Chronological dataset of soil respiration fluxes from a seasonally dry forest in Northwest México.

Soil respiration (CO2 emission to the atmosphere from soils) is an important component of the global carbon cycle. In highly seasonal ecosystems the magnitudes and the underlying mechanisms that control soil respiration (RS) are still poorly understood and measurements are underrepresented in the global flux community. In this dataset, systematic and monthly measurements of RS were conducted with an infrared gas analyzer coupled to a static chamber during 2015, 2016, 2017 and 2019 in a tropical dry forest with a land use history from Northwestern México. These data is useful to assess the intra-annual and seasonal variations of RS at a highly seasonal dry forests and serves as a base line to benchmark soil carbon models in regional and global contexts. The data presented supports the research manuscript: "Soil respiration is influenced by seasonality, forest succession and contrasting biophysical controls in a tropical dry forest in Northwestern Mexico" from Vargas-Terminel et al. [1].

Artificial neural networks and adaptive neuro-fuzzy inference systems for prediction of soil respiration in forested areas southern Brazil.

The purpose of this study was to estimate the temporal variability of CO2 emission (FCO2) from O2 influx into the soil (FO2) in a reforested area with native vegetation in the Brazilian Cerrado, as well as to understand the dynamics of soil respiration in this ecosystem. The database is composed of soil respiration data, agroclimatic variables, improved vegetation index (EVI), and soil attributes used to train machine learning algorithms: artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS). The predictive performance was evaluated based on the mean absolute error (MEA), root mean square error (RMSE), mean absolute percentage error (MAPE), agreement index (d), confidence coefficient (c), and coefficient of determination (R2). The best estimation results for validation were FCO2 with multilayer perceptron neural network (MLP) (R2 = 0.53, RMSE = 0.967 µmol m-2 s-1) and radial basis function neural network (RBF) (R2 = 0.54, RMSE = 0.884 µmol m-2 s-1) and FO2 with MLP (R2 = 0.45, RMSE = 0.093 mg m-2 s-1) and RBF (R2 = 0.74, 0.079 mg m-2 s-1). Soil temperature and macroporosity are important predictors of FCO2 and FO2. The best combination of variables for training the ANFIS was selected based on trial and error. The results were as follows: FCO2 (R2 = 16) and FO2 (R2 = 29). In all models, FCO2 outperformed FO2. A primary factor analysis was performed, and FCO2 and FO2 correlated best with the weather and soil attributes, respectively.

The global energy matrix and use of agricultural residues for bioenergy production: A review with inspiring insights that aim to contribute to deliver solutions for society and industrial sectors through suggestions for future research.

Promoting the use of renewable energy sources has become an important policy strategy for mitigating climate change and for providing better energy security and financial sustainability. To overcome the problems generated by non-renewable energy sources, it is essential to use new energy sources. A literature review was conducted to investigate and understand the opportunities for implementing new renewable energy sources. Agricultural residues have great potential to receive significant consideration worldwide as an alternative, sustainable, and green energy source. The use of agricultural residues for bioenergy generation is a broad and favourable scenario for exploration. This review identified potential and almost unexplored research approaches with the aim of contributing and promoting researchers to deliver technological solutions for the society and industrial sectors. For example, a potentially promising technological solution would be for industries that produce machinery and agricultural implements to adapt their harvesters for different grain crops, to collect these agricultural residues simultaneously during harvest and readily perform granulation, compaction (pressing), pelletizing or briquetting directly on the property. Further studies are required to investigate the use of agricultural residues for bioenergy generation, which can contribute to the diversification of the energy matrix. Accordingly, in this review, several challenges and future research perspectives have been presented, such as suggestions for future research on how to collect, transport, process, market and use these agricultural residues to generate bioenergy, aiming at reducing the dependence on fossil fuels.

Impact of FDI, industrialization, and education on the environment in Argentina: ARDL approach.

Purpose: This study employed the stochastic implications of regression on population, affluence, and technology (STIRPAT) methodology between 1972 and 2021. The main goal of this research is to look at how FDI, population growth, industrialization, and education affect the environment in Argentina. Methodology: The F-bound test and Johansen cointegration test are employed in this research to determine if there is a co-integration association among the variables. Additionally, the Autoregressive Distributed Lag (ARDL) method is used to examine the short-run and long-run elasticity of the independent variable. This study also incorporated a pairwise Granger causality test to determine the direction of causation between the variables. After that, the study applied several diagnostic and stability tests. Findings: The empirical evidence demonstrates the presence of a co-integration association among CO2 emissions, population, industrialization, and education. The findings indicate that population growth and industrialization harm the environment in Argentina in the long run. In addition, a significant inverse association was obtained between CO2 emissions and educational expenditures in the short run. Practical implications: The existence of STIRPAT suggests that Argentina is capable of achieving sustained economic growth. To achieve the goal, countries must implement appropriate government policies and ensure their implementation. This paper argues strongly for more investment in education, renewable energy, sustainable industrialization, and research and development, all of which are essential for a green economy.

