To estimate energy use efficiency for sweet potato production in Bangladesh under subtropical climatic conditions, a study was conducted with 60 individuals (12 producers for each sweet potato variety) by using a structural questionnaire. The results revealed that the majority of the energy input was consumed by the pre-harvest activities (22,313.55 MJ ha−1 or 90.85%), of which fertilizer application (36.84%) and irrigation (35.24%) consumed the most energy input, with only 9.15% (2,248.42 MJ ha−1) consumed by the post-harvest activity for sweet potato production. The energy input involved in the production system was similar to the direct (12,149.76 MJ ha−1 or 49.47%) and indirect (12,412.21 MJ ha−1 or 50.53%) sources, while it was much higher in non-renewable sources (22,884.21 MJ ha−1 or 93.17%) with a minimum (1,677.76 MJ ha−1 or 6.83%) from renewable sources. The average energy use efficiency, energy productivity, specific energy, net energy, energy profitability and water-energy productivity of orange-fleshed sweet potato (OFSP) varieties 4.36, 1.22 kg MJ−1, 0.83 MJ kg−1, 82,511.73 MJ ha−1, 3.36 and 1.32 g m−3 MJ−1, respectively. The OFSP varieties showed better performance in respect of all the energy and water use indicators.

  • Farmers generally grow crops in riverbank areas which need low irrigation; for example, sweet potato.

  • The estimation of energy and water use indicators are important for sweet potato, since this crop needs minimal water.

  • The study estimated energy and water use indicators for the production of sweet potato.

  • The orange-fleshed sweet potatoes showed better performance in respect of energy and water use indicators.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Sweet potato (Ipomoea batatas L.) is one of the most important root crops and considered the seventh most important food crop globally and are grown all over the world. Sweet potatoes are now considered a super food as they contain many important vitamins, minerals, fermented sugars (glucose, fructose, sucrose) dietary fiber, a small amount of protein, lipids, antioxidants and other functional components (Ferrari et al. 2013; Wang et al. 2016). Likewise, sweet potato is an ideal food in terms of energy (Bovell-Benjamin 2007; Rumbaoa et al. 2009). Moreover, sweet potato is a dependable source of Vitamin A, Vitamin B, Iron, Copper and Manganese (Szalay 2017). The antioxidants present in sweet potatoes are long-lasting in the human body and can be beneficial in preventing deadly diseases like diabetes and cancer (Islam et al. 2002; Rumbaoa et al. 2009). In addition to starch, flour, sugar, alcohol and other industrial products, sweet potatoes are currently considered a significant source of feedstock for organic ethanol production (Lee et al. 2006; Adenuga 2010). About 12.5% bioethanol is obtained from fresh sweet potatoes (Qiu et al. 2010). Like other biofuels, bioethanol produced from sweet potatoes can play an important role as an environmentally friendly source of net energy (Flores et al. 2016).

In Bangladesh, sweet potato is grown in the riverbank areas. Currently, about 23,571 tons of sweet potato are being produced from an area of 23,014 hectares of land with an average yield of 10.25 t ha−1 (FAOSTAT 2021). Sweet potato cultivable area and total production in Bangladesh are oscillating. The total production of sweet potatoes increased by 3.16% from 2014 to 2016 and the area increased by 1.94% (FAOSTAT 2015, 2017). Conversely, from 2016 to 2019, it decreased the cultivable area by 11% and also reduced production by 10% (BBS 2020). According to the report of FAOSTAT (2021), the total cultivable area of sweet potatoes in Bangladesh has decreased by 26% and production by 23% in the last decade due to the lower availability of the planting materials (vine) at the farm level, high crop competition, less storability, higher production cost and difficult marketing channels.

Children in Bangladesh are at substantial risk for vitamin-A deficiency-induced night blindness (Mahmud et al. 2021a, 2021b). To combat the vitamin-A deficiency; the Bangladesh Agricultural Research Institute (BARI) has developed several high-yielding vitamin-A enriched sweet potato varieties that will play a significant role in increasing the sweet potato yield and improving the nutrition of the Bangladeshi people.

Energy is an important component to evaluate and optimize agricultural products (Mohammadi et al. 2008; Stolarski et al. 2019). In developing countries like Bangladesh, it is necessary to increase agricultural productivity by using limited resources to feed the ever-increasing population. On the other hand, limited arable land has increased the intensive use of energy and natural resources in agriculture (Flores et al. 2016).

