Livestock Research for Rural Development 14 (6) 2002

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Comparative productivity, profitability and energy use in Organic, LEISA and Conventional rice production in the Philippines

T C Mendoza 

Department of Agronomy, College of Agriculture,
UP Los Baños, Laguna, Philippines
tcm@mudspring.uplb.edu.ph 

Paper presented during the 14th IFOAM Organic World Congress
held at Victoria, Canada on August 21-24, 2002


Abstract
 

The Organic method of rice production was more productive than LEISA (low external input sustainable agriculture) and conventional methods. Only 52 USD were spent and 277 Mcal of energy used in producing 1 tonne of paddy rice through the organic method while 63 USD were spent and 501 Mcal of energy were used in LEISA.  Three times more energy (837 Mcal) and 79 USD were spent in producing 1 tonne of rice in the conventional method.  Growing rice the organic method was 4 times more energy efficient than the conventional. method. 

The agrochemical input (fertilizer/pesticides) accounted for 61% of the fossil fuel based energy inputs and 84% of the cash cost of production in the conventional system.  Organic rice farmers earn 7 dollars per 1 dollar cash expense while only 2 dollars in conventional and 5 dollars in LEISA.  

The findings in this case study have shown that the organic method of production is a cost effective (and energy efficient) means of solving the recurring credit problems of capital-scarce rice farmers in the Philippines.  This is especially relevant considering the unpredictable rain and typhoon occurrence (18 to 20 storms per year) in practically all rice producing areas except Mindanao.  The Government extension program should equally promote the organic method of rice production.  

Keywords: Energy intensity, energy efficiency, productivity, organic agriculture, LEISA


Introduction 

Productivity and profitability continue to be the two most important indicators in assessing the success or failure of crop production.  But high levels of productivity (though not necessarily profitable) have been and continue to be achieved through the heavy use of energy-based cultural inputs (Jones 1989; Hall et al 1992; Pimentel et al 1994) together with fertilizer-responsive high-yielding crop varieties (Jensen 1978), farm mechanization which facilitates timeliness of field operations, and irrigation which relieves the crop from any yield-depressing effect of water deficit during the sensitive growth stage. 

All over the world, there has been a growing realization of the increasing inefficiencies of agricultural production (Pimentel et al 1983; 1980; Soriano 1982;  Gowdy et al 1987; Mendoza 1991; Giampietro 1994; Singh et al 1997).  From the time of Pimentel’s 1983 study, which pioneered energy analysis in agriculture, the direction, attention and interest has been to reduce energy use in production.   

Fossil fuel oil reserves continue to decline and extraction and exploration have become more difficult and expensive.  This has propelled fossil fuel price increases, which in turn has led to higher food prices.  This pattern of thinking, however, is not shared by all.  Bony (1993), for instance, concluded that since 1977, direct energy use for wheat production in France has been decreasing.  Considerable savings of energy are realized since more powerful tractors (combining 2 or 3 field operations simultaneously) are being used.  The results of Bony's (1993) study seem to contradict those obtained by Pimentel et al (1983).  While energy intensity increased by 28.3% between 1944 (4.6 GJ t-1) and 1975 (5.9 GJ t-1), the energy use did not increase since then.  Energy use in the manufacture of nitrogen, which accounts for a high proportion of the total energy use, has decreased (Mudahar and Hignett 1985).  This decrease in the energy coefficient for nitrogenous fertilizer, as suggested by some authors, had in turn decreased the energy intensity of maize production between 1975 and 1983 in USA (Uhlin 1998; Cleveland 1995; Balwindy and Fluck 1993; Panesar and Fluck 1993). 

There are two general ways of pursuing an energy-conserving or energy-reducing agricultural production systems.  The first involves improvement in the conventional practices by introducing or adopting more efficient and energy-saving technologies and practices (Reinjntjes et al 1992).  The second requires fundamental changes, a major shift or transformation in whole systems, values, and beliefs, of not only the farmers but also the society at large.  This has been elucidated by various authors (Steiner 1924; Henning et al 1991; Rigby and Caceres 2001; Ohlander et al 1999, Pretty 1996 ). 

In the Philippines, it appears that some rice farmers are practicing these two unique ways.  Rice is the staple food of about 80% of the population.  Due to the increasing prices of agrochemical inputs relative to stagnant rice prices, farmers are forced to cut costs.  As agrochemicals (fertilizer and pesticides) comprise the major cash cost of production, the practice is to reduce the use of these inputs.  The Philippine government through the Department of Agriculture has also been launching Integrated Pest Management (IPM) whose implementation has reduced considerably the use of pesticides by rice farmers.  In the current terminology, their approach to rice production can be called "Low External Input Sustainable Agriculture" (LEISA) (Reinjntjes et al 1992).  But there have been a number of rice farmers who have adopted more fundamental changes in their system of rice farming.  They no longer apply chemical fertilizer and pesticides.  Instead, they practice rice straw recycling, use green manure crops (Azolla, Sesbania); and raise livestock (ducks, swine, cattle or carabao) to produce on-farm the manure which they apply in their farm as fresh manure or prepared into compost.  Their system of rice farming can be aptly called organic farming (USDA 1980;  Henning et al 1991;  Lampkin and Measures 1999). 

