Co-digestion of terrestrial plant biomass with marine macro-algae for biogas production

This paper investigates factors affecting anaerobic degradation of marine macro-algae (or seaweed), when used as a co-substrate with terrestrial plant biomass for the production of biogas. Using Laminaria digitata, a brown marine seaweed species and green peas, results showed that when only 2% of feedstock of a reactor treating the green peas at an organic loading rate (OLR) of 2.67 kg VS.m3.day-1 was replaced with the seaweed, methane production was disrupted, whilst acidogenesis, seemed to be less adversely affected, resulting in excessive volatile acids accumulation. Reactor stability was difficult to achieve thereafter. The experiment was repeated with a lower initial OLR of green peas of 0.70 kg VS.m3.day-1 before the addition of the seaweed. Although similar symptoms as in first trial were observed, process stability was restored through the control of OLR and alkalinity. These measures led to an increase in overall OLR of 1.25 kg VS.m3.day-1 comprising of 35% seaweed. This study has shown that certain seaweed constituents are more inhibitory to the methanogens even at trace concentrations than to the other anaerobic digestion microbial groups. Appropriate adaptation strategy, involving initial low proportion of the seaweed relative to the total OLR, and overall low OLR, is necessary to ensure effective adaptation of the microorganisms to the inhibitory constituents of seaweed. Where there is seasonal availability of seaweed, the results of this study suggest that a fresh adaptation or start-up strategy must be implemented during each cycle of seaweed availability in order to ensure sustainable process stability.

Otimização da produção biotecnológica de lipases e correlação com a produção de biossurfactantes

As lipases e os biossurfactantes são compostos produzidos por microrganismos através de fermentações em estado sólido (FES) ou sumberso (FSm), os quais são aplicáveis nas indústrias alimentícia e farmacêutica, na bioenergia e na biorremediação, entre outras. O objetivo geral deste trabalho foi otimizar a produção de lipases através de fermentação em estado sólido e fermentação submersa. Os fungos foram selecionados quanto à habilidade de produção de lipases através de FES e FSm e aqueles que apresentaram as maiores atividades lipolíticas foram utilizados na seleção de variáveis significativas e na otimização da produção de lipases nos dois modos de cultivo. Foram empregadas técnicas seqüenciais de planejamento experimental, incluindo planejamentos fracionários, completos e a metodologia de superfície de resposta para a otimização da produção de lipases. As variáveis estudadas na FES foram o pH, o tipo de farelo como fonte de carbono, a fonte de nitrogênio, o indutor, a concentração da fonte de nitrogênio, a concentração do indutor e a cepa do fungo. Na FSm, além das variáveis estudadas na FES, estudaram-se as variáveis concentração inicial de inóculo e agitação. As enzimas produzidas foram caracterizadas quanto à temperatura e pH ótimos e quanto à estabilidade a temperatura e pH. Nas condições otimizadas de produção de lipases, foi avaliada a correlação entre a produção de lipases e bioemulsificantes. Inicialmente foram isolados 28 fungos. Os fungos Aspergillus O- 4 e Aspergillus E-6 foram selecionados como bons produtores de lipases no processo de fermentação em estado sólido e os fungos Penicillium E-3, Trichoderma E-19 e Aspergillus O-8 como bons produtores de lipases através da fermentação submersa. As condições otimizadas para a produção de lipases através de fermentação em estado sólido foram obtidas utilizando-se o fungo Aspergillus O-4, farelo de soja, 2% de nitrato de sódio, 2% de azeite de oliva e pHs inferiores a 5, obtendo-se atividades lipolíticas máximas de 57 U. As condições otimizadas para a produção de lipases na fermentação submersa foram obtidas utilizando-se o fungo Aspergillus O-8, farelo de trigo, 4,5% de extrato de levedura, 2% de óleo de soja e pH 7,15. A máxima atividade obtida durante a etapa de otimização foi 6 U. As lipases obtidas por FES apresentaram atividades máximas a 35ºC e pH 6,0, enquanto que as obtidas por FSm apresentaram ótimos a 37ºC e pH 7,2. A estabilidade térmica das lipases produzidas via FSm foi superior a das lipases obtidas via FES, com atividades residuais de 72% e 26,8% após 1h de exposição a 90ºC e 60ºC, respectivamente. As lipases obtidas via FES foram mais estáveis em pH´s alcalinos, com atividades residuais superiores a 60% após 24 h de exposição, enquanto as lipases produzidas via FSm foram mais estáveis em pH´s ácidos, com 80% de atividade residual na faixa de pH entre 3,5 e 6,5. Na fermentação submersa a correlação entre a produção de lipases e a atividade emulsificante óleo em água (O/A) e água em óleo (A/O) dos extratos foi 95,4% e 86,8%, respectivamente, obtendo-se atividades emulsificantes máximas O/A e A/O de 2,95 UE e 42,7 UE. Embora a maior produção de lipases tenha sido obtida na fermentação em estado sólido, não houve produção concomitante de biossurfactantes. Os extratos da fermentação submersa apresentaram redução da tensão superficial de 50 mN m -1 para 28 mN m -1 e atividade antimicrobiana frente ao microrganismo S. aureus ATCC 25923, com potenciais antimicrobianos de 36 a 43% nos três primeiros dias de fermentação. A fermentação submersa foi a técnica que apresentou os melhores resultados de otimização da produção de lipases, bem como de produção simultânea de biossurfactantes.