Often, farmers do not know how to utilize their resources, and due to low cost and availability, they use their resources excessively and inefficiently. So, increasing input power is required to obtain maximum yield but farmers may not get higher profits despite increased input power due to increased production costs (Erdal et al. 2007). Effective use of energy in agriculture is one of the conditions for sustainable agricultural production as it helps in financial savings, conservation of fossil fuels, resource conservation and reduction of air pollution (Ozkan et al. 2004, 2007; Singh et al. 2004), and also prevents the destruction of natural resources and improves sustainable agriculture (Rafiee et al. 2010; Zhang et al. 2021). Input and output energy are the two crucial factors for energy analysis and environmental efficiency in crop production. Energy analysis is important to ensure efficient and environmentally-friendly production systems (Schroll 1994; Ozkan et al. 2004). The key to sustainable energy management is the improvement of energy efficiency. Efforts need to be made to produce and conserve input energy without affecting the output (production) (Singh et al. 2004). Several studies have focused on energy use for agricultural production in different crops (Kallivroussis et al. 2002; Ozkan et al. 2004, 2007, 2011; Canakci et al. 2005; Hatirli et al. 2005; Sartori et al. 2005; Shahin et al. 2008; Beheshti Tabar et al. 2010; Mobtaker et al. 2010; Mousavi-Avval et al. 2010; Flores et al. 2016; Nabavi-Pelesaraei et al. 2016; Tang et al. 2022). Therefore, sustainable agriculture requires efficient use of energy to increase production and productivity (Ozkan et al. 2004, 2007). Unfortunately, no studies have been conducted on the energy and water use indicators of sweet potato production in Bangladesh. In that case, it is necessary to assess the existing energy to increase energy efficiency in sweet potato production.

Water is an essential element for agricultural production. Globally, agriculture will be the main user of water resources (de Fraiture et al. 2007). Hence, ensuring the supply and optimal use of water for agriculture has become a matter of high relevance for stakeholders and scientists worldwide (Prochnow et al. 2012). In addition to increasing population growth, climate change poses a threat to long-term environmental and economic sustainability (Koech & Langat 2018). Furthermore, irrigators are under pressure to ensure food security for a growing population. The current challenge is to ensure that agricultural water management is environmentally sustainable to make a reasonable profit and meet the needs of a growing population (Cosgrove & Loucks 2015; Rockström et al. 2017). Environmentalists, irrigators and policymakers have different views on what constitutes efficient use of water in agriculture and how to improve it. As a result, confusion arises regarding the interpretation of water use data for crop production (Perry 2011).

Irrigation is another major energy user in agricultural production (Smerdon & Hiler 1985; Khan et al. 2009). All other operations in agriculture can be several times more than just irrigation energy. Efficient use of water increases energy requirements in agricultural production. The need for energy in agricultural production increases with the effective use of water. Meanwhile, in developed countries, the conversion rate of energy gained to extracted water is about 20% but in many countries, it is close to 12.5% or less (Aked 2009). Thus, irrigation should be properly planned and managed to conserve both water and energy inputs to achieve sustainable agriculture. As there are no studies on energy efficiency and water use indices for sweet potato production in Bangladesh, consider that this study has been conducted.

Site description and climatic condition

The energy efficiency and water use indices were estimated from a study which was conducted around Saghata (25.07–25°10′N and 89.28–89°30′E) of Gaibandha district, Bangladesh (representing AEZ 2: Active Tista Floodplain agro-ecological zone of Bangladesh) (Figure 1). The area of experimentation was under a subtropical climate with a rainfall of 42–53 mm during the crop growing season (November–March). The monthly mean maximum and minimum temperature ranges from 26 to 34 °C and 12 to 18 °C in the respected area. The soil type was gray stratified sand and irregular patterns of silt, from strongly acidic to slightly acidic (pH: 3.8–6.4) with very low to low organic matter content. Zn and B contents with soil fertility levels are very low to moderate. A detailed overview of the site is also available in our previously published papers (Mahmud et al. 2021a, 2021b).
Figure 1

Geographical location of the survey area under sweet potato production.

Figure 1

Geographical location of the survey area under sweet potato production.

Close modal

System boundary of sweet potato production

The production system of sweet potatoes at the farmer level is shown in Figure 2. Pre-harvest activities included land preparation, cutting and planting of sweet potato vines into the main field, fertilizer application, irrigation, weeding and earthing up, application of pesticides, etc. On the other hand, post-harvest activities included the removal of sweet potato vines, collection of roots, stacking, cleaning, sorting, bagging and transport from the field to the market for selling.
Figure 2

The system boundary of sweet potato production used in the estimation.

Figure 2

The system boundary of sweet potato production used in the estimation.

