions and maximize resource recycling from various wastes. The extant work examines biogas production in an anaerobic digester using co-digestion, which uses food wastes, algae, chicken, and fish mixed with cow manure. A physicochemical pre-treatment is used to change the lignocellulosic structure of the mixture of the wastes prior to the anaerobic co-digestion.The response surface technique is used to optimize the co-digestion factors, like pH, F/I ratio, organic loading rate, temperature, and concentration of the wastes. The optimal values of cumulative CO2, methane, and biogas have been obtained as 30.18 ml, 1345.97 ml, and 2244.58 ml, respectively.

Soil Origin and Plant Genotype Modulate Switchgrass Aboveground Productivity and Root Microbiome Assembly.

ABSTRACTSwitchgrass (Panicum virgatum) is a model perennial grass for bioenergy production that can be productive in agricultural lands that are not suitable for food production. There is growing interest in whether its associated microbiome may be adaptive in low- or no-input cultivation systems. However, the relative impact of plant genotype and soil factors on plant microbiome and biomass are a challenge to decouple. To address this, a common garden greenhouse experiment was carried out using six common switchgrass genotypes, which were each grown in four different marginal soils collected from long-term bioenergy research sites in Michigan and Wisconsin. We characterized the fungal and bacterial root communities with high-throughput amplicon sequencing of the ITS and 16S rDNA markers, and collected phenological plant traits during plant growth, as well as soil chemical traits. At harvest, we measured the total plant aerial dry biomass. Significant differences in richness and Shannon diversity across soils but not between plant genotypes were found. Generalized linear models showed an interaction between soil and genotype for fungal richness but not for bacterial richness. Community structure was also strongly shaped by soil origin and soil origin × plant genotype interactions. Overall, plant genotype effects were significant but low. Random Forest models indicate that important factors impacting switchgrass biomass included NO3−, Ca2+, PO43−, and microbial biodiversity. We identified 54 fungal and 52 bacterial predictors of plant aerial biomass, which included several operational taxonomic units belonging to Glomeraceae and Rhizobiaceae, fungal and bacterial lineages that are involved in provisioning nutrients to plants.

Global analysis of switchgrass (Panicum virgatum L.) transcriptomes in response to interactive effects of drought and heat stresses

BackgroundSustainable production of high-quality feedstock has been of great interest in bioenergy research. Despite the economic importance, high temperatures and water deficit are limiting factors for the successful cultivation of switchgrass in semi-arid areas. There are limited reports on the molecular basis of combined abiotic stress tolerance in switchgrass, particularly the combination of drought and heat stress. We used transcriptomic approaches to elucidate the changes in the response of switchgrass to drought and high temperature simultaneously.ResultsWe conducted solely drought treatment in switchgrass plant Alamo AP13 by withholding water after 45 days of growing. For the combination of drought and heat effect, heat treatment (35 °C/25 °C day/night) was imposed after 72 h of the initiation of drought. Samples were collected at 0 h, 72 h, 96 h, 120 h, 144 h, and 168 h after treatment imposition, total RNA was extracted, and RNA-Seq conducted. Out of a total of 32,190 genes, we identified 3912, as drought (DT) responsive genes, 2339 and 4635 as, heat (HT) and drought and heat (DTHT) responsive genes, respectively. There were 209, 106, and 220 transcription factors (TFs) differentially expressed under DT, HT and DTHT respectively. Gene ontology annotation identified the metabolic process as the significant term enriched in DTHT genes. Other biological processes identified in DTHT responsive genes included: response to water, photosynthesis, oxidation-reduction processes, and response to stress. KEGG pathway enrichment analysis on DT and DTHT responsive genes revealed that TFs and genes controlling phenylpropanoid pathways were important for individual as well as combined stress response. For example, hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyl transferase (HCT) from the phenylpropanoid pathway was induced by single DT and combinations of DTHT stress.ConclusionThrough RNA-Seq analysis, we have identified unique and overlapping genes in response to DT and combined DTHT stress in switchgrass. The combination of DT and HT stress may affect the photosynthetic machinery and phenylpropanoid pathway of switchgrass which negatively impacts lignin synthesis and biomass production of switchgrass. The biological function of genes identified particularly in response to DTHT stress could further be confirmed by techniques such as single point mutation or RNAi.

Effect of organic and inorganic mulching on weed density and productivity of tomato (Solanum lycopersicum L.)

Use of mulches has been an effective and low cost strategy to increase the yield of vegetable crops. The experiment was conducted at Defence Institute of Bio-Energy Research (DIBER), Haldwani in tarai region of central Himalaya. Both organic and inorganic mulches were used on four tomato varieties to study varietal response to mulching. Results revealed that mulching has significant beneficial effect on fruit yield over control. All the tomato lines used under study responded to mulching treatments and exhibited increase in fruit yield. Weed density was the lowest (2 weeds/m 2 ) in black polythene and the highest in control (80 weeds/m 2 ). Among the inorganic mulches, transparent polythene could not suppress the growth of weeds as the sunlight was available for weeds to grow. Dry weight of weeds under transparent polythene was 56 g/m 2 , whereas among the organic mulches dry weight of weeds was 108 (dencha husk) to 216 g/m 2 (rice straw). Inorganic mulches were found effective in prolonging the crop duration significantly with black polythene almost doubling the duration of fruit availability (62 days) compared to control (32 days).