Puupolttoaineen varastonhallinta- ja hankintamalli

Työssä luodaan energiapuun varastonhallintamalli ja hankintamalli energiantuotantolaitoksen näkökulmasta sekä kuvataan kustannustehokkaita ja toimitusvarmoja vaihtoehtoja puupolttoaineen varastoinnille ja haketukselle. Varastonhallintamallissa keskitytään varastotason hallintamenetelmiin toimintaympäristössään. Hankintamalli määrittää oman varaston ja suoran laitostoimituksen suhteen sekä auttaa pohtimaan strategisen hankinnan merkitystä hankinnan toteuttamiseen ja hankintakanavien valintaan. Työ antaa vastauksia koko hankintatoiminnan toteutukseen ja hallitsemiseen. Varastonhallintamallin skenaariotarkastelussa selvisi, että yrityksen oma varasto vaatii 18 – 37 % varmuusvaraston suhteessa käyttövarastoon. Hankintamallin mukaan oman varaston kannattavimman puupolttoainejakeen hankintaetäisyys voisi olla keskimäärin korkeintaan 96 km. Tarpeen, saatavuuden, jakeiden kustannustasojen ja toimintaympäristön mahdollisuuksien ollessa selvillä, on mahdollista tehdä päätöksiä hankintakanavista ja varmuusvarastoista kustannustehokkuuden perusteella. Yrityksen polttoainemäärien ohjauksen toteutukseen vaaditaan kehittämistoimia. Oman toimintaympäristön vakiointi ja toimintamallien dokumentointi on tärkeää tiedonjaon, toimitussopimusten mitoittamisen ja toiminnan kehittämisen kannalta. Toiminnan pullonkaulojen vähentäminen ja puupolttoaineen ohjaaminen kustannustehokkaimpien haketusketjujen kautta mahdollisimman tehokkaasti synnyttävät kustannussäästöjä toimitusketjussa.

Perspectivas de los biocombustibles en Colombia

Colombia se está iniciando en bioenergía y necesita de políticas e infraestructura para la producción de biocombustibles. En los últimos años, losbiocombustibles vienen avanzando apoyados por la adopción de decretos de ley que permiten la introducción de biocombustibles, mezclados, en primera instancia, con combustibles fósiles como la gasolina y el diésel. Este artículo de “revisión de tema” presenta el comienzo y desarrollo de los biocombustibles en Colombia y la situación actual de la producción, las empresas y las entidades que lideran este proyecto, con el fin de adoptar una fuente de energía renovable y sostenible. En el análisis de este tema sobre biocombustibles en Colombia se apunta un claro comienzo a la independencia de combustibles fósiles, con la premisa de una matriz energética sostenible que asegure el crecimiento de la industria, el desarrollo social y la preservación del ambiente. Por otro lado, se observa la tendencia mundial a la adopción de biocombustibles principalmente en países dependientes del petróleo, siendo los suramericanos como Brasil, Colombia y Argentina los abanderados en estas propuestas. Colombia presenta, a su vez, recursos en este ámbito en disponibilidad de tierras, mano de obra, políticas internas de consumo y producción, que coexisten con dificultades en desigualdad social, conflictos internos, monopolios y trabas políticas que podrían impedir inversión privada y extranjera