Close modal

Data collection

The yield data of four orange-fleshed sweet potatoes (OFSP)-BARI Mistialu-8 (BARI SP-8); BARI Mistialu-12 (BARI SP-12); BARI Mistialu-14 (BARI SP-14); BARI Mistialu-15 (BARI SP-15); with a white-bred local sweet potato variety were collected at the time of harvest from a unit area of 100 m2. For the structural survey, questionnaires were developed for face-to-face interviews of the sweet potato producers and from these interviews, the energy efficiency and water use indices-related data (including all input costs like tillage, fertilizers, irrigation, crop protection, harvesting, cleaning, transport and marketing, etc.) were collected. The interview was conducted with 60 individuals (12 producers for each sweet potato variety) by a random selection method (Kizilaslan 2009). In all the cases, the averaged data were used for the calculation in respect of all the parameters.

Estimation of energy input and output of sweet potato production

Energy used in human labor, tractor and other machinery power, diesel as fuel, fertilizers, pesticides and irrigation were identified as inputs and sweet potato roots were considered as output. The amount of input energy used per hectare was multiplied by the energy coefficient equivalent referred to in Table 1.

Table 1

Energy equivalent of inputs and output in sweet potato production

Input/outputUnitEnergy (MJ unit1)References
Inputs 
 Human labor 1.96 Mohammadi et al. (2010); Rafiee et al. (2010)  
 Tractor 93.61 Canakci et al. (2005)  
 Machinery 62.70 Singh et al. (2002); Erdal et al. (2007); Singh (2002)  
 Diesel 47.80 Canakci et al. (2005)  
 Fertilizer 
 Nitrogen (N) kg 66.14 Rafiee et al. (2010); Yilmaz et al. (2005)  
 Phosphorus (P) kg 12.44 Rafiee et al. (2010); Yilmaz et al. (2005)  
 Potassium (K) kg 11.15 Rafiee et al. (2010)  
 Sulphur (S) kg 1.12 Rafiee et al. (2010)  
 Zinc (Zn) kg 8.4 Rafiee et al. (2010)  
 Boron (B) kg 4.65 Jiménez-González et al. (2000)  
 Insecticides kg 101.20 Ozkan et al. (2007)  
 Irrigation m3 0.63 Hatirli et al. (2005)  
Output 
 Sweet potato roots kg 3.59 Oke & Workneh (2013)  
Input/outputUnitEnergy (MJ unit1)References
Inputs 
 Human labor 1.96 Mohammadi et al. (2010); Rafiee et al. (2010)  
 Tractor 93.61 Canakci et al. (2005)  
 Machinery 62.70 Singh et al. (2002); Erdal et al. (2007); Singh (2002)  
 Diesel 47.80 Canakci et al. (2005)  
 Fertilizer 
 Nitrogen (N) kg 66.14 Rafiee et al. (2010); Yilmaz et al. (2005)  
 Phosphorus (P) kg 12.44 Rafiee et al. (2010); Yilmaz et al. (2005)  
 Potassium (K) kg 11.15 Rafiee et al. (2010)  
 Sulphur (S) kg 1.12 Rafiee et al. (2010)  
 Zinc (Zn) kg 8.4 Rafiee et al. (2010)  
 Boron (B) kg 4.65 Jiménez-González et al. (2000)  
 Insecticides kg 101.20 Ozkan et al. (2007)  
 Irrigation m3 0.63 Hatirli et al. (2005)  
Output 
 Sweet potato roots kg 3.59 Oke & Workneh (2013)  

Estimation of energy indicators of sweet potato

Energy indices were calculated based on input and output energy equivalents. The energy use efficiency, energy productivity, specific energy or energy intensity, net energy and energy profitability were calculated using the formula (Rafiee et al. 2010):
(1)
(2)
(3)
(4)
(5)

Estimation of water use indicators of sweet potato

The irrigation water use indicators in sweet potato production were calculated using the following formula (Khan et al. 2009):
(6)
(7)
(8)
(9)

Root yield of sweet potato

The highest sweet potato root yield ranging from 25.65 to 38.70 t ha−1 was recorded from BARI SP-8 with an average of 31.90 t ha−1 followed by an average of 30.34 t ha−1 in BARI SP-12, slightly lower in BARI SP-14 (28.98 t ha−1) like BARI SP-15 (28.08 t ha−1). The lowest root yield of sweet potato ranged from 12.50 to 22.50 t ha−1 was observed in the local (Pingra) cultivar with an average value of 18.91 t ha−1 (Table 2). The details of the other statistical characteristics are presented in Table 2.