Physical fractions of organic matter and mineralizable soil carbon as quality indicators in areas under different forms of use in the Cerrado-Pantanal Ecotone.

Understanding soil organic matter (SOM) dynamics is essential to employ management that contribute to the improvement of soil quality (SQ). The aim of this study was to characterize the SOM and evaluate the emission of mineralizable C (C-CO2) in different management systems. The soil was collected in five managed areas: exposed soil (ES), conventional tillage system (CTS), no-tillage system (NTS), permanent pasture (PP) and sugarcane (SC), in addition to a forest area (NF), in the layers of 0-5, 5-10, and 10-20 cm. Total organic carbon (TOC), physical-granulometric fractionation of SOM were performed, determining the contents and stocks of particulate organic matter (C-POM; StockPOM) and mineral organic matter (C-MOM; StockMOM), in addition to calculating SQ indices. In addition to C-CO2 emissions from the soil. The areas of PP and NTS presented the highest levels of TOC in the surface layer. The highest levels of C-MOM and StockMOM were observed in the PP area, besides higher CSI (carbon stock index), reaching 1.67 in the 10-20 cm layer. The areas of PP and SC were similar to the NF in all layers regarding CMI (carbon management index). In CTS, there were higher peaks in emissions and accumulation of C-CO2. It is evident that the improvements in the SQ in the areas of PP, SC, and NTS caused mainly by the deposition of plant material and by soil revolving not being performed. In the CTS, high emission peaks of C-CO2 show that the lack of conservation management practices contributes to the emission of greenhouse gases.

Effect of Ornamental Stone Waste Incorporation on the Rheology, Hydration, Microstructure, and CO2 Emissions of Ordinary Portland Cement.

The ornamental stone industry generates large amounts of waste thus creating environmental and human health hazards. Thus, pastes with 0-30 wt.% ornamental stone waste (OSW) incorporated into ordinary Portland cement (OPC) were produced and their rheological properties, hydration kinetics, and mechanical properties were evaluated. The CO2 equivalent emissions related to the pastes production were estimated for each composition. The results showed that the paste with 10 wt.% of OSW exhibited similar yield stress compared to the plain OPC paste, while pastes with 20 and 30 wt.% displayed reduced yield stresses up to 15%. OSW slightly enhanced the hydration kinetics compared to plain OPC, increasing the main heat flow peak and 90-h cumulative heat values. The incorporation of OSW reduced the 1-, 3-, and 28-days compressive strength of the pastes. Water absorption results agreed with the 28 days compressive strength results, indicating that OSW increased the volume of permeable voids. Finally, OSW incorporation progressively reduced the CO2 emission per m3 of OPC paste, reaching a 31% reduction for the highest 30 wt.% OSW content. Overall, incorporating up to 10 wt.% with OSW led to pastes with comparable fresh and hardened properties as comported to plain OPC paste.

How CO2 emissions respond to changes in government size and level of digitalization? Evidence from the BRICS countries.

The role of government size and digitization in the process of environmental quality is a matter of considerable debate in the field of environmental economics. BRICS economies have suffered from environmental pollution. This paper scrutinizes that how CO2 emissions respond to government size and digitization in BRICS economies. Empirical estimates of the ARDL approach show that government size has a positive impact on CO2 in Brazil, India, and China, while negative impact on CO2 in Russia in the long run. The long-run estimates reveal a negative and significant effect of digitization on CO2 in Brazil, India, and China. Education and e-learning activities have a favorable and crucial role played in environmental quality in Brazil, India, and China. Based on these findings, BRICS authorities should improve the efficiency of government expenditures and invest more in digitization to improve the quality of the environment.

Towards Achieving Sustainable Development: Role of Technology Innovation, Technology Adoption and CO2 Emission for BRICS.

