Résumé

Les objectifs de cette étude consistent à évaluer la consommation d’énergie directe et indirecte lors la production du blé tendre. Pour cela, une enquête a été menée auprès de 81 exploitations agricoles réparties en 4 catégories. Les résultats indiquent que la consommation d’énergie par hectare varie de 9,7 à 11,1 GJ. Les fertilisants, les semences et carburant représentent respectivement 43,8%, 27,7% et 18,6% de la consommation totale. Quant à la consommation spécifique, elle varie de 3,05 à 3,37 MJ/kg. En tenant compte de ces résultats et aux attitudes des agriculteurs, des équations de prédiction de la consommation d’énergie ont été établies. Les résultats montrent que la réduction de la dose de semis et de la consommation en carburant mènent à une économie d’énergie variant de 8,6 à 20,6 % .Ce potentiel représente l’équivalent de 29,6 % de la consommation du carburant dans la production du blé tendre au Maroc. La consommation spécifique pourrait également être réduite de 19,6 à 22,9% .L’adoption de ces pratiques réduira l’émission des gaz à effet de serre de 119,1 Kte CO2 par an.



Mots-clés: Blé tendre, Énergie, Gaz à effet de serre

INTRODUCTION

Energy from fossils is an essential input of the modern agricultural production. Even if the sectors of energy and agriculture generate a relatively small part of gross value added, they are crucial in full-filling demands of growing population for energy and agricultural commodities. Global cultivated area and energy consumption almost doubled during the 20th century. Further increase of arable land and fossil energy consumption (even if limited) may cause detrimental effects to the environment. That is why improvement in energy efficiency of agricultural production is a way to rationalize the use of environment resources. Energy analysis, along with economic and environmental analyses, is an important tool to define the behavior of agricultural systems. Energy analysis started as a relevant subject in agricultural production in the 1970’s as a result of the dramatic increase of oil-derivative prices. The consequences were the rationalization of energy consumption, the use of new energy sources, and the aim for more efficient working methods. The establishment of methodologies to identify and evaluate the different energy flows that take part in agricultural production is the basis of an energy analysis. Reduction of energy input implies specific economic and environmental effects. If the trade-off between those effects is positive it means that energy, economic, and environmental performances are improved simultaneously Gołaszewski (2014). Agriculture plays an important role in the Moroccan economy. Its contribution to GDP ranges between 15% and 17%, and it employs over 40% of the active population. The sector also provides indirect support for 60% of the population and generates almost 25% of export revenue (Ait El Mekki, 2006). Cereals represent one of the main sectors of agricultural production in Morocco. Morocco’s per capita consumption of wheat, estimated at 258 kg annually, is among the highest in the world. Morocco’s economy is growing rapidly in all its sectors. Consequently, the energy demand has been increasing steadily. Morocco was consuming 18.8 Mt oe/y as primary energy in 2012. It’s energy needs grow by 8%/yr on average. All energy imports (crude oil and oil products, coal, natural gas and electricity) amounted to 102.5 billion Moroccan Dirham in 2013,10.7 billion USD (or 27% of all the country’s imports) IEA (2012).The country is heavily dependent on external sources, importing up to 93% of its energy supplies. Oil and petroleum products account for the largest part of Morocco’s energy bill. In 2009, Morocco adopted a national energy strategy in order to improve security of energy supply and availability/affordability, while also addressing environmental and safety concerns. The strategy seeks to reach these goals by diversifying energy sources, optimizing the electricity mix, increasing local production particularly from renewable sources, promoting energy efficiency. This paper focuses on energy saving possibilities in Moroccan agriculture especially in soft wheat production in favorable rain fed regions.

MATERIAL AND METHODS

Energy assessment at the national level showed that wheat production in favorable production regions consumed 42.4% of the total energy input in cereals production in Morocco Ramah (2013).These regions utilized favorable rain-fed production systems and became the focus of this work.

The study was performed in central region of Khemisset province which is situated in the North East of Rabat between 33°-34° North and 5°-6° West. The choice of this zone is justified by the availability of a precise data base on cereals producers. A Life Cycle Assessment -like approach has been chosen, but the activities have been restricted to pre-farm gate activities and have thus excluded processing into consumer goods.