Table 2

Statistical properties of the analyzed data of sweet potato

ItemsBARI Mistialu-8BARI Mistialu-12BARI Mistialu-14BARI Mistialu-15Local
Mean 31.90 30.34 28.98 28.08 18.91 
Standard Error 1.09 1.05 1.16 1.02 1.04 
Median 31.06 30.03 29.12 28.20 20.28 
Standard Deviation 3.77 3.64 4.02 3.52 3.61 
Sample Variance 14.19 13.27 16.13 12.40 13.00 
Coefficient of Variation 11.81 12.00 13.86 12.54 19.06 
Kurtosis −0.29 −0.20 −0.76 0.58 −0.81 
Skewness 0.34 0.06 0.25 −0.31 −0.84 
Range 13.05 12.07 12.90 12.71 10.00 
Minimum 25.65 24.67 23.00 21.30 12.50 
Maximum 38.70 36.74 35.90 34.01 22.50 
Sum 382.77 364.13 347.77 336.96 226.97 
Count 12.00 12.00 12.00 12.00 12.00 
Confidence Level (95.0%) 2.39 2.31 2.55 2.24 2.29 
Upper CI 34.29 32.66 31.53 30.32 21.21 
Lower CI 29.50 28.03 26.43 25.84 16.62 
ItemsBARI Mistialu-8BARI Mistialu-12BARI Mistialu-14BARI Mistialu-15Local
Mean 31.90 30.34 28.98 28.08 18.91 
Standard Error 1.09 1.05 1.16 1.02 1.04 
Median 31.06 30.03 29.12 28.20 20.28 
Standard Deviation 3.77 3.64 4.02 3.52 3.61 
Sample Variance 14.19 13.27 16.13 12.40 13.00 
Coefficient of Variation 11.81 12.00 13.86 12.54 19.06 
Kurtosis −0.29 −0.20 −0.76 0.58 −0.81 
Skewness 0.34 0.06 0.25 −0.31 −0.84 
Range 13.05 12.07 12.90 12.71 10.00 
Minimum 25.65 24.67 23.00 21.30 12.50 
Maximum 38.70 36.74 35.90 34.01 22.50 
Sum 382.77 364.13 347.77 336.96 226.97 
Count 12.00 12.00 12.00 12.00 12.00 
Confidence Level (95.0%) 2.39 2.31 2.55 2.24 2.29 
Upper CI 34.29 32.66 31.53 30.32 21.21 
Lower CI 29.50 28.03 26.43 25.84 16.62 

The highest yield increased by 68.7% in BARI SP-8, next to BARI SP-12 (60.4%), BARI SP-14 (53.2%) and BARI SP-15 (48.5%) over the local sweet potato cultivar (Figure 3). Mahmud et al. (2021a) reported that the root yield of BARI SP-8 was 23.96–35.54 t ha−1 with an average of 29.57 t ha−1, 22.50–37.67 t ha−1 in BARI SP-12 with an average of 30.24 t ha−1 and 21.72–30.85 t ha−1 with an average of 27.02 t ha−1 in BARI SP-14 across the different agro-ecological zones of Bangladesh mainly due to the different soil and agro-climatic conditions. They also reported that the average yield increase rate was 44.30–61.50% over the local sweet potato cultivar, similar to our study.
Figure 3

Mean root yield (t ha−1) of sweet potato varieties in the farmed fields in the study area (vertical bars indicate the standard error of the mean).

Figure 3

Mean root yield (t ha−1) of sweet potato varieties in the farmed fields in the study area (vertical bars indicate the standard error of the mean).

Close modal

Energy input and output of sweet potato production

The input–output energy of sweet potato production has been presented in Table 3. The total input energy was 24,561.97 MJ ha−1 for all the sweet potato cultivars. The maximum energy output was observed from the BARI SP-8 (114,511.65 MJ ha−1), followed by BARI SP-12 (108,935.18 MJ ha−1), BARI SP-14 (104,040.78 MJ ha−1) and BARI SP-15 (100,807.20 MJ ha−1), respectively (Table 3).