In the Philippines, the historical energy use in rice production had not been done but energy related studies had been done separately (Nguyen van Nguu 1976; Mendoza 1991; Soriano 1982).  Energy use in conventional rice farming is obviously higher compared with that in the traditional rice production.  As soils have become acidic, fertilizer use efficiency has declined. This had resulted in an increased use of chemical fertilizer inputs (6 bags of fertilizer per ha in the 1970’s to 8-10 bags of fertilizers in the 1990’s).  Farmers now use hand tractors instead of carabaos for land preparation. As soil organic matter declined, tillage has become more difficult, which increased the man-hours to fully prepare the field for planting. The profitability of rice farming has considerably declined. 

Three farming systems (Organic, LEISA, and Conventional farming) were studied.  In addition to productivity and profitability analysis, an energy analysis (efficiency and intensity) was included.  Specifically,  this  case study  was conducted  to:

  • compare the 3 farm systems as to their productivity, profitability and energy use (efficiency and intensity)

  • be able to draw insights and lessons from the 3 systems that could guide research and extension in promoting a more ecology-sustainable rice production system in the country.


Methodology 

Selection and Characterization of Case Study Sites 

In a rice farming community, the research sites were selected based on the following criteria: presence of farmer practitioners of Organic Agriculture (OA), Low External Input Sustainable Agriculture (LEISA) and Conventional Agriculture (CF).  As to the case farms, the following criteria were used:

  • prospective farmer-partners with a farm holding of at least one half hectare and that had been practicing the specific farming approach for the past 3 years, 

  • the farms were located within the same village, and

  • the farmers were willing to share the details of their farming practice. 

Based on the above criteria, two research sites were selected. The first case study was done at Infanta, Quezon (Mendoza et al. 2001) while the second was done at Baco, Oriental Mindoro (Mendoza 2002) 

The first case study site was in the village of Tudturan, in the town of Infanta, Quezon.  Infanta is one of 13 municipalities of the first district of Quezon province.  Most of Infanta has rugged to mountainous terrain (59%) while the low-lying areas have level to gentle slopes (41%).  The case study was done in the low-lying area, as these are the flat and irrigated areas .  As such, they are highly suitable to rice production.  The soil in the study area originated from alluvial deposits washed lower from the adjoining uplands.  The textural classification is silt loam.  The site has no distinct dry season (less 200 mm months-1) but has a very pronounced maximum rainy period from November to January in any given year. 

The case study was conducted in a two (2) year period from 1998 to 2000.  There were four cropping seasons (2 wet and 2 dry) .  Field visits depended on the activities on the farm, i.e. land preparation, planting, weeding/replanting, harvesting/threshing, and gathering materials for composting.  To collect data, the following instruments and methods were used: questionnaires, historical accounts, focus observation, individual interview, use of secondary data, record keeping.  

Agronomic data such as yield per ha were monitored every after harvest.  The area of the farm was noted and the yields were reported on a per ha basis.  Important plant data such as filled grain per panicle, unfilled grain per panicle and weight of 1,000 grains (g) were also obtained in the 3 farms. 

The second case study was done in the village of Mayabig, town of Baco, Oriental Mindoro.  Oriental Mindoro is one of the 2 provinces of the island of Mindoro (the other being Mindoro Occidental). Baco, Oriental Mindoro is dominated by a rugged to mountainous terrain.  The low-lying flat and irrigated areas devoted to rice production derive benefits from the uplands from the alluvial deposits and silt being carried down during heavy rainfall and flooding months.  The town of Baco has almost a similar rainfall pattern to Infanta, Quezon.  It has also a very pronounced rainy period from November to January.  It does not have distinct dry months except during El Niño or a drought year, which occurred in 1983 and 1997-98.  The village where the case study was conducted (Brgy Mayabig) has 249 households with a total population of 1,278 (based on year 2000 Census of Population).  The households have on average 5 to 13 members.  The village has an area of 433 ha.  Of this area, 196 ha are irrigated rice land and 237 ha are uplands devoted to mixed crops (coconut, bananas, fruits and upland crops). 

Data collection was done through an interview of the key informants and individual farmers using a prepared and pre-tested questionnaire.  This was supplemented by focus group discussions that involved not only the participation of farmers (men and women) but also their children (Mendoza 2001).

A total of 23 farmers were interviewed.  Of the 23 farmers, 10 were conventional farmers, 7 were LEISA, and 6 were organic farmers.  From the questionnaire, details of farm activities were asked, their duration (man-days or hours involved), quantity of inputs used (kg of pesticides if they were using them).  Farm household data were also requested. This included: number of years into farming, farm size, other crops planted, membership to organizations, reasons for the farming method being used and important observations and lessons learned in farming. 

The farmers,  representative of the organic and LEISA systems, were identified earlier, while the conventional farmers (still the majority of farmers) were selected randomly from the names provided by the municipal agricultural officer (MAO). 

Data clustering and analysis 

The analysis of data was focused on 3 domains namely: productivity, financial soundness and energy analysis of the 3 farm systems (organic, LEISA and conventional). The productivity analysis was based on the usual yield and other important yield components.  Whenever possible, the reasons for high yields, which  differed across sites and farm systems, were provided.  The agronomic practices, climate or soil features of the farms were compared. In the financial and energy analysis, suitable methods for the case study were adopted. 

Financial Analysis   

All cost items were accorded monetary values (in peso-Philippine currency and in US Dollars;  1 USD = P50).  The cost items were delineated into cash and non-cash costs (cash + non-cash = total costs).  It was necessary to separate the two cost items because the non-cash costs were paid-in-kind at harvest time. They did not involve any cash outlay on the part of the farmer, but they were a substantial costs item when they were deducted from the gross or total yield.  Details of cash and non-cash items are listed in Appendix Table 1.   

