**3.1 Efficiency estimates**

An input-oriented DEA approach was used to determine technical, pure technical and scale efficiencies of wheat farmers in both production systems. Technical efficiency of all farmers was evaluated using CCR model, and BCC model was used to determine pure technical (PTE) and scale efficiency (SE). The results from CCR and BCC model for rain-fed wheat producers in Pakistan are presented in **Figure 2**. It can be seen from the figure that only about 18% rainfed farmers are technically efficient. This shows that there is a considerable inefficiency between

**Figure 2.** *Percentage distribution of TE, PTE, and SE scores of wheat producers in rainfed production system.*

**Figure 3.**

*Percentage distribution of TE, PTE, and SE scores of wheat producers in irrigated production system.*

wheat producers in the study area. From efficient farmers 17% are efficient in both technical and pure technical efficiency score; this means that these farmers are globally efficient and operating at most productive scale size, on the other hand the 22% farmers are only locally efficient farmers and they have disadvantageous scale size. Additionally, 14% and 36% of the farmers have pure technical and technical efficiency score less than 0.5.

Efficiency scores of irrigated wheat producers are demonstrated in **Figure 3**. About 34% irrigated farmers are technically efficient and 42% are pure technically efficient. Among efficient farmers 90% are globally efficient and 10% are locally efficient due to scale problem. Considering CCR model 7% farmers have efficiency scores between 0.9 to less than 1 and 19% have between 0.8 to less than 0.9. On the other hand, in BCC model 13% had scores between 0 to less than 1 and 16% had between 0.8 to less than 0.9. Less than one score of the pure technical efficiency means that producer is using more energy from different sources than required [35].

**Table 4** presents the summarized statistics for technical efficiency, pure technical efficiency and scale efficiency for wheat producer of Pakistan. The results revealed that average technical efficiency of wheat producer in rain-fed production system was 0.62 and in irrigated it was 0.82. The pure technical efficiency and scale efficiency was 0.78 and 0.67, respectively in rain-fed, and 0.87 and 0.85 in irrigated wheat production system. The technical efficiency of irrigated wheat farmers varied

**Table 4.**

*Average efficiency of rain-fed and irrigated wheat production in Pakistan.*

*Energy Use Efficiency in Irrigated and Rainfed Wheat in Pakistan DOI: http://dx.doi.org/10.5772/intechopen.95284*

#### **Table 5.**

*Amount of input and output for 10 efficient and inefficient wheat producers.*

between 0.12 to 1 which shows that all farmers did not have knowledge of right production techniques or they were not applying at the right time. The low average values of scale efficiency in both production systems imply that the average size of the wheat farms is not equal to optimal farm size. This mean if the inefficient wheat farmers operate at optimal scale size considerable saving of energy from different sources is possible without affecting the yield level.

#### **3.2 Input use pattern of efficient and inefficient wheat producers**

The amount of physical inputs and output for 10 efficient and inefficient farmers based on CCR model in both rain-fed and irrigated wheat production system are presented in **Table 5**. The efficient farmers use all inputs in less amount compared to inefficient farmers in irrigated production system. While in rain-fed production system except diesel and nitrogen use of all other inputs was low for efficient farmers than inefficient. Inefficient farmers in rain-fed production system use more human labor hours by 27.78%, seed by 1.92%, FYM by 48.5%, and phosphate by 7.14%. In irrigated production system, use of inputs by efficient farmers is lower than inefficient farmers by, 28.40% for human labor hour, 11.61% for diesel fuel, 34% for chemicals, 42.85% for nitrogen, 34.6% for phosphate, 59.97% for potash and 60% for water for irrigation. Looking at output it is evident that yield of efficient farmers is higher than inefficient farmers in both production systems.

### **4. Conclusions**

Energy security and environmental problems due to its use are the major concern for most of the developing world. Agriculture is among the largest energy consuming sectors; this chapter was an effort to estimate energy use in wheat production which is an important staple food in Pakistan. Data on quantity of different energy inputs used in wheat production was collected through field surveys. Energy consumption in wheat was calculated by multiplying amount of inputs with their energy equivalents drawn from literature. Energy indices which are important to interpret how energy is being used were also estimated. A non-parametric data envelopment analysis technique was used to identify efficient and inefficient farmers.

In Pakistan two different wheat production systems prevail (rain-fed and irrigated). So, all estimations were performed separately for both production systems. The results of the study showed that, FYM, fertilizer, and diesel fuel has the highest share in total input energy consumption in rain-fed wheat, while in irrigated wheat fertilizer, water for irrigation, and diesel were the main energy consuming inputs. In both production systems consumption of indirect and non-renewable energy resources was higher than direct and renewable energy resources. The results of the DEA analysis revealed that, 85% of the farmers in rain-fed wheat production and 65% in irrigated wheat production were technical efficient in Pakistan. Based on BCC model the estimate of target energy use showed that there is a great scope for energy savings from various input sources. If the optimum energy requirement levels are adopted by farmers, then it would lead to increase in energy efficiency. Comparison of 10 most efficient and no-efficient farmers revealed that input usage of inefficient farmers is comparatively higher than efficient ones with no difference in yield output and size. Based on result it could be said that there is dire need for dissemination of information about best agricultural practices and economic benefits of use of inputs at recommended levels. Adoption of better agriculture technologies is highly recommended as it will result in improvement in efficiency of use of diesel and human labor. Most of the wheat is cultivated manually and majority of the farmers apply flood irrigation leading to higher use of water and diesel fuel also. Efficient management of water for irrigation would improve energy efficiency and minimize environmental impacts.


*2.2. Preparation of Blend*

A 50/50 blend ratio of milled Norway spruce and pea starch was prepared by weighing 45 g of each respective material in order to achieve a uniform weight ratio for blending. Both materials were placed in a plastic container and thoroughly mixed together for 10 min using a 220-V Janke and Kunkel Ika-Werk mixer rotated at a speed of 60 rpm. The blend was prepared by mixing with water to achieve a moisture content (10%) equal to that of the pure samples described in the previous section. The procedure for achieving the desired moisture content for the blend was such that an appropriate amount of water was added to 90 g of the mixture and then mechanically rotated again for another 10 min. Shortly after rotation, the mixture was sealed in small plastic bags and stored for 48 h to allow the moisture to settle in and to prevent further absorption of moisture from the surroundings. Care was taken during the preparation of mixtures with water so as to avoid the formation of rigid irreversible gel by pea starch, which may alter the analysis results. The 50/50 percentage blend was a random selection aimed at keeping the ratio of the admixture of Norway spruce and pea starch equal for a fair comparison of the mechanism of bonding between the pure and blended pellet samples made from the two materials. The pellet production process of the pure and blended samples of Norway spruce and pea starch is described in the section below.