Table 3

Energy input and output which were used in sweet potato production in the subtropical climate of Bangladesh

Input/outputUnitQuantity (ha−1)Total energy equivalent (MJ ha−1)
Inputs 
 Human labor 856 1,677.76 
 Tractor 14 1,310.54 
 Other Machinery 30 1,881.00 
 Diesel 140 6,692.00 
 Fertilizer   9,018.27 
 Nitrogen (N) kg 120 7,936.80 
 Phosphorus (P) kg 30 373.20 
 Potassium (K) kg 60 669.00 
 Sulphur (S) kg 15 16.80 
 Zinc (Zn) kg 2.11 17.72 
 Boron (B) kg 1.02 4.74 
 Insecticides kg 202.40 
 Irrigation m3 6,000 3,780.00 
Total input   24,561.97 
Output (Sweet potato roots) 
 BARI SP-8 kg 31,897 114,511.65 
 BARI SP-12 kg 30,344 108,935.18 
 BARI SP-14 kg 28,981 104,040.78 
 BARI SP-15 kg 28,080 100,807.20 
 Local kg 18,914 67,901.86 
Input/outputUnitQuantity (ha−1)Total energy equivalent (MJ ha−1)
Inputs 
 Human labor 856 1,677.76 
 Tractor 14 1,310.54 
 Other Machinery 30 1,881.00 
 Diesel 140 6,692.00 
 Fertilizer   9,018.27 
 Nitrogen (N) kg 120 7,936.80 
 Phosphorus (P) kg 30 373.20 
 Potassium (K) kg 60 669.00 
 Sulphur (S) kg 15 16.80 
 Zinc (Zn) kg 2.11 17.72 
 Boron (B) kg 1.02 4.74 
 Insecticides kg 202.40 
 Irrigation m3 6,000 3,780.00 
Total input   24,561.97 
Output (Sweet potato roots) 
 BARI SP-8 kg 31,897 114,511.65 
 BARI SP-12 kg 30,344 108,935.18 
 BARI SP-14 kg 28,981 104,040.78 
 BARI SP-15 kg 28,080 100,807.20 
 Local kg 18,914 67,901.86 

However, the minimum energy output (67,901.86 MJ ha−1) was recorded from the local sweet potato cultivar due to the lowest root yield (18.91 t ha−1). The variation of output energy among the sweet potato varieties is mainly due to the variation of root yields. Flores et al. (2016) stated that the energy output from sweet potato was 53,885.90 MJ ha−1 in Tarlac, Philippines, which was half compared with our study. The reason for the lower energy output from sweet potato production in their study was mainly due to the lower root yield (15.01 t ha−1) compared with our study (28.08–31.90 t ha−1). Most of the total energy input was contributed by chemical fertilizers (36.72%), of which nitrogen fertilizers contributed a maximum of 32.31%, followed by diesel (27.25%) and irrigation by 15.39% (Figure 4). Similar results have been revealed for sweet potato (Flores et al. 2016), rice (Rahman et al. 2015), wheat (Singh et al. 2007; Devi et al. 2018), corn (Yousefi et al. 2014), Irish potato (Pishgar-Komleh et al. 2012), watermelon (Nabavi-Pelesaraei et al. 2016) and sugar beet (Asgharipour et al. 2012), where fertilizer, especially nitrogenous fertilizer, was the largest energy contributor to the total input energy of most crops, similar to our study. Total energy input and output amounts were variable depending on crop type and even varied from species to species.
Figure 4

Energy share (%) involvement in sweet potato production.

Figure 4

Energy share (%) involvement in sweet potato production.

Close modal

Energy involved in each activity for sweet potato production

The energy spent on pre-harvest and post-harvest activity for sweet potato production is presented in Table 4.

Table 4

Activity-based energy input of sweet potato production in the Teesta Riverbank area of Bangladesh

ActivitiesTotal energy equivalent (MJ ha−1)% Energy share
Pre-harvest activities 
 Tillage/Land preparation 3,529.00 14.37 
 Vine cutting and plantation in the main field 595.84 2.43 
 Fertilizer application 9,049.63 36.84 
 Irrigation 8,654.44 35.24 
 Insecticide application 249.44 1.02 
 Weeding and earthing up 235.20 0.96 
Post-harvest activities 
 Harvesting 470.4 1.92 
 Field gathering 47.04 0.19 
 Cleaning, grading and packaging 78.4 0.32 
 Transport to the market 1,652.58 6.73 
Total input   
ActivitiesTotal energy equivalent (MJ ha−1)% Energy share
Pre-harvest activities 
 Tillage/Land preparation 3,529.00 14.37 
 Vine cutting and plantation in the main field 595.84 2.43 
 Fertilizer application 9,049.63 36.84 
 Irrigation 8,654.44 35.24 
 Insecticide application 249.44 1.02 
 Weeding and earthing up 235.20 0.96 
Post-harvest activities 
 Harvesting 470.4 1.92 
 Field gathering 47.04 0.19 
 Cleaning, grading and packaging 78.4 0.32 
 Transport to the market 1,652.58 6.73 
Total input   

The pre-harvest operation consumed the major energy input (22,313.55 MJ ha−1), which is about 91% of the total energy input for sweet potato production (Figure 5). Conversely, about 2,248.42 MJ ha−1 energy input was from the post-harvest activity for sweet potato production, which contributed about 9% of the total energy input (Figure 5).
Figure 5

Energy inputs (MJ ha−1) and energy share (%) involved in the pre-harvest and post-harvest activities for sweet potato production.