In the digital era, technology innovation and adoption trigger economic growth and enhance CO2 emissions through productivity, which places it in the mainstream policy debate. For BRICS economies, this paper uses the first method proposed in the literature to quantify their information and communication technology (ICT) and innovatively links each country to their information technology adoption rate, as a surrogate indicator for measuring information and communication technology. Environmental Kuznets curve evidence is also examined, using technology innovation, technology adoption, and trade openness as the control variables for sustainable development. The results show that two out of three technology innovation instruments, fixed telephone, and broadband subscriptions increase CO2 emissions. Simultaneously, mobile cellular subscriptions have a lowering effect on CO2 emission in BRICS. The technology adoption indicators, high-technology exports, and electric power consumption also cause an upsurge in CO2 emission. Moreover, trade openness also enriches the level of CO2 emission in the BRICS regions. There is a need to devise technology innovation and adoption policies to better use technology and to ensure a green environment.

Does bank credit to the private sector promote low-carbon development in Brazil? An extended STIRPAT analysis using dynamic ARDL simulations.

In support of the global efforts to tackle climate change, policy makers in the past decades have been actively involved, exploring possible options for ensuring low-carbon pattern of development. This study contributes to this important stream of policy discussion by using a newly developed econometric technique, dynamic ARDL simulations, to estimate and simulate the impact of bank credit to the private sector on aggregate carbon emissions and carbon emission intensity in Brazil over the period 1971-2014. The examined empirical model is based on a framework that incorporates the impact of population, economic growth, fossil energy intensity of consumption, and economic globalization. The analysis produced interesting results. First, the estimates show that economic growth and fossil energy intensity of consumption have significant long-run increasing impact on CO2 emissions in Brazil. Second, bank credit to the private sector has significant short-run and long-run reducing effects on aggregate CO2 emission and carbon emission intensity in the economy. Overall, the results reflect the tendency of the economy to become less carbon-intensive as bank credit supply to the private sector increases.

On the remittances-environment led hypothesis: Empirical evidence from BRICS economies.

In this paper, we investigated the association between CO2 emissions, remittances, income, energy use, and foreign direct investment (FDI) through panel cointegration analysis, common correlated effect mean group (CCEMG), fully modified least squares (FM-LS) estimates, and panel causality test for the Brazil, Russia, India, China, and South Africa (BRICS) economies over 1986-2016. The empirical outcomes of CCEMG and FM-LS clarified that remittance inflows into BRICS region are contributing to environmental degradation. Similarly, results in the case of Brazil, Russia, and China supported the remittances-led emission hypothesis. On the other hand, different results have been reached in India, thus the remittances; inflows have dictated that they are helping to combat CO2 emission. Furthermore, FDI has a positive and significant sign for BRICS economies. This relationship narrated that the FDI inflows to this region increase the CO2 emission, hence obeying the pollution haven hypothesis. Finally, energy use also supports the energy-led emanation phenomenon in BRICS panel and alongside the countries. The panel causality test confirms the bidirectional linkage between remittances and CO2 emissions.

Avaliação da energia incorporada e da emissão de CO2 em recipientes para refrigerantes: PET versus vidro / Evaluation of energy and CO 2 emissions in soft drink containers: PET versus Glass

RESUMO Este artigo busca avaliar e comparar qual material (PET ou vidro) proporciona um ciclo de vida mais sustentável para os recipientes utilizados no envase de refrigerantes. Foram comparados quatro recipientes de vidro - três retornáveis e um descartável - com cinco recipientes em polietileno tereftalato (PET) - três descartáveis produzidos com material virgem, um descartável produzido com 20% de material reciclado e um retornável (RefPET). Utilizou-se como ferramenta o programa CES-Selector/EcoAudit, o qual considera cinco etapas principais do ciclo de vida do produto - material (obtenção de matéria-prima), produção, transporte, uso e descarte. Os indicadores resultantes foram a energia incorporada e a quantidade de CO2 emitida. Os resultados, para cada 1.000 L de refrigerante envasado, comprovam que a reutilização do recipiente é a escolha ambientalmente mais correta e mostram que, nas garrafas de PET, quanto maior a capacidade do recipiente, menor a quantidade de material de PET utilizado, menor a energia incorporada e menor a emissão de CO2. Por outro lado, para as garrafas de vidro, o resultado é oposto, ou seja, quanto maior a capacidade do recipiente, maior a quantidade de material utilizado, maior a energia incorporada e maior será a quantidade de CO2 emitida. Considerando a energia incorporada e o CO2 gerado, o resultado final mostra que, para envasar pequenos volumes (vidro de 290 mL e PET de 250 mL), os recipientes de vidro apresentam resultados melhores, enquanto, para envasar volumes maiores (acima de 600 mL), os recipientes de PET são os mais indicados.

