Comparison of energy intensity of different food materials and their energy content

The energy embodied in different food materials refers to energy input in its production in agricultural and or livestock farms in direct or indirect forms. In this work, it is intended to make a comparison among the energy intensity of cereals, cow milk and bull meat production. The study was performed to evaluate the energy flow in dairy farms and related feedstuff production farms in the northwest of Iran. According to the results, the energy intensity of wheat and maize corn is 4.35 and 9.19 MJ kg, respectively, while they have the energy content of nearly 15 MJ kg as food materials with almost 15% moisture content. The energy intensity of ECM milk was calculated to be 5.81 MJ kg, while it has the energy content of only 3.15 MJ kg, with a water content of 87.2%. As for boneless meat, for a bull mass of up to 400 kg, the energy intensity was 75.4 MJ kg while it was 103.8 MJ kg for bulls up to 700 kg body mass. It is much higher than for milk and cereals, while, it has only 8.8 MJ kg energy content for the fresh state with nearly 70% water content. A comparison of these energy values indicates the high use of resources, harmful to the environment, for products of animal origin, especially for meat. This issue will get worse with an increasing demand for animal products in the future. Therefore, replacing bull meat with less energy-intensive food materials such as cereals and other meat, e.g. poultry, could reduce pressure on the environment.


Introduction
More than 3.7 billion people in the world were faced with malnourishment (Pimentel, 2009). In 2010, it was determined that of these 3.7 billion, 925 million people, mostly in developing countries, were undernourished, increasing worldwide since 1995 (FAO and WFP, 2010). Poverty and undernourishment of a large part of the population are caused by fundamental problems in the distribution of food and resources, otherwise, agriculture produces enough food to overcome future demands (FAO, IFAD and WFP, 2002).
The increase in demand for livestock products is growing more rapidly than the population growth rate (Schneider, 2010), because of increasing living standards and shifting demographic parameters (Steinfeld et al., 2006). Global production of milk and meat in 2050 is projected to be more than double the production of 1999 (Steinfeld et al., 2006), an increase that is being called the Livestock Revolution (Devendra, 2002). By efforts to increase food productions, more intensive use of energy in agricultural systems is unavoidable. Producing enough food by agriculture, especially in the form of livestock products has seriously challenged agriculture by environmental and resources restrictions problems.
Energy efficiency improvement is one of the most important aspects in regard to combatting these challenges. Energy efficiency improvement contributes to the reductions of emissions and climate change (Varone and Aebischer, 2001) and is a solution for fuel resource restrictions. One of the aspects of energy efficiency improvements in the use or consumption of products as well as food materials with lower energy intensity. Energy intensity is the primary energy embodied in materials production mostly revealed in MJ per kg of agricultural products. On the other hand, the energy output from food materials for the human body is quite different for agricultural and livestock products. Besides efforts to reduce the energy intensity of food production, consumption of food materials with lower eISSN: 2550-2166 © 2021 The Authors. Published by Rynnye Lyan Resources FULL PAPER energy intensity and higher energy content would strongly suggest helping to overcome malnourishment, environmental issues and energy restrictions. Therefore, the energy output to input ratio could be well defined as an important index in food materials comparison by energy perspective.
Energy input in farms mainly refers to energy from tractor fuel and irrigation facilities and energy consumed in the production of fertilisers, pesticides and seeds. In the same way, energy input in livestock production refers to indirect energy input from feedstuffs and materials and direct energy of fuels and electricity consumed inside livestock farms. Energy intensity depends on production practices varying significantly from farm to farm and region to region. According to Stanton and LeValley (2010) and Feedipedia (2012), the energy content of cereals is nearly 15 MJ kg -1 (with a moisture content of 15%). For milk, it is 3.15 MJ kg -1 ECM (ECM = energy corrected milk with 4% fat and 3.4% protein which has 12.8% dry matter; Ulbrich et al., 2004) and 8.8 MJ kg -1 for boneless fresh meat (Klinge, 1989) with approximately 75% moisture. The energy efficiency of livestock production is lower than that of crop production (Pimentel, 2009). Because conversion ratios of primary energy to the product in animals are significantly less than that for photosynthesis in crops.
A plentiful study about the energy intensity of agricultural products (feedstuffs, cereals etc.) has been carried out. Their results vary widely. The differences in results come from different cultivation methodology, environment and also study methods.
The energy intensity calculated by Refsgaard et al. (1998) for cereals in Denmark was approximately 2.6 MJ kg -1 DM with a yield of 3,000-4,000 kg ha -1 . In studies in Iran, it was found that the energy intensity of wheat is from 5.4 MJ kg -1 (Ghobadifar, 2009) to 17.8 MJ kg -1 (Ziaei et al., 2015. The average energy intensity for several studies in wheat cultivation in Iran was found to be 8.3 MJ kg -1 FM by an average yield of 4.5 t ha -1 (Mohammadi et al., 2015) much higher than reported by Refsgaard et al. (1998). For maize corn, the energy intensity was calculated from 4.6 MJ kg -1 FM (Feizbakhshi and Soltani, 2013) to 17.5 MJ kg -1 (Sami et al., 2014) for Iran. The average energy intensity of 9.9 MJ kg -1 FM maize corn with an average yield of 6.4 t ha -1 was calculated by Mohammadi et al. (2015). It seems higher than 5.1 MJ kg -1 maize corn reported by Frorip et al. (2012) for Estonia. The energy intensity calculated for rapeseed was 9.1-10.7 MJ kg -1 DM for a study in Iran by Mousavi-Avval et al. (2011) with a yield of 1.9 t ha -1 FM and much higher than for Germany (5.2 MJ kg -1 DM) estimated by Kraatz (2009).
The energy intensity of milk production for dairy farms in European countries was reported by some studies. The high share of energy input from feedstuffs makes the energy intensity of feedstuffs the main determinative factor in the energy intensity of milk. Refsgaard et al. (1998) found that 70% of the energy input in milk production is from feedstuffs, 20% from direct energies and 10% from facilities (e.g. building and machinery) resulted in energy intensity of 3.3 MJ kg -1 ECM in Denmark. Kraatz (2009) found it to be 3.5 MJ kg -1 ECM and Abel (1997) calculated it as 4.4 MJ kg -1 , both for Germany. Williams et al. (2006) determined an energy intensity of 2.5 MJ kg -1 fresh milk in the UK.
The energy intensity of beef meat production in Germany for conventional keeping systems was 56.35 MJ kg -1 and 25.50 MJ kg -1 for organic systems according to the data from GEMIS 3.1 (Taylor, 2000). In the UK, the energy intensity of cattle meat production was estimated to be 28 MJ kg -1 of the carcass mass (Williams et al., 2006). Frorip et al. (2012), calculated the energy intensity for meat as 69 MJ kg -1 for Estonia.
In comparison to crop production, few studies have been conducted on the energy efficiency of livestock farming (Wechselberger, 2000) and there is a scarcity of data for energy intensity of meat and milk production. This study was defined to evaluate the primary energy intensity of cereals, cow milk and bull meat production in northwest Iran.