Figure 5

Energy inputs (MJ ha−1) and energy share (%) involved in the pre-harvest and post-harvest activities for sweet potato production.

Close modal

Among the pre-harvest activities, the most energy was consumed by fertilizer application (9,049.63 MJ ha−1 or 36.84%) followed by irrigation (8,654.44 MJ ha−1 or 35.24%) and land preparation (3,529.00 MJ ha−1 or 14.37%) of the total input energy for sweet potato production (Table 4). In the case of post-harvest activity, about two-thirds of the energy input (1,652.58 MJ ha−1 or 6.73%) was consumed by the transportation of sweet potato from field to market for selling (Table 4). The remaining one-third of energy is consumed by harvesting (470.4 MJ ha−1 of 1.92%, field gathering (47.04 MJ ha−1 or 0.19%) and cleaning, grading, and packaging (78.4 MJ ha−1 or 0.32%). Flores et al. (2016) reported that the amount of input energy was 26,327.41 MJ ha−1 or 89.77% for pre-harvest and 2,999.45 MJ ha−1 or 10.23% for post-harvest operation for sweet potato production in the Philippines which is similar to our study.

Diverse energy forms of sweet potato production

The total energy inputs involved in sweet potato production can be categorized as direct, indirect, renewable and non-renewable energies (Figure 6). The amount of indirect energy (12,412.21 MJ ha−1) was slightly more compared with the direct energy (12,149.76 MJ ha−1) for sweet potato production due to the energy inputs supplied by the fertilizers. Considering the energy share ratio, both the direct and indirect energy contributed similar trends (Figure 6). The reason for this was that more diesel was used especially for irrigation as well as human labor in direct energy, which was equated by the fertilizer and machinery functioned as indirect energy. Most of the total input energy share in this study (22,884.21 MJ ha−1 or 93%) was from non-renewable energy contributed by the fertilizers, machinery and diesel used in the production of sweet potatoes and the remainder (1,677.76 MJ ha−1 or 7%) from renewable energy (Figure 4). Flores et al. (2016) reported that the amount of direct, indirect, renewable and non-renewable energy involved in sweet potato production was 46.07, 53.93, 11.77 and 88.23%, respectively, similar to our study. Several studies reported that the use of non-renewable energy is more than renewable energy in sweet potato (Flores et al. 2016), soybean (Mousavi-Avval et al. 2010), wheat (Shahin et al. 2008; Devi et al. 2018) and winter tomato (Ozkan et al. 2011) production. Moreover, the use of low input energy in sustainable crop production is more efficient than conventional systems and much more efficient in organic farming instead of chemical inputs (Mendoza 2005).
Figure 6

Total energy input and energy share (%) involved in different categories for sweet potato production (direct energy includes human labor, diesel and irrigation water; indirect energy includes tractor, other machinery, fertilizer and insecticides, renewable energy includes human labor and non-renewable energy includes machinery, diesel, fertilizer and insecticides).

Figure 6

Total energy input and energy share (%) involved in different categories for sweet potato production (direct energy includes human labor, diesel and irrigation water; indirect energy includes tractor, other machinery, fertilizer and insecticides, renewable energy includes human labor and non-renewable energy includes machinery, diesel, fertilizer and insecticides).