ABSTRACT The present paper aims to assess and compare which material (PET or glass) provides a more sustainable life cycle for soft drink containers. Four glass containers, three returnable ones and one disposable were compared to five PET containers (polyethylene terephthalate), three disposable ones made from virgin material, one disposable made from 20% of recycled material and one returnable (RefPet). The CES-Selector/EcoAudit program, which considers five main stages of the product life cycle - material (obtaining raw material), production, transportation, use and disposal - , was used. The resulting indicators were the energy and the amount of CO2 emission. The results, for every 1,000 liters of soft drink bottled, prove that the reuse of containers is the most environmentally correct choice and show that in PET bottles the larger the container capacity the smaller the amount of PET material used, lower the energy and the lower the CO2 emission. On the other hand, for glass bottles, the result is opposite, that is, the larger the container capacity, the greater the amount of material used, the greater the embodied energy and the greater the CO2 emission. Considering the incorporated energy and the CO2 generated, the final result shows that glass containers present better results when filling small-volume packages (290 ml glass and 250 ml PET), while PET containers are the most suitable ones for larger volumes (above 600 ml).

Emissions of an agricultural engine using blends of diesel and hydrous ethanol / Emissões de motor agrícola utilizando misturas de óleo Diesel e etanol hidratado

The growing global demand of energy, the decrease of petroleum reserves and the current of environmental contamination problems, make it imperative to study renewable energy sources for use in internal combustion engines, in order to decrease the dependence on fossil fuels and reduce emissions of pollutant gases. This study aimed to evaluate the emissions of a diesel-cycle engine of an agricultural tractor that uses diesel S500 (B5) mixed with 3, 6, 9, 12 and 15% of hydrous ethanol. It determined emissions of CO2 (ppm), NOx (ppm), and opacity (k value) of gases. A standard procedure was applied considering eight operating modes (M1, M2, M3, M4, M5, M6, M7, and M8) by breaking with an electric dynamometer in a laboratory. The experimental design was completely randomized, with 60 replicates and a 6 x 8 factorial design. Greater opacity and gas emissions were observed when the engine operated with 3% ethanol, while lower emissions occurred with 12 and 15%. With these fuels, the reduction of opacity, CO2, and NOx, in relation to diesel oil, was 24.49 and 26.53%, 4.96 and 5.15%, and 6.59 and 9.70%, respectively. In conclusion, the addition of 12 and 15% ethanol in diesel oil significantly reduces engine emissions.(AU)

A crescente demanda mundial por energia, a diminuição das reservas de petróleo e os atuais problemas de poluição ambiental, instigam o estudo de fontes renováveis de energia para utilização nos motores de combustão interna, visando à diminuição da dependência do combustível fóssil e redução das emissões de gases poluentes. Este trabalho teve por objetivo avaliar as emissões de um motor ciclo Diesel de um trator agrícola utilizando óleo Diesel S500 (B5) e, em mistura com 3, 6, 9, 12 e 15% de etanol hidratado. As variáveis avaliadas foram as emissões de CO2 (ppm), NOx (ppm) e a opacidade (valor k) dos gases. Para a avaliação utilizou-se procedimento normalizado, com aplicação de oito modos de operação (M1; M2; M3; M4; M5; M6; M7 e M8), por meio da frenagem com um dinamômetro elétrico, em laboratório. O delineamento experimental foi inteiramente casualizado, com 60 repetições e no esquema fatorial 6x8. Os maiores valores de opacidade e emissões de CO2 e NOx foram alcançados com 3% de etanol, enquanto que os menores valores foram obtidos quando o motor utilizou 12 e 15%. Com estes combustíveis, a redução da opacidade, CO2 e NOx, em relação ao óleo diesel, foi de 24,49 e 26,53%; 4,96 e 5,15% e 6,59 e 9,70%, respectivamente. Conclui-se que, a adição de 12 e 15% de etanol no óleo diesel reduz significativamente as emissões do motor.(AU)

Emissions of an agricultural engine using blends of diesel and hydrous ethanol / Emissões de motor agrícola utilizando misturas de óleo Diesel e etanol hidratado