The energy efficiency indicator is best expressed as the ratio of energy use per cultivation area (GJ.ha -1) and energy use per unit of product (GJ.t-1):Specific Energy = Energy input in MJ/ ha/ crops output in t.ha-1. A stratified random sampling method was used to determine survey volume. The stratification was based on farm size and employed four subgroups: 5-10 ha, 10-20 ha, 20-50 ha and >50 ha. With this technique, we have a higher statistical precision compared to simple random sampling. This is because the variability within the subgroups is lower compared to the variations when dealing with the entire population. The technique requires a small sample size which can save a lot of time, money and effort for us. Consequently calculated sample size in this study was 81. A preliminary investigation was conducted in order to define the variability of strata and sample size based on the following equation:

ni=(Ni σyi)*n/(Ni σyi)

with the terms defined in Table 1.

The information related to the inputs and the yield related to the year of 2012 was extracted in the form of questionnaires.

The first part of our investigation consisted of interviews with individual farmers. The second part, fuel consumption data, characteristics of machinery used was collected from the contractors interviewed and from the manufacturer’s specifications for tractors and implements. The total inputs for production of a unit area consisted of: plant protection products (herbicides, fungicides), fertilizers, diesel fuel, machinery, seeds and human power. The amount of energy consumption was calculated from the multiplication of the Input consumption and its energy equivalent per unit (extracted from scientific resources).The according to energy input and output,specific energy was calculated: Energy input(MJ.Ha-1)/yield of wheat (kg.Ha-1). It should be mentioned that the free sources of energy (solar energy input for photosynthesis) were not accounted for.

All information on energy inputs and wheat yields was transferred into Excel spreadsheets and analyzed by the “Statistical Package for the Social Sciences” SPSS 21 program analysis of variance; the energy consumption per hectare and the specific energy were calculated. The significance level chosen before data collection is set to 0.05 (5%).

Prediction equations were used in order to predict the energy saving in soft wheat production: E0 = X0+ a X1+ b X2+ c X3 + d X4 where a,b,c,d were respectively the energy conversion coefficient of nitrogen,phosphore,seed and diesel, X0 is the sum of energy used in pesticides,machinery and labor. X1 was the nitrogen quantity used, X2 the phosphorus quantity, X3 seed rate and X4 diesel consumption per hectare. Used data is based on the median that gives a more robust measure, of each group of farm type. The energy saving expressed in %, Es was calculated to be:(Ep-E0)*100/E0 where Ep is energy prediction calculated by varying seed rate and fuel quantity in conventional system and added the changing of energy used in pesticides, machinery in no till technique.

In order to predict specific energy reduction, our calculation was based on a survey result of 325 samples of soil analysis. The last part of our study consisted on GHG analysis which leads us to have an idea about the energy saving impact on the environment. The GHG emissions were calculated per hectare by multiplying the application rate of inputs by its corresponding emission coefficient (Table 2).

Table 2: GHG conversion coefficients in MJ (Biograce 2011)

Coefficient

KG N 5.88

Kg P2O5 1.011

Kg K2O 0.576

Pesticides /active ingredient 10.971

Seed/Kg 0.276

Machines/MJ 0.069

Diesel/MJ 0.088 MJ

RESULTS AND DISCUSSION

Energy inputs

About 171.5 to 186.6 kg of seed, 8 to 13 h human labor, 9.7 to 14.4 h machinery power and 45.2 to 58.4 L diesel fuel for total operations were used in wheat production on a hectare basis. The use of nitrogen fertilizer, phosphorus and potassium were 59 to 69.3 kg, 57.6 to 72.7 kg and 1.4 to 3.8 kg respectively. Pesticides 0.71 to 0.76 kg a.c. The total energy consumption varied from 9.7 to 11.1 GJ ha-1, and there was no significant difference between the four farm categories presented in Table 3. The results are lower than results found in other countries such as Portugal (12.9), Deutchland (18.6), Greece (19.9), Poland (15.1), Netherlands (18.1), Finland (12) (AgrEE, 2012), Iran (14.9) (Azarpor 2011), Turkey (14.5) (Marakuglu, 2010) and Italy (15.4) (Alluvione, 2011).