The different indicators computed in the financial analysis were as follows: Net revenue (NR), net revenue/cash expense ratio (NCER), Break-even Yield (BEY) and cost to produce 1 tonne of grain.  The corresponding mechanical formulae used in computing the different financial indicators were as follows: 

Net Revenue (NR)  = Gross Revenue (GR)-Total Costs (TC)             (1) 

Where:     (GR) = Grain yield * Price of un-milled rice (farm gate price)
               
(TC) = Cash costs + Non-cash costs 

Net Revenue/Cash Expense Ratio (NCER) = NR ÷ Cash expense           (2) 

It is important to note that NCER was used instead of ROI (return on investment), where the denominator is the total cost, because the cash outlay was more important for the farmers in rural Philippines.  The non-cash cost is not treated as costs by the farmers since it does not involve money on their part. 

         Break-even Yield (BEY) =     Total Costs   ÷     Unit Price                                                         (3)

                                                =     P ha-1   ÷   (P) Price of rice kg-1

                                                =     kg ha-1

         Cost to produce 1 tonne of rice   =     Total Costs ÷  Grain Yield ha -1                             (4)

                                                            =     P ha-1  ÷  tonnes ha-1

                                                            =     P tonne-1

Energy Analysis 

The use of energy was delineated into fossil fuel based energy inputs (FFEI) and indirect fossil fuel based inputs (IFFEI).  The FFEI includes: fuel and oil used by the tractor, chemical fertilizers (N, P, K) and pesticides.  The energy values (Mcal) were derived from published literature (Pimentel et al 1983; Cox and Atkins 1979).  Labor and seeds comprised the indirect fossil fuel energy inputs. For labor, the energy values (Mcal) by operation were taken from Kuether and Duff (1980), as cited by Soriano (1982).

Rice grain energy values were as follows: Seeds at 12% of moisture, 4.0 Mcal kg -1 ; un-milled rice wet season harvest, 20-24% moisture at 3.0 Mcal kg-1 and un-milled rice dry season harvest, 18-20% moisture at 3.2 Mcal kg-1. 

Two measures of energy use were employed: energy efficiency (Ee) and energy Intensity (Ei). 

The Energy efficiency (Ee) is the ratio between the Mcal energy output per ha (grain yield) and the Mcal energy inputs per ha.  It gives an indication of how much energy was produced per unit energy used.  Since the energy inputs were delineated into 2 categories (FFEI and IFFEI), Ee was computed twice as follows:

         Energy Efficiency (Ee)     =     Mcal (grain)    ÷    Mcal (FFEI)                                         (5)

         Energy Efficiency (Ee)     =     Mcal (grain)    ÷    Mcal (TEI)                                            (6) 

This was done to find out the Ee with the direct fossil fuel-based energy inputs as in the manufacture of fertilizer or pesticides.  Labor and seeds as in the financial analysis are not really treated as costs by farmers in the Philippines but there is considerable energy in the use of seeds (1 kg = 4.0 Mcal).  Also, energy in labor was also huge (Appendix Table 2).  This explains why they were also included in the audit of total energy inputs (TEI). 

The Energy intensity (Ei) shows how much energy (Mcal) was used to produce 1 tonne of grain.  As in Ee, it was estimated in two ways as follows:

         Ei  =  Mcal (FFEI) ÷ Grain yield (tonne ha-1) = Mcal t-1 of grain                (7)

         Ei  =  Mcal (TEI) ÷ Grain yield (tonne ha-1) = Mcal t-1 of grain                   (8) 

While related to Ee, Ei provides quantitative data on how much energy (FFEI or TEI) was spent in the production of rice (Mcal tonne-1 of grain).


Results and Discussion 

Productivity 

The comparative yields of Organic, LEISA and Conventional farmers are shown in Table 1.   

Table 1.  Comparative yields (t ha-1) among the Organic, LEISA and Conventional Farming systems

Site

Organic

LEISA

Conventional

Average

Infanta, Quezon1/

4.37

3.88

2.98

3.74

Baco, Oriental Mindoro2/

3.25

3.28

3.52

3.35

Ave. for 2 sites

3.81

3.58

3.25

1/Average for 4 cropping seasons (2 wet season and 2 dry season crops, 1998-2000 for Organic and LEISA and   2 cropping seasons (Wet and Dry season 1999-2000) for conventional.
2/Based on reported average yield across season obtained by the farmers we interviewed (Dec 2001)
*Reported yields are paddy or unmilled rice.

The representative case farms for organic rice production in Infanta, Quezon obtained the highest yield followed by LEISA and the lowest was the conventional system.  Rice yields obtained at Baco, Oriental Mindoro were about the same for the 3 types of farming systems. 

The average yields for the two sites revealed that yields obtained in the organic farms were slightly higher (17.2%) when compared to the conventional farms.  Farmers who were into cost cutting measures (through LEISA) also obtained slightly higher yields when compared to farmers using the conventional method. 

Only in Infanta, Quezon were seasonal yields monitored.  Yield data gathering was done in two (2) wet seasons (WS) and two dry seasons (DS).  During the wet season, rice yield was highest in he Organic farms, followed by LEISA farms, and it was lowest in the conventional farm  (Table 2). 

Table 2.  Rice yield (kg ha-1) obtained in the three (3) farms for wet season (WS) and dry season (DS), Infanta, Quezon only

Farm

Wet Season

Dry Season

Average*

Conventional

2,445

3,507

2,976

LEISA

3,748

4,024

3,886

Organic

3,918

4,822

4,370

*Average of four (4) cropping seasons for LEISA and Organic, while 2 cropping season for Conventional.

