Energy analysis for faba bean production: A case study in Golestan province, Iran

Kazemi, Hossein; Shahbyki, Malihe; Baghbani, Sepideh

doi:10.1016/j.spc.2015.07.004

Cited by 25 publications

(22 citation statements)

References 30 publications

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“…Despite the use of the same quantity of energy input every year, the effect of tillage system was significant with the highest energy input being used in CT (15229.2 MJ ha -1 ) and the lowest in NT (10745 MJ ha -1 ). Our average energy input value was in line with the one (13833.7 MJ ha -1 ) reported by Kazemi et al [12] for faba bean production across 30 farms in Golestan province of Iran. Their energy output, however, were about 50% less than the average value reported in this study.…”

Section: Input/output Analysissupporting

confidence: 90%

“…In today's agricultural practices, soil tillage and applications of chemicals are the greatest consumers of energy and labor. Since fertilization is lowered to the minimum due to N 2 fixation from faba bean, the selection of an appropriate tillage method will lead to an improvement of energy use efficiency, reduce the input costs [11] and increase cop profitability, and therefore system sustainability [12]. The application of no tillage practice [13] in order to adapt the crop to dry and low rainfall conditions while reducing the reliance on fossil fuel has been tested and described as potentially advantageous adaptations of faba bean to rainfed cultivation in drylands.…”

Section: Introductionmentioning

confidence: 99%

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Implications of No-tillage System in Faba Bean Production: Energy Analysis and Potential Agronomic Benefits

Ali¹,

Tedone²,

Verdini³

et al. 2018

TOASJ

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Background: Given the nutritional value of faba bean, however its susceptibility to water deficit, especially in Mediterranean environment, tillage practices need to be modified in order to adapt the crop to dry and low rainfall conditions and promote the interest in its cultivation. Objective: To identify whether no-tillage system can be considered as a sustainable means in faba bean cultivation under Mediterranean condition. Method: The study was conducted during a 6-year period (2010/11 to 2015/16) in southern Italy within wheat-faba bean rotation framework of a long-term experiment. The effect of No-Tillage (NT) on agronomic and energy parameters of faba bean (Vicia faba L.) cultivation was evaluated and compared to those of Conventional (CT) and Reduced (RT) Tillage. Results: The agronomic results indicate that NT performed better and/or is comparable to CT, while its application was 28% and 30% more energy efficient compared to CT and RT respectively. For agronomic parameters, tillage had a significant effect on number of plant m-2, grain yield, grain protein content and 100-seed weight whereas year effect was significant for yield components and quality parameters. Energy indexes, instead, were significantly affected by both factors. NT gave the best results in terms of energy efficiency, energy intensity and net energy, and consumed 39% and 36% less non-renewable energy than CT and RT, respectively. Conclusion: Our findings revealed that the key benefit of NT in rainfed faba bean is its ability to produce sufficient yield of high quality with a significant reduction in energy inputs entailed the fewest field operations and therefore lowest energy requirements.

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Section: Input/output Analysissupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Implications of No-tillage System in Faba Bean Production: Energy Analysis and Potential Agronomic Benefits

Ali¹,

Tedone²,

Verdini³

et al. 2018

TOASJ

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“…Faba (FB) beans, ranked as the third‐most important grain legume, are a suitable crop for sustainable agriculture and are considered as cheap protein source. FB beans are produced in many countries, especially in African and Asian regions accounting for 80% of the production of dry FB beans (Alghamdi, Migdadi, Ammar, Paull, & Siddique, ; Etemadi et al., ; Kazemi, Shahbyki, & Baghbani, ). Lima (LM) beans, one of the 12 primary grain legumes, are widely cultivated in the tropics with yields up to 284.4 tons/km 2 and are an important protein source for millions of Nigerians (Betancur, Ancona, Guerrero, Camelo Matos, & Ortiz, ; Ezeagu & Ibegbu, ; Ormeño‐Orrillo, Vinuesa, Zúñiga‐Dávila, & Martínez‐Romero, ; Shlichta, Cuny, Hernandez‐Cumplido, Traine, & Benrey, ).…”

Section: Introductionmentioning

confidence: 99%

Whole faba bean flour exhibits unique expansion characteristics relative to the whole flours of lima, pinto, and red kidney beans during extrusion

Masli

Ganjyal

2019

Journal of Food Science

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Determining the impacts of extrusion conditions on extrudate characteristics of whole beans flours is critical to find the suitable types of beans to use for making direct expanded products. Whole bean flours of four different bean types, faba, lima, pinto, and red kidney, were extruded. The influence of barrel temperature (120, 140, and 160°C), moisture content (17%, 21%, and 25%), and screw speed (150, 200, and 250 rpm) on process and product responses was studied with a corotating twin screw extruder. The barrel temperature, moisture content, screw speed, and variety of bean had significant influence on process and product responses, back pressure (MPa), torque (N·m), specific mechanical energy (kJ/kg), expansion ratio, water absorption index (g/g), and water solubility index (%) (P < 0.05). Faba bean extrudates had a significantly higher expansion ratio compared to other beans (lima, pinto, and red kidney beans) even though faba bean contained significantly higher protein and higher crude fiber contents (P < 0.05).Keywords: extrusion, faba bean, lima bean, pinto bean, red kidney bean Practical Application: The outputs of this research will be helpful to the food industry in the production of high nutrient-dense food products from whole beans by maintaining the expansion and texture of the products. The data should assist to choose the suitable types of whole bean flours and the optimum processing conditions for making direct expanded extruded products.

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“…This input was the largest contributor of the total energy consumption, comprising 58.55% (Figure ). Several researchers have reported that the energy consumption of chemical fertilizer was the highest energy consumer during Iranian crop production in general . Soheili‐Fard et al .…”

Section: Resultsmentioning

confidence: 99%

Integration of principal component analysis and artificial neural networks to more effectively predict agricultural energy flows

Nikkhah

Rohani

Rosentrater

et al. 2019

Env Prog and Sustain Energy

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There are some studies regarding the prediction of agricultural energy flows using artificial neural networks (ANNs). These models are quite sensitive to correlations amongst inputs, and, there are often strong correlations amongst energy inputs for agricultural systems. One potential method to remediate this problem is to use principal component analysis (PCA). Therefore, the purpose of this research was to predict energy flows for a specific agricultural system (Iranian tea production) via a novel methodology based on ANNs, and using principal components as model inputs, not raw data. PCA results showed that the first and second components could account for more than 99% of variation in the data, thus the dimensions of the data set could be decreased from six to two for the prediction of energy flows for Iranian tea production. Using these principal components as inputs, an ANN model with 2–15–1 structure was determined to be optimal for energy flow modeling of this system. To conclude, the results of this study highlighted that the use of PC as ANN inputs improved ANN model prediction through reducing its complexity and eliminating data colinearity. Many agricultural systems could benefit from using this methodology for energy modeling. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13130, 2019

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Energy analysis for faba bean production: A case study in Golestan province, Iran

Cited by 25 publications

References 30 publications

Implications of No-tillage System in Faba Bean Production: Energy Analysis and Potential Agronomic Benefits

Implications of No-tillage System in Faba Bean Production: Energy Analysis and Potential Agronomic Benefits

Whole faba bean flour exhibits unique expansion characteristics relative to the whole flours of lima, pinto, and red kidney beans during extrusion

Integration of principal component analysis and artificial neural networks to more effectively predict agricultural energy flows

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