Materials and methods
This work is intended to make a comparison among the energy intensity of cereals, cow milk and bull meat production. The study was performed for evaluation of the energy flow in dairy farms and related feedstuff production farms in northwest Iran.

Framework of the study
The main framework of this study is based on the IFIAS methodology (IFIAS, 1974) for energy analysis and more detailed new guidelines for cumulative energy demand (CED) and life cycle assessment (LCA) concepts introduced respectively by the Association of German Engineers (VDI 4600, 2012) and International Standard Organisation (ISO 14040 and 14044) (2006). The investigation focused on the calculation of the energy intensity and energy output-input ratio indicators for the production of some cereals, milk and meat.
As the whole study project, the dairy farm system consisted of two individual units: the feedstuff production unit and the dairy cattle farm unit, which were investigated separately. The outputs of the first unit eISSN: 2550-2166 © 2021 The Authors. Published by Rynnye Lyan Resources FULL PAPER are the inputs for the second unit, both were studied according to LCA methodology (ISO 14040, 2006). Whereas most other studies were focused either on plant production or animal production, in this study, the boundaries of the dairy farming system started with the feedstuff production in feedstuff farms and ended with the production of milk, meat and manure as market products.

Data acquisition
Alfalfa, maize silage, maize corn, barley and oilseeds meal are the most used feedstuffs for Iranian cattle farming. Dairy farms in Iran largely have no grazing facilities. Iranian dairy farms buy the most feedstuffs from other, plant producing agricultural farms located in the same region or neighbour regions. A few feedstuffs are imported from abroad. Moghan agroindustrial company in Moghan plain (in north-western Iran) was chosen for investigating the energy efficiency of feedstuff production. The farms area under cultivation in this company was more than 45,000 ha. Energy intensity for some feedstuffs (e.g., cottonseed and soya bean) not investigated were derived from the scientific literature.
Nearly 85% of dairy cattle in Iran are kept in herds with less than 51 heads. The 24 dairy farms were selected representative of prevailing dairy farming methods in north-western Iran. Cattle and bull in the region are crossbreeds of Holstein and a local breed, with different degrees of breed purity. Data were gathered for 2008, 2009 and 2010.