The growing global demand of energy, the decrease of petroleum reserves and the current of environmental contamination problems, make it imperative to study renewable energy sources for use in internal combustion engines, in order to decrease the dependence on fossil fuels and reduce emissions of pollutant gases. This study aimed to evaluate the emissions of a diesel-cycle engine of an agricultural tractor that uses diesel S500 (B5) mixed with 3, 6, 9, 12 and 15% of hydrous ethanol. It determined emissions of CO2 (ppm), NOx (ppm), and opacity (k value) of gases. A standard procedure was applied considering eight operating modes (M1, M2, M3, M4, M5, M6, M7, and M8) by breaking with an electric dynamometer in a laboratory. The experimental design was completely randomized, with 60 replicates and a 6 x 8 factorial design. Greater opacity and gas emissions were observed when the engine operated with 3% ethanol, while lower emissions occurred with 12 and 15%. With these fuels, the reduction of opacity, CO2, and NOx, in relation to diesel oil, was 24.49 and 26.53%, 4.96 and 5.15%, and 6.59 and 9.70%, respectively. In conclusion, the addition of 12 and 15% ethanol in diesel oil significantly reduces engine emissions.

A crescente demanda mundial por energia, a diminuição das reservas de petróleo e os atuais problemas de poluição ambiental, instigam o estudo de fontes renováveis de energia para utilização nos motores de combustão interna, visando à diminuição da dependência do combustível fóssil e redução das emissões de gases poluentes. Este trabalho teve por objetivo avaliar as emissões de um motor ciclo Diesel de um trator agrícola utilizando óleo Diesel S500 (B5) e, em mistura com 3, 6, 9, 12 e 15% de etanol hidratado. As variáveis avaliadas foram as emissões de CO2 (ppm), NOx (ppm) e a opacidade (valor k) dos gases. Para a avaliação utilizou-se procedimento normalizado, com aplicação de oito modos de operação (M1; M2; M3; M4; M5; M6; M7 e M8), por meio da frenagem com um dinamômetro elétrico, em laboratório. O delineamento experimental foi inteiramente casualizado, com 60 repetições e no esquema fatorial 6x8. Os maiores valores de opacidade e emissões de CO2 e NOx foram alcançados com 3% de etanol, enquanto que os menores valores foram obtidos quando o motor utilizou 12 e 15%. Com estes combustíveis, a redução da opacidade, CO2 e NOx, em relação ao óleo diesel, foi de 24,49 e 26,53%; 4,96 e 5,15% e 6,59 e 9,70%, respectivamente. Conclui-se que, a adição de 12 e 15% de etanol no óleo diesel reduz significativamente as emissões do motor.

Financial development, globalization, and CO2 emission in the presence of EKC: evidence from BRICS countries.

This study examines the impact of energy consumption, financial development, globalization, economic growth, and urbanization on carbon dioxide emissions in the presence of Environmental Kuznets Curve (EKC) model for BRICS economies, by using a family of econometric techniques robust to heterogeneity and cross-sectional dependence. Results from LM test, CIPS and CADF unit root test, Westerlund Cointegration test, the Dynamic seemingly unrelated regression (DSUR), and Dumitrescu-Hurlin Granger causality test show that (i) the data is cross sectionally dependent and heterogeneous; (ii) carbon dioxide emissions, energy consumption, financial development, globalization, economic growth, square of GDP and urbanization have integration of order one; (iii) the examined variables are co-integrated; (iv) energy consumption and financial development contribute to the carbon dioxide emissions whereas globalization and urbanization have negative but insignificant relationship with carbon dioxide emissions; (v) supports the EKC hypothesis in BRICS economies; (vi) bidirectional causality exists among energy consumption, financial development, economic growth and square of GDP with carbon dioxide emissions whereas globalization and urbanization have unidirectional relationship with carbon dioxide emissions. Since these panel techniques account for heterogeneity and cross-sectional dependence in their estimation procedure, the empirical results are robust and reliable for policy recommendations. Furthermore, this study also uses time series tests (ADF, P-P, and FMOLS) to find the empirical results for each of the country and finds mixed results. Empirical findings directed towards some important policy implications.

Classification of soil respiration in areas of sugarcane renewal using decision tree

The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soilmoisture > potential acidity.