While rice yields were higher during the dry season (DS), the yield trend was the same for the 3 case farms.  Highest yield was obtained in the organic farm, followed by the LEISA farm and the lowest was in the conventional farm.  Higher yields were obtained in all farms during the dry season. This could be attributed to the higher photosynthetic productivity occurring during the sunshine-rich dry season cropping.  It was the conventional farm which had the lowest yield during the wet season as cloudy-rainy weather is not conducive to input utilization.  Also, the case study period coincided with frequent heavy rains.  It was observed that more than 50% of rice plants simply lodged in the conventional farms.  Heavy N-fertilized crops had heavy top growth.  This rendered the rice plants in the conventional farm susceptible to lodging. That the Organic farm yielded higher during both wet and dry seasons, compared with the conventional farm, is suggestive of the following important considerations in the life of small-holder rice farmers in the Philippines:

  • It should dispel doubts that rice yield would decline if no chemical fertilizer or pesticides are applied.

  • It eliminates the risks of losing money due to weather-induced risks.

While organic residue recycling is more labor intensive than applying fertilizers, it is more rewarding as yields were higher.  

Rice yield in the organic farm was 19.9% higher than in the LEISA farm and was 37.4% higher than in the conventional farm during the dry season.  Not only was the yield in tonnes per ha higher in the Organic farm, but the grains in the panicle were also heavier. The weight of 1000 grains in the Organic farm was also higher than in the Conventional farm (Table 3).  Filled grains per panicle were highest in the Organic farm while it was lowest in LEISA, the Conventional farm being intermediate.  Percent unfilled grains were highest in LEISA while it was comparable in Organic and Conventional farms. 

Table 3.  Comparative grain features (filled-unfilled grains, weight of 1000 grains) in Organic, LEISA and Conventional farms

Farm

Filled grain
per panicle

Unfilled grain per panicle

% Unfilled
Grain

Weight of
1000 grains (g)

Organic Farm

91.5

24.1

20.0

27.4

LEISA Farm

44.9

25.8

36.0

23.4

Conventional Farm

70.8

19.5

22.0

25.7

Grain weight is a determinant of grain milling recovery.  Upon milling, higher grain recovery was obtained in the Organic farm.

Why were organic farmers getting higher yields than LEISA or the Conventional farmers? It was not simply the weather factor or the input application that affected yields.  Farm management and crop care also affected yields. It is important to point out that most of the conventional farmers were tenants, while the organic farmers owned the farm.  In Infanta, Quezon, the representative farmers for both LEISA and conventional farm were tenants.  Of the 10 farmers interviewed representing  conventional farming only 3 owned their farms.  The rest of the farmers were also tenants.  Since the farmers do not own the farm, they were just following the instruction given to them by their landowners (Mendoza 2001).  As landowners, the organic farmers were more motivated to increase yield.  They were adopting better farm management practices.  Close attention and care were being accorded to the crops (Damo 2002). 

In both sites (Infanta, Quezon and Baco, Oriental Mindoro), the representative organic farmers were raising livestock (ducks in Infanta, Quezon and ducks and swine in Baco, Oriental Mindoro).  Thus, they produced on-farm the manure or compost requirements of their rice crop.  When asked why they were raising livestock, the farmers answered that it was their way of increasing their income from farming.  The income from rice farming alone was not sufficient to support their families.  From the seminars/training they attended, livestock (due to their manure) was a critical component of organic farming (source of manure, farm power, immediate cash as in poultry and ducks). 

The organic rice farmers were not simply mono-crop rice farmers.  They were involved in rice cum livestock production due to the following reasons: ducks  because they help the farmers in picking golden snails (golden snail is one of the serious pests in lowland rice production in the Philippines);  swine, because they can use their rice bran in the feed mixture. 

The variations in yield obtained in organic farms when compared with those in the conventional farms were consistent with the intensive reviews done by Stanhill (1990).  Of the 30 yield comparisons he made, the mean yield of 13 cases of organically grown crops exceeded those of the conventional cropping systems, were equal in 2, and were less in 15.  In our case study, of the seven (7) organic rice farms studied, all except one (1) were getting higher yields compared with the average yields obtained in the conventional farms.  Stanhill's (1990) data were based on maize; ours was rice.  Stanhill (1990) noticed that conventionally farmed fields gave higher maize yields than organic fields during favorable cropping conditions, whereas the opposite was the case during adverse, low yielding conditions.  In our case study, rice yields were higher in both conditions.  Rice yields in organic farms were 38% higher during sunny and zero typhoon dry season cropping  (favorable condition)  and about 60% higher during rainy, cloudy and typhoon-laden wet season cropping  (less favorable condition)  at Infanta, Quezon.  

Financial Analysis 

In Infanta, Quezon, the lowest gross revenue was obtained during the wet season in the Conventional farms (USD 357/ha) while the highest gross revenue was obtained in the Organic farms during the dry season (USD 771).  The lower yield  in the conventional farms explains why the revenue was the lowest.  Low yield was attributed mainly to the rainy weather as explained earlier.  For easier comparisons of the financial soundness of the 3 farms, the indicators used in the financial analysis were summarized as follows:  Net Revenue (Table 4), Total Cost (Table 5), Break-even yield (Table 7), Net revenue/cash expense ratio (Table 8) and cost to produce 1 tonne of un-milled rice (Table 9). 