Close modal

Energy indices of sweet potato production

Energy indices have been presented in Table 5. Energy use efficiency is an indicator to assess the energy efficiency for crop production. Energy use efficiency is commonly used as an indicator to evaluate energy efficiency in crop production systems. The energy use efficiency or energy ratio of OFSP varieties ranged from 4.10 to 4.66 with an average of 4.36 which was 58% higher compared with the local sweet potato cultivar with a value of 2.76. This indicates that the energy used in sweet potato production has been replaced by 4.10–4.66 times the energy produced by the output energy from sweet potato roots. The higher the energy ratio, the more efficient use of energy in crop production will be achieved. Flores et al. (2016) stated the energy use efficiency of sweet potato was 1.84, lower than our study because of low output energy as well as consumption of high input energy. The higher energy use efficiency attains the efficient use of input energy to increase productivity, sustainability and competitiveness in agricultural production (Hatirli et al. 2005). The energy use efficiency varied from crop to crop and even from location to location. Several studies reported the energy use efficiency in potato was 0.95–1.71 (Mohammadi et al. 2008; Zangeneh et al. 2010; Pishgar-Komleh et al. 2012); 2.29 in soybean (Mousavi-Avval et al. 2010); 3.13 in wheat (Shahin et al. 2008); 0.8 in tomato (Ozkan et al. 2011) and 1.52 in watermelon (Nabavi-Pelesaraei et al. 2016). The energy productivity in the OFSP varieties was 1.14–1.30 kg MJ−1 with an average of 1.22 kg MJ−1 compared with the local sweet potato cultivar (0.77 kg MJ−1), which implies that 1.14–1.30 kg of sweet potato root is produced from per unit input energy. In this study, the specific energy was 0.77–1.30 MJ kg−1, indicating about 0.77–1.30 MJ input energy consumed for one kg of sweet potato root production. Flores et al. (2016) reported energy productivity of 0.51 kg MJ−1, comparatively lower and specific energy of 1.95 MJ kg−1, comparatively higher than our study for sweet potato production in the Philippines. The net energy of OFSP varieties ranged from 76,245.23 to 89,949.68 MJ ha−1 with an average of 82,511.77 MJ ha−1, about 90% more compared with the local sweet potato cultivar (43,339.89 MJ ha−1). Variation in net energy among sweet potato cultivars is mainly due to variation in output energy production from sweet potato roots while expending the same input energy. Energy profitability in OFSP ranged from 3.10 to 3.66 with an average of 3.36, almost double that of the local (1.76) sweet potato cultivar.

Table 5

Energy use indices involved in sweet potato production in the subtropical climate of Bangladesh

IndicatorsUnitQuantity
BARI SP-8BARI SP-12BARI SP-14BARI SP-15Local
Energy input MJ ha−1 24,561.97 24,561.97 24,561.97 24,561.97 24,561.97 
Energy output MJ ha−1 114,521.00 108,920.60 104,038.20 100,807.20 67,886.90 
Energy use efficiency – 4.66 4.44 4.24 4.10 2.76 
Energy productivity kg MJ−1 1.30 1.24 1.18 1.14 0.77 
Specific energy MJ kg−1 0.77 0.81 0.85 0.87 1.30 
Net energy MJ ha−1 89,949.68 84,373.21 79,478.81 76,245.23 43,339.89 
Energy profitability – 3.66 3.44 3.24 3.10 1.76 
IndicatorsUnitQuantity
BARI SP-8BARI SP-12BARI SP-14BARI SP-15Local
Energy input MJ ha−1 24,561.97 24,561.97 24,561.97 24,561.97 24,561.97 
Energy output MJ ha−1 114,521.00 108,920.60 104,038.20 100,807.20 67,886.90 
Energy use efficiency – 4.66 4.44 4.24 4.10 2.76 
Energy productivity kg MJ−1 1.30 1.24 1.18 1.14 0.77 
Specific energy MJ kg−1 0.77 0.81 0.85 0.87 1.30 
Net energy MJ ha−1 89,949.68 84,373.21 79,478.81 76,245.23 43,339.89 
Energy profitability – 3.66 3.44 3.24 3.10 1.76 

Water use indices of sweet potato production

The water use indices of sweet potato production have been presented in Table 6. The water use efficiency of OFSP ranged from 26.67 to 30.30 with an average of 28.33, about 58% higher compared with the local sweet potato cultivar (17.96), which indicates that an average increase of 1 MJ energy inputs leads to an extra growth in output energy by 28.33 MJ ha−1. The water productivity of OFSP ranged from 4.68 to 5.32 kg m−3 with an average of 4.97 kg m−3, revealing that the 4.68–5.32 kg root yield of sweet potato produced from per m3 of irrigation water. However, the lowest water productivity showed in the local sweet potato cultivar due to the lowest root yield with the same irrigation (6,000 m3) water. The water intensity of the OFSP variety ranged from 0.19 to 0.21 m3 kg−1 when it was 0.32 m3 kg−1 in the local sweet potato cultivar, specifying that 1 kg OFSP production required 0.19–0.21 m3 irrigation water when it was 0.32 m3 for the local cultivar of sweet potato. The water-energy productivity of OFSP ranged from 1.24 to 1.41 g m−3 MJ−1 with an average of 1.32 g m−3 MJ−1, 59% higher than that of the local cultivar (0.83 g m−3 MJ−1). This might be due to the higher output energy from sweet potato roots with a similar energy input of irrigation. The water-energy productivity was 0.02–0.07 g m−3 MJ−1 in soybean in different irrigation systems (Mousavi-Avval et al. 2010) and 0.03 g m−3 MJ−1 in potato (Mohammadi et al. 2010) which is much lower compared with our study. This may be due to the higher input energy consumed for the irrigation of the crops compared with their study. The amount of irrigation required in sweet potato can vary depending on the soil type.