Classification of soil respiration in areas of sugarcane renewal using decision tree

The use of data mining is a promising alternative to predict soil respiration from correlated variables. Our objective was to build a model using variable selection and decision tree induction to predict different levels of soil respiration, taking into account physical, chemical and microbiological variables of soil as well as precipitation in renewal of sugarcane areas. The original dataset was composed of 19 variables (18 independent variables and one dependent (or response) variable). The variable-target refers to soil respiration as the target classification. Due to a large number of variables, a procedure for variable selection was conducted to remove those with low correlation with the variable-target. For that purpose, four approaches of variable selection were evaluated: no variable selection, correlation-based feature selection (CFS), chisquare method (χ2) and Wrapper. To classify soil respiration, we used the decision tree induction technique available in the Weka software package. Our results showed that data mining techniques allow the development of a model for soil respiration classification with accuracy of 81 %, resulting in a knowledge base composed of 27 rules for prediction of soil respiration. In particular, the wrapper method for variable selection identified a subset of only five variables out of 18 available in the original dataset, and they had the following order of influence in determining soil respiration: soil temperature > precipitation > macroporosity > soilmoisture > potential acidity.(AU)

Metabolism and water loss rate of the haematophagous insect Rhodnius prolixus: effect of starvation and temperature.

Haematophagous insects suffer big changes in water needs under different levels of starvation. Rhodnius prolixus is the most important haematophagous vector of Chagas disease in the north of South America and a model organism in insect physiology. Although there have been some studies on patterns of gas exchange and metabolic rates, there is little information regarding water loss in R. prolixus. We investigated whether there is any modulation of water loss and metabolic rate under different requirements for saving water. We measured simultaneously CO2 production, water emission and activity in individual insects in real time by open-flow respirometry at different temperatures (15, 25 and 35°C) and post-feeding days (0, 5, 13 and 29). We found: (1) a clear drop in metabolic rate between 5 and 13 days after feeding that cannot be explained by activity and (2) a decrease in water loss rate with increasing starvation level, by a decrease in cuticular water loss during the first 5 days after feeding and a drop in the respiratory component thereafter. We calculated the surface area of the insects and estimated cuticular permeability. In addition, we analysed the pattern of gas exchange; the change from a cyclic to a continuous pattern was affected by temperature and activity, but it was not affected by the level of starvation. Modulation of metabolic and water loss rates with temperature and starvation could help R. prolixus to be more flexible in tolerating different periods of starvation, which is adaptive in a changing environment with the uncertainty of finding a suitable host.

Soil respiration in cucumber field under crop rotation in solar greenhouse

Crop residues are the primary source of carbon input in the soil carbon pool. Crop rotation can impact the plant biomass returned to the soil, and influence soil respiration. To study the effect of previous crops on soil respiration in cucumber (Cucumis statirus L.) fields in solar greenhouses, soil respiration, plant height, leaf area and yield were measured during the growing season (from the end of Sept to the beginning of Jun the following year) from 2007 to 2010. The cucumber was grown following fallow (CK), kidney bean (KB), cowpea (CP), maize for green manure (MGM), black bean for green manure (BGM), tomato (TM), bok choy (BC). As compared with CK, KB, CP, MGM and BGM may increase soil respiration, while TM and BC may decrease soil respiration at full fruit stage in cucumber fields. Thus attention to the previous crop arrangement is a possible way of mitigating soil respiration in vegetable fields. Plant height, leaf area and yield had similar variation trends under seven previous crop treatments. The ratio of yield to soil respiration revealed that MGM is the crop of choice previous to cucumber when compared with CK, KB, CP, BGM, TM and BC.

Soil respiration in cucumber field under crop rotation in solar greenhouse

Crop residues are the primary source of carbon input in the soil carbon pool. Crop rotation can impact the plant biomass returned to the soil, and influence soil respiration. To study the effect of previous crops on soil respiration in cucumber (Cucumis statirus L.) fields in solar greenhouses, soil respiration, plant height, leaf area and yield were measured during the growing season (from the end of Sept to the beginning of Jun the following year) from 2007 to 2010. The cucumber was grown following fallow (CK), kidney bean (KB), cowpea (CP), maize for green manure (MGM), black bean for green manure (BGM), tomato (TM), bok choy (BC). As compared with CK, KB, CP, MGM and BGM may increase soil respiration, while TM and BC may decrease soil respiration at full fruit stage in cucumber fields. Thus attention to the previous crop arrangement is a possible way of mitigating soil respiration in vegetable fields. Plant height, leaf area and yield had similar variation trends under seven previous crop treatments. The ratio of yield to soil respiration revealed that MGM is the crop of choice previous to cucumber when compared with CK, KB, CP, BGM, TM and BC.(AU)