Highest net revenue per ha was obtained in organic farms in both sites (Table 4).  The average for the two sites was 70% higher than in the conventional farms. Between sites, net revenue was more than doubled in the organic farm at Infanta, Quezon.  This could be attributed to the higher gross revenue due mainly to higher yields obtained in the organic farm.   

Table 4.  Comparative Net Revenue (in USD per ha) of organic, LEISA, and conventional farms in 2 sites

Site

Organic

LEISA

Conventional

Infanta, Quezon

  498.64 

382.20

198.02

(251.20)

(193.00)

(100.00)*

Baco, Oriental, Mindoro

332.00

 304.00

290.00

(114.50)

(104.80)

(100.00)

Ave. for 2 sites

  415.32

 343.10

244.01

(170.20)

(140.57

(100.00)

*Figures in parenthesis are relative values where the conventional farm was used as the reference or index value

Moreover, the total costs of production were highest in the conventional farm (Table 5)  This was due to the higher cash costs of production which in turn were due to the fertilizer and pesticides amounting to about 84% of the cash cost of production. 

Table 5.  Total cash (cash + non-cash) expenditures (in USD) in producing rice per ha basis in the 3 different farms and in 2 sites, Philippines

Site

Item

Organic

LEISA

Conventional

Infanta, Quezon

Total

187.96

226.72

238.28

Cash

84.22

69.33

121.22

Non-Cash

103.75

157.38

117.06

Baco, Oriental Mindoro

Total

187.98

220.48

271.28

Cash

38.98

  74.40

117.88

Non-Cash

149.12

146.08

155.20

Average

Total

187.97

223.60

254.78

Cash

  61.54

  71.86

119.55

Non-Cash

126.43

151.74

135.23

In Baco, Oriental Mindoro, despite the slightly lower yields obtained in the organic farms (3.25 tonnes ha-1) compared with the conventional farm (3.35 tonnes ha-1), net revenue was higher by 14.5%.  This is because the total cost of production was much lower in the organic farm than in the conventional farm.  The main reason why the total cost was 44% higher in the conventional farm was because of the chemical inputs applied which were 83% of the cash costs or 36.0% of the total cost of production.  The agrochemical inputs (fertilizer and pesticides) in the conventional farm as a percent of both the cash and total cost were computed (Table 6).  Chemical fertilizer accounted for about half (52.2%) of the cash input costs. 

Table 6.  Agrochemical inputs (fertilizer and pesticides) in Conventional farms as per cent (%) cash input cost and total cost  in two sites, Philippines

Item

Infanta, Quezon

Baco, Oriental, Mindoro

Average

Production Cost*

Cash Cost

6,061

5,894

5,977

Non-Cash Cost

5,853

7,760

6,806

Total (P)

11,914

13,654

12,784

(USD)             

238

    273

   255

Input (Cash Input)

6,061

 5,894

5,977

Oil

   989

    989

   989

Agrochem

5,072

 4,905

4,988

     

Fertilizer

2,400

 3,822

3,111

     

Pesticides

2,672

 1,083

1,877

Fertilizer

        % of Input Cost

39.6

64.8

52.2

        % of Total Cost

20.1

28.0

24.1

Pesticides

       % of Input Cost

44.1

18.4

31.2

% of Total Cost

22.4

  8.0

15.2

   AgroChem

      % of Input Cost

83.7

83.2

83.4

      % of Total Cost 

42.6

36.0

39.3

*Philippine peso currency, exchange rate  1USD = P50; unless specified the figures are in peso.

In terms of net revenue, LEISA was at the middle of the two.  The relative net revenue was high (93%) in Infanta, Quezon while it was minimal (4.8%) in Baco, Oriental Mindoro.  This was due to the considerably higher yield (hence gross revenue) obtained in the LEISA farm and the cost of production was still slightly lower (5%) in the LEISA farm.  In both sites, the minimal chemical input application brought down considerably the cash cost of production by 37% (average for 2 sites). Since the total cost of production was mainly due to the higher cash cost of production, breakeven yield (the yield level that pays for all the costs) was highest in the conventional farm followed by organic and LEISA farms, respectively (Table 7).  

Table 7.  Breakeven Yield (kg ha-1) in organic, LEISA and conventional farms in 2 sites, Infanta, Quezon and Baco, Oriental Mindoro, Philippines

Site

Organic

LEISA

Conventional

Infanta, Quezon

1253

1445

1489

(84)

(97)

(100)*

Baco Oriental, Mindoro

1175

1378

1706

(69)

(81)

(100)

Average for 2 sites

1214

1412

1597

(76)

(88.4)

(100)

*Data in parenthesis are relative breakeven yields where the conventional farm was used as the reference yield

This means that organic farmers were earning more as shown in the net return over cash expense (NRCE).  NRCE is the ratio between the net return over the cash cost of production (Table 8).  NRCE was used instead of the usual return on investment (ROI) because ROI is the ratio between Gross Return over Total Cost of Production (Cash + Non-Cash).  The non-cash costs of production in rice farming under Philippine condition are paid in-kind at harvest time.  The farmers do not consider these items as costs.  What they consider as cash expenses were only those that required money as in buying inputs and in paying labor for transplanting.  Due to the high cash costs and the lower net revenue in the conventional farm, the NCRE values were lowest in the conventional farm and highest in the organic farms.  This means that rice farmers in the Philippine earn more money for every peso they spend in organic rice farming than in conventional and LEISA farming . 