Monitoramento por microcontrolador do cultivo de spirulina em fotobiorreator raceway

A oportunidade de produção de biomassa microalgal tem despertado interesse pelos diversos destinos que a mesma pode ter, seja na produção de bioenergia, como fonte de alimento ou servindo como produto da biofixação de dióxido de carbono. Em geral, a produção em larga escala de cianobactérias e microalgas é feita com acompanhamento através de análises físicoquímicas offline. Neste contexto, o objetivo deste trabalho foi monitorar a concentração celular em fotobiorreator raceway para produção de biomassa microalgal usando técnicas de aquisição digital de dados e controle de processos, pela aquisição de dados inline de iluminância, concentração de biomassa, temperatura e pH. Para tal fim foi necessário construir sensor baseado em software capaz de determinar a concentração de biomassa microalgal a partir de medidas ópticas de intensidade de radiação monocromática espalhada e desenvolver modelo matemático para a produção da biomassa microalgal no microcontrolador, utilizando algoritmo de computação natural no ajuste do modelo. Foi projetado, construído e testado durante cultivos de Spirulina sp. LEB 18, em escala piloto outdoor, um sistema autônomo de registro de informações advindas do cultivo. Foi testado um sensor de concentração de biomassa baseado na medição da radiação passante. Em uma segunda etapa foi concebido, construído e testado um sensor óptico de concentração de biomassa de Spirulina sp. LEB 18 baseado na medição da intensidade da radiação que sofre espalhamento pela suspensão da cianobactéria, em experimento no laboratório, sob condições controladas de luminosidade, temperatura e fluxo de suspensão de biomassa. A partir das medidas de espalhamento da radiação luminosa, foi construído um sistema de inferência neurofuzzy, que serve como um sensor por software da concentração de biomassa em cultivo. Por fim, a partir das concentrações de biomassa de cultivo, ao longo do tempo, foi prospectado o uso da plataforma Arduino na modelagem empírica da cinética de crescimento, usando a Equação de Verhulst. As medidas realizadas no sensor óptico baseado na medida da intensidade da radiação monocromática passante através da suspensão, usado em condições outdoor, apresentaram baixa correlação entre a concentração de biomassa e a radiação, mesmo para concentrações abaixo de 0,6 g/L. Quando da investigação do espalhamento óptico pela suspensão do cultivo, para os ângulos de 45º e 90º a radiação monocromática em 530 nm apresentou um comportamento linear crescente com a concentração, apresentando coeficiente de determinação, nos dois casos, 0,95. Foi possível construir um sensor de concentração de biomassa baseado em software, usando as informações combinadas de intensidade de radiação espalhada nos ângulos de 45º e 135º com coeficiente de determinação de 0,99. É factível realizar simultaneamente a determinação inline de variáveis do processo de cultivo de Spirulina e a modelagem cinética empírica do crescimento do micro-organismo através da equação de Verhulst, em microcontrolador Arduino.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).

Antimicrobial Compounds from Eukaryotic Microalgae against Human Pathogens and Diseases in Aquaculture

The search for novel compounds of marine origin has increased in the last decades for their application in various areas such as pharmaceutical, human or animal nutrition, cosmetics or bioenergy. In this context of blue technology development, microalgae are of particular interest due to their immense biodiversity and their relatively simple growth needs. In this review, we discuss about the promising use of microalgae and microalgal compounds as sources of natural antibiotics against human pathogens but also about their potential to limit microbial infections in aquaculture. An alternative to conventional antibiotics is needed as the microbial resistance to these drugs is increasing in humans and animals. Furthermore, using natural antibiotics for livestock could meet the consumer demand to avoid chemicals in food, would support a sustainable aquaculture and present the advantage of being environmentally friendly. Using natural and renewable microalgal compounds is still in its early days, but considering the important research development and rapid improvement in culture, extraction and purification processes, the valorization of microalgae will surely extend in the future.