Analyze per source

The difference between the energy sources was significant for all operations. The difference was significant between farm types in fuel,labor and machinery source.

Results show that fertilizers are the highest inputs and represent 41.6 to 45.2% of total inputs. Nitrogen, in particular, was the most important and comprised 75.6 to 80.1% of energy from fertilizers. The contribution of K and especially P was much lower (on average 19.9 to 23.6% and 0.4 to 1.5% of fertilizers, respectively). Seeds were second and covered 26.4 to 28.6% of total inputs. Fuel was the third input and represented 18.2 to 21.4% of total inputs. Weed and diseases control had a far lower importance and represented only 2.3 to 2.9% of total energy.

Figure 1: Average percentage of total energy input

Energy Input in Farm Operations

Seventy five percent of the total input energy as shown in Figure 2 consumed during the operation of fertilizing and seedbed preparation. Tillage operation consumed 52%,49.4%,47.6% and 44.9% of the total fuel used respectively for small farms, medium farms 10-20, 20-50 ha and large scale farms over 50 ha.

Figure 2: Average energy percentage per operation

For all farm sizes, energy included in the fertilization represented the highest input (43.3 to 45.4% of the total input)followed by seedbed preparation (29.4 to 32%). Comparing the size of land holdings, the energy requirements for tillage decreased towards higher size of farm. It revealed that farmers who have large land holdings use more energy for soil tillage, sowing and harvesting. Results showed that the total energy input per unit area in small fields was 9.5% smaller than that of large fields. Fuel consumption per hectare increased with increasing farm size. The energy consumed by machinery varied from 2.4 GJ ha-1 in small scale farms to 3.3 GJ ha-1 in large scale farms, 70 to 88.1% is consumed during tillage and harvesting operation (Figure 3). Statistical analysis showed that difference is significant between farm sizes only in the operation of pesticide application.

Specific energy consumption in GJ/t

Specific energy shows the amount of energy spent to produce a unit of marketable product. It was slightly higher 3.37 GJ/t in medium scale farms as compared to small farms (3.07), large scale farms (3.05) (Table 4).

Table 4: Specific energy results

Farm size 5-10 ha 10-20 ha 20-50 ha >50 ha

Total inputs MJ/ha 10116 9748 9937 11078

Outputs in Kg/ha 3300 2890 3145 3630

Energy intensity MJ/t 3.07 3.37 3.16 3.05

Energy saving prediction

Quantification of energy savings

Results showed that fertilizers,fuel and seeds are the most energy consuming (89.4 to 91% of total energy inputs per hectare). The seed rate used by farmers varies from 170 to 190 kg/ha. The fuel consumed varies from 46.4 to 58.1 L/Ha. The quantity of seed could be saved using 1000 kernel weight for calculating seed rate. Taking in consideration that the majority of interviewed farmers use exclusively more than 170 kg of seed rate per hectare. Conclusively for our study energy saving could be obtained mainly through reducing seed rate and fuel consumption reduction. The energy consumed per category of farm, equations cited below were based on results of our investigation.

Equation 5-10 ha: 898.2+ a 65.8+ b 69+ c 180 + d 46,4

Equation 10-20 ha: 981.7+ a 60.5+ b 69+ c 170+ d 46.8

Equation 20-50 ha: 1010.8+ a 60.5+ b 69+ c 180+ d 47.4

Equation >50 ha: 1118.3+ a 60.5+ b 69 +c 190+ d 58.1

The variation of seed rate and fuel consumption factors implies the change in the energy input assuming all other factors fixed there is a higher potential for decreasing energy input. Results calculations showed that if all farmers operated efficiently by reducing seed rate (S)by 20 to 40 kg.ha-1 would result in a reduction of total energy consumption from 3.2 to 5.9% . These estimations are not based only on technical data but also on farmer’s practices and agronomic possibilities. The results revealed that using direct seeding (DS) technique could lead to an energy saving varying from to 8.6 to 14.7% (Table 6). Among the variables included in the equations, seeds and fuel were found as the most important variables which influence energy economy in soft wheat production.