Table 8.  Net return over cash expense ratio (NRCER) ratio among organic, LEISA and conventional farms in 2 sites, Philippines

Site

Organic

LEISA

Conventional

Infanta, Quezon

5.92

5.51

1.63

(363)

(338)

(100)*

Baco, Oriental

8.54

4.09

2.46

(347.2)

(166.3)

(100)

Average for

7.23

4.8

2.05

(353)

(234)

(100)

*Data in parenthesis are relative NRCE where the Conventional farming was used as the reference value

It was cheaper to produce 1 tonne of un-milled rice in organic than in LEISA and in conventional farming. (Table 9). 

Table 9.  Cost to produce 1 tonne (in USD) of un-milled rice in Organic, LEISA and Conventional Farms in 2 sites, Infanta Quezon and Baco, Oriental Mindoro

Site

 Organic

 LEISA

 Conventional

Infanta, Quezon

 46.0

 58.4

   80.0

(57.5)

(73)

(100)*

Baco Oriental,  Mindoro

57.8

67.2

77.6

(74.5)

(86.6)

(100)

Average for 2 sites

52.0

62.8

78.8

(66.0)

(79.7)

(100)

*Data in parenthesis are relative values where cost to produce 1 tonne of un-milled rice in conventional farming was used as the reference value

With globalization and the ensuing import liberalization, growing rice through the organic farming method could enable the farmers to compete with the influx of cheaply imported caloric food sources (bread, wheat) including rice.  Organic farming as adopted in rice production lessens the cash expense considerably. Where to borrow money is a big worry especially among women as they are the money keepers under Philippine culture.  It also minimizes the sleepless nights or nightmares of farmers especially during the rainy season.  Rains in the Philippines are mainly caused by typhoons and 18-20 typhoons hit the country every year. 

Energy Analysis 

The detailed energy audit of the various energy requiring operations and stages of rice production under organic, LEISA and Conventional farm in two sites (Infanta, Quezon and Baco, Oriental Mindoro) are shown in Appendix Table 3 and 4.  Energy Input utilization showed similar trends in both sites.  On the average, organic farms (Table 10) utilized the lowest amount of energy, which was only 36.6% of the total energy utilized in the conventional farms.  The LEISA farms were at the middle.  On average, they utilized only 62.2% of the energy utilized in the conventional farms.  Many researchers found the same result in earlier studies (Loake 2001; Refsgaard et al 1998; Pimentel et al 1983). 

The indirect fossil fuel based energy inputs (labor, seeds) were almost the same in both sites and in the 3 farm systems. It was only slightly higher in the organic farms at Infanta, Quezon.  This was because the case study farmer was hauling the manure and the rice harvest, and the distance was quite far from the farm to the feeder road.  The main factor, therefore, that caused the big difference in the total energy used in the 3 farms was the fossil fuel based energy inputs ((Table 10).  On the average, the organic farms utilized only 24.3% (LEISA 55.3%) of fossil fuel based energy inputs relative to the conventional farm. Of the total 2,848 Mcal ha-1 energy utilized in the conventional farms, 84% (2,385 Mcal ha-1) was the share of the fossil fuel based energy inputs. 

Table 10.  Energy inputs in Organic, LEISA and Conventional farms in two sites

Item

Organic,
Mcal ha-1

LEISA,
Mcal ha-1

Conventional,
Mcal ha-1

Infanta, Quezon

FFEI

612

1,338

1,793

(34.1%)*

(74.6)*

(100.0%)

IFFEI

530

496

504

Total Energy

1,142

1,834

2,297

Baco, Oriental Mindoro

FFEI

546

1,300

2,977

(18.3%)*

(43.7)*

(100.0%)

FFEI

402

412

423

Total Energy

948

1712

3,400

Average for 2 sites

FFEI:

578

1,319

2,385

(24.3%)*

(55.3)*

(100.0%)

IFFEI:

466

   454

   463

Total Energy

1,045

1,773

2,848

(36.6%)

(62.2%)

(100.0%)

*Data in parenthesis are percentage of energy utilized in organic and/or LEISA relative to Conventional farms (the reference value);
FFEI: Fossil Fuel based Energy Input
IFFEI: Indirectly Fossil FuelBased Energy Input

A detailed accounting on how the fossil fuel based energy inputs (FFEI) were utilized in relation to the total energy inputs (TEI) is shown in Table 11.  Agro-chemical inputs (fertilizer and pesticides) on the average, accounted for about 82.8% of fossil fuel based energy inputs (FFEI) in the conventional farms. At Baco, Oriental Mindoro, FFEI was about 88%.  Paddy fields at Oriental Mindoro were less fertile than Infanta, Quezon.  Thus, farmers were applying more fertilizers particularly nitrogen and nitrogen fertilizer utilizes high amount of energy (14.19 Mcal kg-1) during manufacture (Mudahar and Hignett 1985).  Nitrogen fertilizer alone accounted for about 69.1% for the FFEI or 60.5% of TEI in the conventional farms at Baco, Oriental Mindoro. In LEISA farms, the share of FFEI to TEI was 74% and only 54.8% on organic farms.  Agrochemical inputs were zero (0) in organic farms, 40.5% in LEISA and about 60.6% in the conventional farms. 