RISKS TO FOOD AVAILABILITY AND ACCESS FROM CLIMATE POLICIES: AN INTEGRATED ASSESSMENT OF REGIONAL FOOD AVAILABILITY AND ACCESS WITH ALTERNATIVE CLIMATE MITIGATION STRATEGIES TO 2050

Although mitigating GHG emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production, certain mitigation measures may generate unintended consequences to food availability and access due to land use competition and economic burden of mitigation. Prior studies have examined the co-impacts on food availability and global producer prices caused by alternative climate policies. More recent studies have looked at the reduction in total caloric intake driven by both changing income and changing food prices under one specific climate policy. However, due to inelastic calorie demand, consumers’ well-being are likely further reduced by increased food expenditures. Built upon existing literature, my dissertation explores how alternative climate policy designs might adversely affect both caloric intake and staple food budget share to 2050, by using the Global Change Assessment Model (GCAM) and a post-estimated metric of food availability and access (FAA). My dissertation first develop a set of new metrics and methods to explore new perspectives of food availability and access under new conditions. The FAA metric consists of two components, the fraction of GDP per capita spent on five categories of staple food and total caloric intake relative to a reference level. By testing the metric against alternate expectations of the future, it shows consistent results with previous studies that economic growth dominates the improvement of FAA. As we increase our ambition to achieve stringent climate targets, two policy conditions tend to have large impacts on FAA driven by competing land use and increasing food prices. Strict conservation policies leave the competition between bioenergy and agriculture production on existing commercial land, while pricing terrestrial carbon encourages large-scale afforestation. To avoid unintended outcomes to food availability and access for the poor, pricing land emissions in frontier forests has the advantage of selecting more productive land for agricultural activities compared to the full conservation approach, but the land carbon price should not be linked to the price of energy system emissions. These results are highly relevant to effective policy-making to reduce land use change emissions, such as the Reduced Emissions from Deforestation and Forest Degradation (REDD).

Induction of Microalgal Lipids for Biodiesel Production in Tandem with Sequestration of High Carbon Dioxide Concentration

There is no doubt that sufficient energy supply is indispensable for the fulfillment of our fossil fuel crises in a stainable fashion. There have been many attempts in deriving biodiesel fuel from different bioenergy crops including corn, canola, soybean, palm, sugar cane and vegetable oil. However, there are some significant challenges, including depleting feedstock supplies, land use change impacts and food use competition, which lead to high prices and inability to completely displace fossil fuel [1-2]. In recent years, use of microalgae as an alternative biodiesel feedstock has gained renewed interest as these fuels are becoming increasingly economically viable, renewable, and carbon-neutral energy sources. One reason for this renewed interest derives from its promising growth giving it the ability to meet global transport fuel demand constraints with fewer energy supplies without compromising the global food supply. In this study, Chlorella protothecoides microalgae were cultivated under different conditions to produce high-yield biomass with high lipid content which would be converted into biodiesel fuel in tandem with the mitigation of high carbon dioxide concentration. The effects of CO2 using atmospheric and 15% CO2 concentration and light intensity of 35 and 140 µmol m-2s-1 on the microalgae growth and lipid induction were studied. The approach used was to culture microalgal Chlorella protothecoides with inoculation of 1×105 cells/ml in a 250-ml Erlenmeyer flask, irradiated with cool white fluorescent light at ambient temperature. Using these conditions we were able to determine the most suitable operating conditions for cultivating the green microalgae to produce high biomass and lipids. Nile red dye was used as a hydrophobic fluorescent probe to detect the induced intracellular lipids. Also, gas chromatograph mass spectroscopy was used to determine the CO2 concentrations in each culture flask using the closed continuous loop system. The goal was to study how the 15% CO2 concentration was being used up by the microalgae during cultivation. The results show that the condition of high light intensity of 140 µmol m-2s-1 with 15% CO2 concentration obtain high cell concentration of 7 x 105 cells mL-1 after culturing Chlorella protothecoides for 9 to 10 day in both open and closed systems respectively. Higher lipid content was estimated as indicated by fluorescence intensity with 1.3 to 2.5 times CO2 reduction emitted by power plants. The particle size of Chlorella protothecoides increased as well due to induction of lipid accumulation by the cells when culture under these condition (140 µmol m-2s-1 with 15% CO2 concentration).