The total energy that could be saved is converted to fuel quantity in order to have an idea about the fuel quantity saved. The table below shows the maximum energy that can be saved using zero tillage technique and reducing seed rate to 150 Kg/ha.

The final result indicates that the total energy that could be saved represents 29,6 % of energy used in fuel consumption in the production of soft wheat production in Morocco.

Specific energy consumption reduction

According to soil analysis of 325 samples in the area were the survey was conducted, the recommended formula is: 87 kg N,32 Kg P and 40 Kg K, farmers then used more phosphorus than needed, and less nitrogen and potassium. Nitrogen use is too low and varied from 60.5 to 65.8 kg, phosphorus 69 kg. So even the input energy will be higher, the specific energy per ton will be less, cause of improving the yield by assuming that 3 kg of nitrogen lead to a gain of 100 kg production. The specific consumption could be reduced by 8.6 to 26.3% for large scale farm by reducing seed rate and using direct seeding operation (Table 6).

Green house emissions analysis

The results of CO2 emissions of soft wheat production are given in Table 7.

GHG emissions were calculated from the resource use inventory and multiplied by their appropriate emission factor.

Total energy involved,computed as C equivalent, was 726.8 kg CEq/ha in small farms and 795.3 kg CEq/ha in large farms. The Emission per grain produced varied from 219 to 230 Kg CO2e/t. Results indicated that the highest share of CO2 emissions was attributed to fertilizers 58 to 64% followed by diesel fuel with 22 to 26%seeds 6.5 to 7.4% (Figure 4). Ali Mohammadi reported a total emission of 1171.1 kg CO2eq ha-1 in irrigated areas Mohammad (2014).While Alireza Khoshroo reported 280.6 kg CO2eq ha-1 for wheat production in rainfed areas Khoshroo (2014). Khakbazan et al. calculated the CO2 emissions from wheat production and found that it can be ranged from 410 kgCO2eq ha-1 to 1130 kg CO2eq. Rajaniemi et al. 2300 kg CO2eq.ha-1 for conventional technique and 2250 for direct seeding in Finland (Rajaniemi et al.).The emissions per ton of grain produced was calculated to vary from 134 to 149 Kg CO2e/t, these values are less than emitted in wheat production in New Zealand (340 Kg CO2e/t; Safa, 2012) and in Finland (590 Kg CO2e/t; Rajaniemi, 2011). Analysis of GHG emission showed that total emission that can be saved is estimated to be 119 097 Tons C Eq annually in soft wheat production in rainfed areas.

CONCLUSION

Energy input in soft wheat production was similar for the four farm types studied, it varied from 9.7 to 11.1 GJ/Ha. The indirect energy embodied in fertilizers and seeds followed by direct energy in fuels are the major energy input among all the energy inputs for growing soft wheat in Morocco. Their share varied from 89.4 to 91%.Specific energy was 3.05 to 3.37 GJ/T. The prediction equations showed that there is a potential for energy savings in wheat production and trade-off effects between energy savings and GHG-emissions. The potential is evaluated to 13.2% to 20.6%.

Assuming 1.055 million hectares of soft wheat land, under no-till, and all farms using 150 kg of seeds per hectare, there will be an energy saving of 1.73 millions Gigajoules, converted in fuel that means that 42.5 million liters can be saved annually which correspond to 29.6 % of annually used fuel in wheat production in Morocco. This savings is valued about 320 million MAD. Specific consumption could be reduced from 8.6 to 26.3%.The total GHG emission estimates ranged from 664.5 to 795.3 kg eCO2 /Ha for winter soft wheat. The calculations showed that the two major contributors to the final result were the GHG emissions associated with fertilizer production and fuel. These two emissions accounted for 80 to 90% of the total emissions.

Results of investigating land size lead to note that large farms have higher productivity and use more energy than small farms and presented a large gap of energy saving. Reaching these results could be done by establishing some strategies such as providing better extension and training programs for farmers in order to increase energy efficiency of wheat crop production in the region. Farmers should be trained with regard to the optimal use of inputs, especially fertilizer’s and employing new production technologies: no till techniques.