Table 11.   Percentage (%) share of the various energy inputs in Organic, LEISA and Conventional farms in two sites, Philippines

Input

Organic

LEISA

Conventional

% FFEI

%TEI

%FFEI

%TEI

%FFEI

%TEI

Infanta, Quezon

FFEI

-

  52.0

-

  73.0

-

  78.0

 Machinery + fuel

100.0

  52.0

45.3

  33.1

33.8

     26.4

 Agro-chemical

    0

54.7

  39.9

65.7

     51.3

IFFOEI

  48.0

  27.0

  21.9

   Labor

  19.5

    9.6

       7.8

  Seeds

  28.4

  17.4

     14.1

TOTAL

100.0

100.00

100.0

Baco Oriental Mindoro

FFEI

  57.6

  79.9

  88.0

 Machinery + fuel

100.0

  57.6

45.3

  34.2

20.5

     18.0

 Agro-chemical

    0

   

54.8

  41.7

79.5

     70.0

IFFOEI

  42.4

  24.1

  12.0

      Labor

  17.1

  10.1

       5.0

      Seeds

  25.3

  14.0

       7.0

TOTAL

100.0

100.00

100.00

Average for 2 sites 

FFEI

  54.8

  74.0

82.8

 Machinery + fuel

100.0

  54.8

45.3

  33.5

27.2

    22.2

 Agro-chemical

    0

54.7

  40.5

72.6

    60.6

IFFOEI

 

 

17.2

      Labor

  18.0

  10.5

     7.4

      Seeds

  27.2

  15.5

     9.8

TOTAL

100.0

100.0

100.00

Agro-chemical = fertilizer+ pesticides
FFEI = Fossil fuel energy inputs
IFFOEI = Indirectly Fossil Fuel Oil based Energy inputs
TEI = Total energy inputs

Because the conventional farms were utilizing a considerably high amount of fossils fuel based energy inputs, particularly in the form of agrochemical inputs (fertilizers and pesticides), their energy efficiencywas the lowest among the 3 farms (Table 12). 

Table 12.  Energy efficiency (Ee) and Energy intensity (Ei) of Organic, LEISA, and Conventional farms in two sites, Philippines

Indicator

Organic

LEISA

Conventional

Infanta, Quezon

Energy Efficiency (Ee)*

Ee (FFEI)

23.64(3.98x)

    9.57(1.61x)

    5.94

Ee (TEI)

  12.72

    7.0

    4.67

Energy Intensity (Ei)**

Ei (FFEI) Mcal t-1

140.0

350.0

560.0

Ei (TEI) Mcal t-1

260.0

475.0

714.0

Baco, Oriental Mindoro

Energy Efficiency (Ee)

Ee (FFEI)

19.4

    8.25

    3.91

Ee (TEI)

  11.18

    6.26

    3.42

Energy Intensity (Ei)

Ei (FFE) Mcal t-1

170

400

844

Ei (TEI) Mcal t-1

294

527

960

* Ee (FFEI)  =  Mcal of grain yield ÷ Mcal of Fossil Fuel based Inputs
 * Ee (TEI)    =  Mcal of grain yield ÷ Mcal of Total Energy Inputs
**Ei (FFEI)   =  Mcal of Fossil Fuel Based Inputs ÷ Grain yiled t ha-1
**Ei (TEI)     =  Mcal of Total Energy Inputs ÷ Grain Yield t ha-1

In this particular energy audit, the seeds and labor were given energy values.  At the farm level, farmers do not usually pay particular attention to these items.  Firstly, they are mostly using saved seeds from their previous harvests.  Second, they are farmers and they are there in the farm to work.  Thus, their labor is not considered as cost.  As in the financial analysis, these were treated as non-cash costs.  In this energy analysis they were grouped as indirect fossil fuel oil based energy inputs (IFFOEI).  Seed production also utilized fossil fuel-based energy and labor was also incurred in the various field operations.  If these items are not treated as cash-cost, they could also be treated as non-energy cost.  This would increase considerably the energy efficiency (Ee) of organic farms at Ee  =  21.5, and LEISA at Ee = 8.91.  Conventional farms had  Ee = 4.93.  This makes organic farms 4.4 times more energy efficient while LEISA was 1.8 times more energy efficient than the conventional farms. 

The organic farms were the least energy intensive (Ei).  Conventional rice farming utilized 4.2 times more FFEI when compared with rice grown the organic way. Comparing the 2 study sites , Ei was higher in Baco, Oriental Mindoro compared with Infanta, Quezon.  The higher Ei  at Baco,Oriental Mindoro was due to the higher amount of agrochemical inputs used, which in turn was due to its lower soil fertility.  Higher yields were also obtained by the case study organic rice farmer at Infanta, Quezon . 

The influence of season on energy use, energy efficiency and intensity was also estimated.  This was done only in Infanta, Quezon (Table 13).  The use of energy inputs (TEI, Mcal ha-1) was slightly higher during the dry season than the during the wet season in all of the 3 farms.  But the difference in energy use between dry and wet season was largest in LEISA, 678 Mcal ha-1, followed by the conventional farm 246 Mcal ha-1, and lowest in the organic farm at 33 Mcal ha-1.  The main reason is that the farmers were using more chemical fertilizers in both LEISA and conventional farms during the dry season than during the wet season.  Lesser risks due to typhoons, heavy rains and pests, and plenty of sunshine during the dry season motivate farmers to apply more yield-increasing inputs like chemical fertilizer particularly nitrogen in the conventional farms. 