Energy equivalents
A wide range of assumptions for energy equivalents has been made in energy studies. The energy equivalents used in this study for direct energies (e.g. for Diesel 47.8 MJ l -1 ) were taken from Ortiz-Canavate and , except for electricity which was corrected to 8.4 MJ kWh -1 . Human work was not viewed as an energy input. Machine equivalents were calculated using the method of Bowers (1992). The building was taken into account for dairy farms by the use of 1.1 GJ m -2 energy equivalent (Baird et al. 1997) according to their dimensions. The energy equivalent of fertilisers was taken from Helsel (1992) which was for N fertiliser 78.2 MJ kg -1 and pesticides were from Rathke and Diepenbrook (2006). The water consumption equivalent in channels and network irrigation systems was assumed to be 0.63 MJ m -3 water (Ozkan et al., 2004). The transportation equivalent was assumed to be 1.6 MJ t -1 km -1 of truck transportation . Seed equivalents were used from Heichel (1980) and Ortiz-Canavate and .
For the energy outputs, the Higher Heating Value (HHV) of the products is considered as the energy equivalent for cereals, milk and meat. The reason to use the HHV was that the energy value of food materials in human health sciences is measured and reported by food HHV. As discussed earlier, it was assumed to be 15 (avg.), 3.15 and 8.8 MJ kg -1 for cereals with 15% moisture content, ECM (milk) and boneless fresh bull meat, respectively. Approximately 40-47% of the bull mass was intended to be boneless meat (Afolayan et al., 2002) and other parts of the cattle bull body were neglected. For intermediate materials, (e.g. foodstuff input to dairy farms) the energy equivalent was primary energy intensity.

Allocation of energy input between product and byproducts
There are several patterns to allocate the energy input between product and by-products in multi-product systems. Kraatz (2009) used economical values of products for allocation and Grönroos et al. (2006) used their mass yield percent. In this study according to HHV yield of produced meat and milk and substitution of manure with chemical fertilisers, the total energy input allocation ratios were accepted to be 83%, 15% and 2%, respectively for milk (ECM), manure and meat (cow cattle meat, other than bull meat studied here).

Feedstuff energy input
The feedstuff consumption data were checked by calculating the cattle demand for feed energy intake on the basis of animal nutrition knowledge (Kirchgeßner et al., 2008). The standard cattle energy intake requirements, the data on cattle live mass (LM) growing rates, and milk yield from the investigated farms were obtained from these calculations.
The cattle growing period was divided into different categories. The live mass, average daily mass gain and average metabolisable energy (ME) requirement in each category were summarised according to Kirchgeßner et al. (2008) and are shown in Table 1 The number of days that cattle from each category stayed on the farms was calculated using the mass gain values given in Table 1 and the farm data on the live mass of each category of cattle at the beginning/end of each year and also those sold or bought from each farm. A prediction model was established to allocate the growing period of the existing cattle to the categories listed in Table 1. Then, the standard ME requirements were calculated for each cattle category. These calculated standard ME requirements were compared with the farm data of the ME consumption of each farm for each year. Based on the calculated ME requirements for each cattle category and the derived feedstuff rations, the embodied energy in the consumed feedstuff were allocated to the cattle categories for each farm and year of investigation.

Energy intensity of feedstuffs
The feedstuff crops consumed by cattle farms investigated in this study are listed in Table 2 and other feedstuffs not investigated in this study are listed in Table 3. The energy intensity and allocated energy for their by-products are summarised in these tables.
For feedstuffs for which there was not enough information about production energy e.g., fish meal, fat powder, poultry meat and bone meal, their HHVs were used to calculate their energy intensity (EI). They had values of 37.9, 20.9, 16.7 and 22.7 MJ kg -1 DM, respectively. The HHV-based output-input ratio (OIR) indicator was therefore assumed to be equal to 1 for these materials.

