Agricultural applications: energy uses and audits

On-farm energy efficiency is becoming increasingly important in the context of rising energy costs and concerns over greenhouse gas (GHG) emissions. Energy inputs represent a major and rapidly increasing cost to the growers around the world. This entry reviews the currently available tools and technologies for conducting on-farm energy audits/assessments. Opportunities to reduce operational energy inputs and impacts on GHG emissions are also discussed

Application of spectroscopic method to predict sugar content of sugarcane internodes

The aim of this study was to investigate the potential of near-infrared (NIR) reflectance spectroscopy for predicting sugar content of sugarcane from internode samples. NIR spectral data were measured using a full-range spectroradiometer (FRS) in the wavelength region between 350 and 2,500 nm based on cross sectional scanning method (CSSM) and skin scanning method (SSM). Statistical models were developed using the partial least square (PLS) to interpret the spectral data and develop calibration model for the sugar content (Brix) of sugarcane. Both CSSM and SSM had good prediction accuracies in predicting Brix values, with the corresponding correlation of determination (R2) values of 0.92 and 0.82 and root mean square error of prediction (RMSEP) of 1.03 and 1.50 Brix respectively. These results showed that the FRS can be used to predict the sugar content from internode samples using CSSM or SSM. However, CSSM was found to give better prediction accuracy than SSM. These findings showed that spectroscopic methods have the potential to be applied for rapid determination of sugar content from stalk samples in the fields

Prediction of sugarcane quality from juice samples using portable spectroscopy

Rapid determination of sugarcane quality using low-cost and portable equipment is more practical for field use. Thus, this study explored the potential application of a portable visible and shortwave near infrared spectroradiometer (VNIRS) to predict pol and brix from sugarcane juice samples. A total of 100 sugarcane juice samples for each clear and raw juice samples were assessed. The spectral data were collected by scanning the juice samples in a cuvette with 10 mm path length using transmittance mode. Partial least squares (PLS) and principal component analysis (PCA) were applied to interpret the spectra and develop both calibration and prediction models. The prediction performances for the clear juice samples were good with coefficient of determination (R2) values of pol and brix were 0.85 and 0.84, respectively. For the raw juice samples, the prediction performances were acceptable with R2 values for pol and brix were 0.73 and 0.74, respectively. Based on these results, it was concluded that the VNIRS combined with PLS models could be applied to predict sugarcane quality from both clear and raw sugarcane juices

Stability and error analysis of one-leg methods for nonlinear delay differential equations

AbstractThis paper is concerned with the numerical solution of delay differential equations (DDEs). We focus on the stability behaviour and error analysis of one-leg methods with respect to nonlinear DDEs. The new concepts of GR-stability, GAR-stability and weak GAR-stability are introduced. It is proved that a strongly A-stable one-leg method with linear interpolation is GAR-stable, and that an A-stable one-leg method with linear interpolation is GR-stable, weakly GAR-stable and D-convergent of order s, if it is consistent of order s in the classical sense

Development in energy generation technologies and alternative fuels for agriculture

Energy use is now seen as one of the key indicators of sustainable development. Renewable energy sources should contribute to the energy security. Agriculture can also play a dual role as an energy user and as an energy supplier in the form of bioenergy. Advanced technologies and alternative fuels can be used to improve the efficiency of agricultural production, while minimizing energy consumption in the farming sector

On-farm energy use in the dairy industries

Dairying is one of largest agricultural industries in Australia. This paper reviews the on-farm energy use in various dairy operations. It is found that the total direct on-farm energy needed to produce one kilogram of milk varies between 0.41-0.83 MJ/kg milk in Australia. This is in comparison with 0.19-2.47 MJ/kg milk overseas. The differences in energy uses are mainly due to different farming systems and technologies adopted and also different analysis methods employed. The large variation of energy uses indicates the significant opportunities for reducing energy use

On-farm energy use in the grain and horticultural industries

Agriculture and the related primary industry requires energy as an important input. Energy is needed to a differing extent in all the stages of the agri-food chain. In this paper, on-farm energy use in the grain and horticultural industries is evaluated. It is found that the energy use varies significantly with the farm enterprises and also the farming systems, including irrigation and heating/cooling methods. The total direct on-farm energy use for grain grown under dryland conditions with no tillage may be as low as 0.35 GJ/ha, while for horticultural products, the direct on-farm energy use may reach up to 20000 GJ/ha for tomatoes grown in greenhouses. The large variation of energy uses may indicate the significant opportunities for reducing energy use in these industries

Developing life cycle inventory for life cycle assessment of Australian cotton

Life Cycle Assessment (LCA) is an internationally recognised approach for evaluating the environmental impacts of products and services. In this paper, the potential issues in the development of a consistent and comprehensive life cycle inventory (LCI) data are illustrated in the context of Australian cotton industry. These include diversity and variable nature of farming practices, and the inherent complexities such as the inter-linkages between co-products. For the implementation of LCI, the choices of functional unit and system boundary, definition of regional sub-sectors, methods of energy assessments, and rules of allocations of inputs and emissions are discussed. It is shown that for cotton production, the contribution of on-farm indirect 'chemical' inputs is particularly important, accounting for up to 50–80% of the total energy input in the life cycle. The need for quantified trade off analysis between alternative systems in the LCA context is also emphasized

Gasification of non-woody biomass: a literature review

Non-woody biomass, having a lower lignin content than woody materials, is a common waste material found in agricultural processing plants and fields. Non-woody biomass is often bulky and has a comparatively low energy content. However, non-woody materials sourced from agricultural waste are abundant and cheap. Experimental studies into gasification of non-woody biomass have been conducted by various researchers. This paper reviews feedstock characteristics, pre-treatments, gasification methods, and future directions of this technology. Due to the heterogeneous nature of non-woody biomass, it is critical to apply suitable pre-treatments prior to gasification. Combining non-woody biomass with a small percentage of high grade carbon sourced from biochar or coal into fuel pellets for co-gasification has the potential to improve fuel quality. Synergistic effects of non-woody biomass-coal/charcoal co-gasification can also reduce tar formation and increase the occurrence of mineral based catalytic reactions. Factors influencing these effects are often complex and require further investigation. 15–20% of the energy content of fuel pellets may be needed to power the biomass pre-treatment process. The gasification of pelletised non-woody waste provides an attractive alternative fuel source to achieve agricultural energy self-sufficiency and off-grid operation

Special issue 'Advances in postharvest process systems' [Editorial]

The world population is predicted to increase from the present 7.7 billion to 9.7 billion in 2050, demanding a significant increase in food supply and production. However, around 25–30% of food is wasted worldwide every year due to poor postharvest supply chain design and management in different stages of the food supply chain, including postharvest handling, processing, and storage systems. This special issue presents state-of-the-art information on the important innovations and research in the agricultural and food industry. Different novel technologies and their implementation to optimize postharvest processes and reduce losses are reviewed and explored. In particular, it examines a range of recently developed and improved technologies and systems to help the industry and growers to manage and minimize postharvest losses, enhance reliability and sustainability in the postharvest food value chain, and generate high-quality products that are both healthy and appealing to consumers. This special issue consists of three sections, focusing on food storage and preservation technologies [1–4], food processing technologies [5–8], and the applications of advanced mathematical modeling and computer simulations [9–11]. We wish to acknowledge the expert contributions of all authors here. We also wish to acknowledge and thank MDPI staff for their professional assistance in editing the published articles. We sincerely hope that this special issue will assist all readers and stakeholders working in or are associated with the fields of agriculture, agri-food chain, and technology development and promotion. After all, efficient postharvest technology is an essential and key factor underlying future global food security, and ultimately human survival and development