Table 6

Water use indices for sweet potato production in the subtropical climate of Bangladesh

IndicatorsUnitQuantity
BARI SP-8BARI SP-12BARI SP-14BARI SP-15Local
Water energy use efficiency  30.30 28.81 27.52 26.67 17.96 
Water productivity kg m−3 5.32 5.06 4.83 4.68 3.15 
Water intensity m3 kg−1 0.19 0.20 0.21 0.21 0.32 
Water-energy productivity g m−3 MJ−1 1.41 1.34 1.28 1.24 0.83 
IndicatorsUnitQuantity
BARI SP-8BARI SP-12BARI SP-14BARI SP-15Local
Water energy use efficiency  30.30 28.81 27.52 26.67 17.96 
Water productivity kg m−3 5.32 5.06 4.83 4.68 3.15 
Water intensity m3 kg−1 0.19 0.20 0.21 0.21 0.32 
Water-energy productivity g m−3 MJ−1 1.41 1.34 1.28 1.24 0.83 

A case study of energy and water inputs for sweet potato production in the subtropical climatic condition of Bangladesh has been presented in this study. The data collection was done by applying structural questionnaires in a random method. Energy and water indicators were measured based on the use of energy and water inputs from various sweet potato growers. The following conclusions were drawn:

  • The OFSP produced total output energy ranging from 100,807.20 to 114,511.65 MJ ha−1 with an average of 107,073.70 MJ ha−1 using the same input energy (24,561.97 MJ ha−1), which was 39,171.75 MJ ha−1 more or 58% higher compared with the local sweet potato variety.

  • Among the input energy, chemical fertilizers contributed the most (36.72%) followed by diesel (27.25%).

  • The major share of energy input was consumed by pre-harvest activities (22,313.55 MJ ha−1 or 90.85%), whereas only 9.15% (2,248.42 MJ ha−1) was consumed by the post-harvest activity for sweet potato production.

  • The total energy inputs involved in the direct and indirect sources were similar to a value of 12,149.76 MJ ha−1 (49.47%) and 12,412.21 MJ ha−1 (50.53%). Conversely, it was much higher from the non-renewable sources (22,884.21 MJ ha−1 or 93.17%) than renewable sources (1,677.76 MJ ha−1 or 6.83%).

  • The OFSP varieties showed greater average energy use efficiency (4.36), energy productivity (1.22 kg MJ−1), specific energy (0.83 MJ kg−1) and net energy (82,511.73 MJ ha−1) and energy profitability (3.36) compared with the local sweet potato cultivar.

  • Similar trends were also observed in the OFSP varieties in terms of the average water use efficiency (28.33), water productivity (4.97 kg m−3), water intensity (0.20 m3 kg−1) and water-energy productivity (1.32 g m−3 MJ−1). Finally, we can say the OFSP varieties showed better performance in the case of all energy and water use indicators.

  • Re-examination of chemical inputs and use of non-renewable energy resources is needed to increase sweet potato productivity as well as sustainability. Besides, inclusions of leguminous crops may be considered in the crop rotation to reduce the use of more nitrogen fertilizers.

  • In order to control the high rate of non-renewable energy use, the use of organic fertilizers or green manures should be considered instead of chemical fertilizers.

  • The use of non-renewable energy (diesel) can be reduced for irrigation by using organic mulching materials.

The authors extend their appreciation to Taif University Researchers Supporting Project number (TURSP-2020/39), Taif University, Taif, Saudi Arabia.

No living organism (human or animal) was involved in conducting the present experiments.

Conceptualization: M.J.A. and A.A.M.; methodology: M.J.A. and A.A.M.; formal analysis: M.J.A. and A.H.; data curation: M.J.A. and A.H.; statistical expertise: M.J.A. and A.H.; writing – original draft preparation: M.J.A. and A.A.M.; writing – review and editing: A.G, M.E., S.S. and A.H.; visualization: M.J.A. and A.A.M.; supervision: A.A.M.; funding acquisition: A.G, M.E., S.S. and A.H. All authors have read and agreed to the published version of the manuscript.

The work was financially supported by On-Farm Research Division (OFRD), Bangladesh Agricultural Research Institute (BARI), Gaibandha 5700, Bangladesh. The research program was also partially supported by Taif University Researchers Supporting Project number (TURSP-2020/39), Taif University, Taif, Saudi Arabia.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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