Composting of different agro-food wastes: Effects of the phenolic and lignocellulosic fractions on greenhouse gases emissions

Currently, society faces a number of challenges related to the large amounts of organic wastes generated and accumulated by the increasing expansion of agroindustrial activities1. Most of these wastes are rich in lignocellulosic compounds, which represents a major fraction of all plant biomass (of above 90%), so, its degradation is crucial for global carbon cycle2. These organic wastes may be introduced directly on agriculture sector as soil organic amendment, however, these might contain phytochemicals, such as phenolic compounds which may introduce toxic effects to soil and to beneficial organisms. Transformation and degradation of these renewable organic wastes into composts (COMPOSTING) is a possible solution for these problems and an environmentally friendly processes that allows make use of natural resources efficiently3. The main potential handicap is generation and emission of greenhouse gases such as carbon dioxide (CO2 ), methane (CH4 ) and nitrous oxide (N2O) and another ones which may led serious problems like nitric oxide (NO) and ammonia (NH3) 4. For this reason, quantification of GHG emissions from composting and finding possible relations with the chemical and structural composition of the wastes used is crucial to the development of technologies for mitigating emissions and should help to make decisions concerning waste management.

Microbial nanowires : an electrifying tale

Electromicrobiology has gained momentum in the last ten years with advances in microbial fuel cells and the discovery of microbial nanowires (MNWs). The list of MNWs producing microorganisms is growing and providing intriguing insights into the presence of such microorganisms in diverse environments and the potential roles MNWs can perform. This review discusses the MNWs produced by different microorganisms, including their structure, composition and role in electron transfer through MNWs. Two hypotheses, metallic-like conductivity and an electron hopping model, have been proposed for electron transfer and we present a current understanding of both these hypotheses. MNWs are not only poised to change the way we see microorganisms but may also impact the fields of bioenergy, biogeochemistry and bioremediation, hence their potential applications in these fields are highlighted here.

Above ground biomass estimation in Mediterranean multiple use systems with high spatial resolution satellite images

Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. It was identified as a global strategic reserve, due to its applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. The estimation of above ground biomass is frequently done with allometric functions per species with plot inventory data. An adequate sampling design and intensity for an error threshold is required. The estimation per unit area is done using an extrapolation method. This procedure is labour demanding and costly. The mail goal of this study is the development of allometric functions for the estimation of above ground biomass with ground cover as independent variable, for forest areas of holm aok (Quercus rotundifolia), cork oak (Quercus suber) and umbrella pine (Pinus pinea) in multiple use systems. Ground cover per species was derived from crown horizontal projection obtained by processing high resolution satellite images, orthorectified, geometrically and atmospheric corrected, with multi-resolution segmentation method and object oriented classification. Forest inventory data were used to estimate plot above ground biomass with published allometric functions at tree level. The developed functions were fitted for monospecies stands and for multispecies stands of Quercus rotundifolia and Quercus suber, and Quercus suber and Pinus pinea. The stand composition was considered adding dummy variables to distinguish monospecies from multispecies stands. The models showed a good performance. Noteworthy is that the dummy variables, reflecting the differences between species, originated improvements in the models. Significant differences were found for above ground biomass estimation with the functions with and without the dummy variables. An error threshold of 10% corresponds to stand areas of about 40 ha. This method enables the overall area evaluation, not requiring extrapolation procedures, for the three species, which occur frequently in multispecies stands.