Energy intensity of milk
The ECM yield of the investigated dairy farms was 6,585 kg cow -1 yr -1 , on average. The energy input for ECM produced in these 24 farms ranged widely between 5.60 and 10.11, with an average of 7.07 MJ kg -1 . According to the mentioned allocation ratios, the mean energy intensity of ECM milk was calculated to be 5.81 MJ kg -1 .
According to this fact that mostly there are no grazing facilities in dairy farms in Iran, the energy intensity of milk is higher than reported by European studies e.g. the report of Kraatz (2009) for Germany with an amount of 3.54 MJ kg -1 with a half-day grazing plan. The energy input for live cattle and meat production

Energy intensity of meat
The dairy farms kept the bulls and heifers until they reached an average of 415±161 kg body mass when they were sold. The bulls were sold a few weeks after birth only in two of the dairy farms, and in some dairy farms, they were kept until reaching approximately 700 kg.
The energy input to live beef cattle was their demand from direct energies and facilities. Because there was no determined consumption amount for each category in the farms, energy input from feedstuff was allocated from the total feedstuff consumption of a farm considering metabolisable energy requirement ratios of each category of cattle. According to the calculations, the energy intensity of a head of a live bull and the energy intensity per kg of boneless meat in each category is summarised  Table 2. Energy intensity (EI) of the investigated feedstuffs and allocated energy intensity to their by-products when used as feedstuff a EI allocated based on the metabolisable energy (ME) ratio of grain and straw and consumed energies in their production; b Weighted average of the results for summer and spring maize silage in this study according to cultivation area and yield; c Allocated EI based on the ME ratio of grain and bran.   Table 4. The boneless meat is considered to be 40-47% of live mass adopted from Khalafalla et al. (2011), Afolayan et al. (2002 and Pfuhl et al. (2007).
According to Table 4, about boneless meat, for a bull mass of up to 400 kg, the energy intensity was 75.4 MJ kg -1 while it was 103.7 MJ kg -1 for bulls up to 700 kg body mass. The energy input from feedstuff was the main source of the energy input with a mean value of 80%. In a bull of 400 kg, the share of the energy input was 78% from feedstuff, 17% from direct energy, 4% from buildings, and 1% from machinery.

Energy indices for the products
The comparison of the energy intensity (EI) related to the dry matter (DM) shows quite clearly that cereals production needs much less energy than the production of milk and meat. For wheat, barley and maize corn the calculated EI was 4.35, 6.76 and 9.19 MJ kg -1 DM, respectively. While they provide more than 18 MJ kg -1 energy in the human body as their HHV. The EI for fresh milk and meat with 87.5% and 70% moisture content, was calculated to be 5.81 and more than 75.4 MJ kg -1 , respectively. The corresponding DM related EI was 46.5 MJ kg -1 DM for milk and 251 MJ kg -1 DM for meat. While, for human nutrition fresh milk and meat delivered energy of just 3.15 and 8.8 MJ kg -1 , respectively.
To make it easy to compare the consumed energy and the energy earned from food, the energy output-input ratio (OIR) index could be used. The OIR for cereals investigated here is 1.96 MJ MJ -1 for maize corn to 4.14 MJ MJ -1 for wheat. Where the OIR for milk (ECM) is 0.54 MJ MJ -1 and for meat is 0.08 to 0.12 MJ MJ -1 (respectively from bull up to 700 kg and bull up to 400 kg body mass). It means, from each MJ primary energy input for wheat, 4.14 MJ energy for the human body is produced while, for milk, it is only 0.54 MJ and for meat, it is less than 0.12 MJ.
It is obvious that human nutrition with milk and meat is much more energy expensive than to live by cereals. The high EI of meat indicates the high use of resources and related harmful effects of meat production on the environment (e.g. land use, emissions). The increasing demand for animal products in the future dramatically will affect the environment and may cause food shortage by allocating the farms to produce feedstuff instead of farm products as wheat and other crops. However, this study was done for cattle kept in an intensive manner as described above. For ruminants grazing on permanent grassland, lower energy consumption and less harmful effects on the environment can be expected. Therefore, replacing bull meat with sustainable food materials such as cereals could reduce pressure on the environment and guarantee enough food supply.

Conclusion
Primary energy consumed in different food material production in agriculture and animal husbandry is quite different. The primary energy embodied in cereals (energy intensity in MJ kg -1 ) is less than in milk and meat. It is because in the animal body a huge amount of energy intake from feedstuffs is lost during the conversion into milk or meat. Furthermore, with their higher HHV cereals provide more energy for human nutrition than milk and meat. The higher energy outputinput ratio for cereals compared to animal products indicates the high use of resources and harmful environmental effects of milk and meat production. The increasing demand for animal products in the future dramatically will affect the environment and may cause a food shortage. Providing human body energy demand from cereals instead of milk and even more meat contributes to the conservation of resources and to ensure enough food supply for the increasing world population.