Table 13.  Comparative seasonal (wet and dry) energy utilization; energy efficiency (Ee) and energy intensity (Ei) in Organic, LEISA, and Conventional farms, Infanta, Quezon

Season

Organic

LEISA

Conventional

Wet Season

FFEI, Mcal ha-1

    586

  1247

  1672

IFFEI, Mcal ha-1

    539

    498

    502

TEI, Mcal ha-1

  1125

   1245

  2174

Energy Output (Grain) (Mcal ha-1)

11754

 11235

  8835

Energy Efficiency (Ee)

          Ee (FFEI)

      20.0

 9.0

 5.3

          Ee (TEI)

      10.4

 6.4

 4.1

Energy Intensity (Ei)

          Ei (FFEI) (Mcal tonne-1)

     150

330

    570

          Ei (TEI) (Mcal tonne-1)

     290

 470

    738

Dry Season

FFEI, Mcal ha-1

    637

 1429

  1914

IFFEI, Mcal ha-1

    521

  494

    506

TEI, Mcal ha-1

  1158

 1923

  2420

Energy Output (Grain) (Mcal ha-1)

17359

 14486

12625

Energy Efficiency (Ee)

          Ee (FFEI)

      27.2

10.1

        6.6

          Ee (TEI)

      15.0

  7.5

        5.2

Energy Intensity (Ei)

          Ei (FFE) (Mcal tonne-1)

     132

 360

    550

          Ei (FFEI) (Mcal tonne-1)

     240

 480

    690

Ee (FFEI)  =  Mcal of grain yield ÷ Mcal of Fossil Fuel based Inputs
Ee (TEI)    =  Mcal of grain yield ÷ Mcal of Total Energy Inputs
Ei (FFEI)   =  Mcal of Fossil Fuel Based Inputs ÷ Grain yield t ha-1
Ei (TEI)     =  Mcal of Total Energy Inputs ÷ Grain Yield t ha-1

The higher yields obtained during the more photosynthetically productive and input efficient dry season cropping led to its higher energy efficiency (Ee) in the 3 farms when compared with the  wet season cropping. Higher yields (when expressed in calorific energy yields) during the dry months had sufficiently offset the higher energy use due to chemical fertilizer in both LEISA and conventional farms.  The case study organic farm was still superior when compared to LEISA and conventional farms.  Energy efficiency in the organic farms was about 3 times higher when compared to the conventional farm and about 2 times to that of LEISA. Consequently, the energy intensity (Ei) which is the production of 1 tonne of un-milled rice was less during the dry season compared with the wet season in the conventional farm.  Within seasons, Ei was 2.5 times higher in the conventional farms vs. organic farms during the wet season and about 3.0 times higher during the dry season. 

Bony’s study (1993) revealed that the increasing energy efficiency of maize production in France was mainly due to the increase in resource use efficiency, which in turn was due to the advent of bigger and more efficient tractors and decreased energy use in nitrogen fertilizer manufacture.  The use of bigger and more efficient machines could not be adopted in wetland paddy fields and the small farms in the Philippines.  Moreover, agrochemical input nominal prices are increasing with the increase in oil price and currency devaluation relative to the US dollar.  Thus, the more practical step to reduce energy use is for the farmers to adopt LEISA as a transitional practice and to go fully organic when organic fertilizer (compost, animal manure) could be made on-farm and the land ownership issue settled with the full implementation of a comprehensive agrarian reform program in the Philippines.


Conclusions 

Growing rice by the organic method was more energy efficient (4 times) compared to conventional and almost 2 times compared to Low External Input Sustainable Agriculture (LEISA).   The agrochemical input (chemical fertilizer and pesticides), while it was zero in the organic farms, was about 61% of the total energy inputs in the conventional farms and  reduced to 40.5% in LEISA.  Organic farms were using only 37% the total energy use on conventional farms, while  LEISA was using 62.2%.

Organic farms required the least amount of energy to produce 1 tonne of paddy rice.  Conventional farms used 3 times more energy to produce the same tonne of paddy rice compared with the organic farms. 

Agrochemical inputs (pesticides and fertilizer) were 83.4% of the cash cost production in the conventional farm.  It was 32% cheaper to produce the same quantity of paddy rice in organic compare to conventional farming.  Because of the lower cash expenditure in organic farms, the break-even yield (or the yield level to recover costs) was also lower in the organic farms  compared to conventional farmand LEISA farms. 

Organic farmers realized 7 pesos per 1 peso cash expense (net return over cash expense ratio, NCER) while only 2 pesos per peso expenditure in the conventional farm.  It was about 5 pesos in LEISA. 

Thus, in all the 3 major bases of comparisons (productivity, profitability, and energy use), growing rice the organic way was found to be a superior method.  Organic farmers obtained slightly higher yields on the average.  It was found to be the cheapest way to grow rice.  It required the least amount of energy (fossil fuel based energy).  The organic method is the rice farming system that holds greatest promise to uplift the economic plight of small-scale and resource-poor rice farmers.  The organic method of rice farming was shown to minimize cash expenses and the need for huge production loans.


Acknowledgement
 

Case study 1 (Infanta, Quezon) was funded by the Philippine Council for Agriculture Resources Research and Development (PCARRD), while case study 2 (Baco, Oriental Mindoro) was sponsored by Plan International Philippines.  The author would like to thank Ms. Lucila Pecadizo, University Researcher, Department of Agronomy, College of Agriculture, UP Los Baños, Laguna, who was instrumental in field data collection at Infanta, Quezon and Dr. Don Del Castillo of Plan International Philippines for facilitating the case study at Baco, Oriental Mindanao, Philippines. 


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Received 14 September 2002

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