Local agricultural extension centers in the region have an important role in these cases to establish the more energy efficient by implementing farm field schools which is a form of adult education that evolves from the concept that farmers learn optimally from field observation and experimentation in regular sessions from planting to harvest. The results must be disseminated to farmers by extension agents thought the national office of agricultural extension in order to promote no tillage system, accurate fertilizer management, crop rotation with legumes in order to save N fertilizer, pesticide management, preventive weed control and use of selected seed rate according to kernel per thousand, fuel management by training the operator who play the most influential part. The operator decides how to adjust the implement, the speed and the efficient operation of the tractor or self propelled working machine.

This study showed how efficient energy is being used, identified energy and saving opportunities and highlighted potential improvements in productivity and quality in Moroccan’s soft wheat production .According to our study’s results, there is a high potential for energy savings in agricultural sector, so a future research must be focused mainly on irrigated agricultural crops such as citrus, tomatoes growing greenhouse and super intensive olive growing.

REFERENCES

AgrEE Agriculture and energy efficiency (2012) .State of the art on energy efficiency in agriculture. Country data on energy consumption in different agro-production sectors in the European countries.

Agriculture and horticulture development board. understanding foot printing carbon for wheat and oilseeds hgca 57 guide www.hgca.com.

Alluvione F, Moretti B, Sacco D, Grignani C (2011). EUE of cropping systems for a sustainable agriculture. Energy 36 pp 4468-4481.

Alonso Antonio M, Gloria J.G ( 2010).Comparison of efficiency and use of energy in organic and conventional farming in Spanish agricultural systems. Journal of sustainable Agriculture 34:312-338.

American Society of Agricultural Engineers. D497.4 FEB03 Agricultural Machinery Management Data.

Beicip-Franlab (2009). Options for a low carbon energy future in Morocco. Final Report.

Biograce harmonized calculation of biofuel greenhouse gaz emissions in Europe 2013 User manual for the BioGrace Excel tool Version 4c.

Charles R, Jolliet 0, Gaillard G, Pellet D (2006).Environmental analysis of intensity level in wheat crop production using life cycle assessment. Agricuture, Ecosystems and environment 113:216-225

CIHEAM analytic note N°7 – March 2006 Cereals policies in Morocco Akka Aït El Mekki ENA Meknès ( Morocco).

Dalgaard T, Halberg N, Porter J.R (2001). A model for fossil energy use in Danish agriculture used to compare organic and conventional farming. Agriculture,Ecosystems and Environment 87;51-65.

Data worldbank (2013) Employment in agriculture (% of total employment).

Decker J.A.E, Epplin FM, Morely D.L, Peeper T.F (2009). Economics of five wheat production systems with no till and conventional tillage. Agronomy Journal Volume 101,Issue 2.

Elizabeth Brown, R Neal Elliot (2005). Potential energy savings in the agriculture sector,ACEEE (American Council for an Energy Efficient Economy) Report number IE053.

Houshyar E., M.J. Sheikh Davoodi, H.Bahrami, S.Kiani and M. Houshyar (2010). Energy use forecasting for wheat production utilizing artificial neural networks (ANN).World Applied Sciences Journal 10:958-962.

IFIAS Workshop report (1978). Energy Analysis and Economics. Resources and energy 1:151-204.

Jacqueline, Ho (2011).Calculation of the carbon footprint of Ontario wheat. Study by undergraduate Researchers at Guelph Vol,4,n° 2,Winter,49-55.

Janusz Gołaszewski, Marcel van der Voort, Andreas Meyer-Aurich, Luis L. Silva, Hannu J. Mikkola (2014). Case studies and comparative analysis of energy efficiency in wheat production in different climatic conditions of Europe. International conference of Agricultural Engineering AgEng 2014 Zurich 6-10 July.

Jokiniemi T, Mikkola H, Rossner H, Talgre L, Lauringson E, Hovi M, Ahokas J (2012). Energy savings in plant production. Agronomy Research Biosystem Engineering Special Issue 1, 85-96.