Evolutionary algorithms for the modeling of bioreactors

This work aims to study the application of Genetic Algorithms in anaerobic digestion modeling, in particular when using dynamical models. Along the work, different types of bioreactors are shown, such as batch, semi-batch and continuous, as well as their mathematical modeling. The work intendeds to estimate the parameter values of two biological reaction model. For that, simulated results, where only one output variable, the produced biogas, is known, are fitted to the model results. For this reason, the problems associated with reverse optimization are studied, using some graphics that provide clues to the sensitivity and identifiability associated with the problem. Particular solutions obtained by the identifiability analysis using GENSSI and DAISY softwares are also presented. Finally, the optimization is performed using genetic algorithms. During this optimization the need to improve the convergence of genetic algorithms was felt. This need has led to the development of an adaptation of the genetic algorithms, which we called Neighbored Genetic Algorithms (NGA1 and NGA2). In order to understand if this new approach overcomes the Basic Genetic Algorithms (BGA) and achieves the proposed goals, a study of 100 full optimization runs for each situation was further developed. Results show that NGA1 and NGA2 are statistically better than BGA. However, because it was not possible to obtain consistent results, the Nealder-Mead method was used, where the initial guesses were the estimated results from GA; Algoritmos Evolucionários para a Modelação de Bioreactores Resumo: Neste trabalho procura-se estudar os algoritmos genéticos com aplicação na modelação da digestão anaeróbia e, em particular, quando se utilizam modelos dinâmicos. Ao longo do mesmo, são apresentados diferentes tipos de bioreactores, como os batch, semi-batch e contínuos, bem como a modelação matemática dos mesmos. Neste trabalho procurou-se estimar o valor dos parâmetros que constam num modelo de digestão anaeróbia para o ajustar a uma situação simulada onde apenas se conhece uma variável de output, o biogas produzido. São ainda estudados os problemas associados à optimização inversa com recurso a alguns gráficos que fornecem pistas sobre a sensibilidade e identifiacabilidade associadas ao problema da modelação da digestão anaeróbia. São ainda apresentadas soluções particulares de idenficabilidade obtidas através dos softwares GENSSI e DAISY. Finalmente é realizada a optimização do modelo com recurso aos algoritmos genéticos. No decorrer dessa optimização sentiu-se a necessidade de melhorar a convergência e, portanto, desenvolveu-se ainda uma adaptação dos algoritmos genéticos a que se deu o nome de Neighboured Genetic Algorithms (NGA1 e NGA2). No sentido de se compreender se as adaptações permitiam superar os algoritmos genéticos básicos e atingir as metas propostas, foi ainda desenvolvido um estudo em que o processo de optimização foi realizado 100 vezes para cada um dos métodos, o que permitiu concluir, estatisticamente, que os BGA foram superados pelos NGA1 e NGA2. Ainda assim, porque não foi possivel obter consistência nos resultados, foi usado o método de Nealder-Mead utilizado como estimativa inicial os resultados obtidos pelos algoritmos genéticos.

Sugarcane Water Productivity Assessments in the São Paulo state, Brazil.

São Paulo state, Brazil, has been highlighted by the sugarcane crop expansion. The actual scenario of climate and land use changes, bring attention for the large-scale water productivity (WP) analyses. MODIS images were used together with gridded weather data for these analyses. A generalized sugarcane growing cycle inside a crop land mask, from September 2011 to October 2012, was considered in the main growing regions of the state. Actual evapotranspiration (ET) is quantified by the SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm, the biomass production (BIO) by the RUE (Radiation Use Efficiency) Monteith?s model and WP is considered as the ratio of BIO to ET. During the four generalized sugarcane crop phases, the mean ET values ranged from 0.6 to 4.0 mm day-1; BIO rates were between 20 and 200 kg ha-1 day-1, resulting in WP ranging from 2.8 to 6.0 kg m-3. Soil moisture indicators are applied, indicating benefits from supplementary irrigation during the grand growth phase, wherever there is water availability for this practice. The quantification of the large-scale water variables may subsidize the rational water resources management under the sugarcane expansion and water scarcity scenarios.

Componentes lignocelulósicos do sorgo biomassa em diferentes épocas de colheita.

2016