Khoshroo A (2014). Energy Use Pattern and Greenhouse Gas Emission of Wheat Production: A Case Study in Iran. Agricultural communications, 2: 9-14.

Kempen Markus, Tim Kraenzlein (2008). Energy in agriculture use: A modeling approach to evaluate energy reduction policies.107th EAAE Seminar “Modeling of agricultural and rural development policies” Sevilla, Spain, .

Khoshroo A (2014). Energy use pattern and greenhouse gas emission of wheat production. A case study in Iran. Agricultural communications 9-14.

Kranzlein T (2005).Quantifying the energy use in agriculture. C APRI Meeting. Swiss Federal Research Station for Agricultural Economics and Engineering CH-8356 Ettenhausen.

Lars E (2009). Greenhouse gas emissions from cultivation of winter wheat and winter rapeseed for biofuels and from production of biogas from manure. Directive 2009/28/EC of the European Parliament on the promotion of the use of energy from renewable sources

Lal. R. (2004) Carbon emission from farm operations. Environment International 30:981– 990.

Ministry of Agriculture and Forestry New Zealand Ltd (2011). Carbon Footprint of New Zealand Arable Production – Wheat, Maize Silage, Maize Grain and Ryegrass Seed .Technical Paper No: 2011/97 Prepared for Foundation for Arable Research ISBN 978-0-478-38754-4.

Meyer-Aurich A (2012) Economic and Environmental Analysis of Energy Efficiency Measures in Agriculture Case Studies and trade offs. Project Report funded by the Senenth Framework Program of the EC.

Moghimi Mohamed Rezza, Mohsen Pooya and Ahmad Mohammadi (2014).Study on energy balance,energy forms and greenhouse gas emission for wheat production in Gorve city,Kordestan province of Iran. European Journal of Experimental Biology 3:234-239

Mohammad A, Jafari A, Keyhani A (2014). Energy use efficiency and greenhouse gas. Renewable and Sustainable Energy Reviews 30: 724–733.

Moreno M.M,C Lacasta, R. Meco. C.Moreno (2011). Rainfed crop energy balance of different farming systems and crop rotation in a semi arid environment: results of a long term trial. Soil Tillage Research 114:18-27.

Mousavi Avval S. H., Sh. Rafiee and A. Keyhani (2012). Energy Efficiency Analysis in Agricultural Productions: Parametric and Non-Parametric Approaches, Energy Efficiency - A Bridge to Low Carbon Economy, Dr. Zoran Morvaj (Ed.), ISBN: 978-953-51-0340-0,

Osamu Kitani, Thomas Jungbluth, Robert M. Peart,Abdellah Ramdani (1999).CIGR Handbook of Agricultural Engineering Volume V Energy and Biomass Engineering. Published by the American Society of Agricultural Engineers.

Pimentel D (2009). Reducing Energy Inputs in the Agricultural Production System. Monthly review an independent socialist magazine 61, Issue 03 (July-August).

Pimentel D, Williamson S, Courtney E.A, Gonzalez-Pegan O, Caitlin Kontak. Steven E. Mulkey (2008). Reducing energy inputs in the US food system. Hum Ecol. 36:459-471.

Rajaniemi. M, H.Mikkola and J.Ahokas (2011). Greenhouse gas emissions from oats,barely,wheat and rye production. Agronomiy Research Biosystem Engineering Special Issue 1,189-195.

Ramah M, Baali EH (2013). Energy Balance of Wheat and Barley under Moroccan Conditions. Journal of energy technologies policy. 3:No 10.

Risoud B.,O. Theobald (2002). Référentiel pour l’analyse énergétique de l’exploitation agricole et son pouvoir de réchauffement global. ENESAD-ADEME.

Safa M, Mohtasebi S.S, Behroozi Lar M, Ghasemi-Varnamkhasti, M (2010).Energy consumption in production of grains prevalentin Saveh, Iran. African Journal of Agricultural Research 5:2637-2646.

Safa M, Sandhya S (2012).CO2 emmissions from farm inputs”case study of wheat production in Canterbury,New Zeland. Environmental pollution 171:126-132.