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In Ecuador, sugar agroindustry is one of the oldest in the country. Because of its economic importance, sugar production constitutes a very significant activity, in which agriculture and industry are related, whose final product results in a good of the basic family basket. In addition, this activity impacts on the social area, by generating sources of employment (Pérez and Rappo 2016 and Prado-Pérez de Corko et al. 2018).
The potential of suitable lands for sugarcane production in Ecuador is 675,932 ha. Out of these, only 172,476 are sown, which represents 25.71% of the available total. From the total planted area, only 113,160 ha have been used for sugar production. The remaining 59,316 ha have been used in other productions, such as for ethyl alcohol, panela and ethanol (Prado-Pérez de Corko et al. 2018).
Pastaza province, located in the Ecuadorian Amazon, houses the Achuar, Andwa, Huaorarani, Kichwa, Shiwiar, Shuar and Zapara nationalities in its territory, as well as the migrant mestizo population of other provinces of Ecuador. Population data from Pastaza refers that 20,739 people are dedicated to agricultural activity.
Sugarcane is a perennial crop. Under the conditions of this region, it is exploited as monoculture or associated with other crops, and constitutes the main agricultural head of the province (GADPPZ 2014), with a total of 1,403.8 ha devoted to its sowing (Abril 2016). Fresh sugarcane or fruit sugarcane, cut for sale in tourist areas, is one of its uses. In addition to its use for preparing panela (granulated and in blocks), molasses, juices and spirits (Valle et al. 2015).
Panela sector in Ecuador and in Pastaza evidences a scientific-technical delay. It is more considered a manufactured production than an industrial one, because panela preparation is carried out in small factories. In addition, derivatives of panela agroindustry in the market are maintained under unfavorable conditions with respect to its main competitor, which is the white sugar that is produced in the sugar mills located in the Ecuadorian coast (Quezada-Moreno et al. 2015). Instability in the sale price of panela in the formal and informal market is characterized by the predominance of intermediaries, which do not pay differentiation for product quality, conditions that have caused a crisis in this productive sector (Murcia and Ramírez 2017). In this area, most agronomic tasks during sugarcane cultivation are manually performed. For this, day laborers are occasionally hired and the harvest is carried out by means of the thinning cut system. This system differs from the cut-off system, which is carried out in sugar mills from the Ecuadorian coast. Regarding agronomic management practices, planting system, fertilization and nutrition plans and control of pests, diseases and weeds (Ramírez et al. 2014) are implemented.
In Pastaza province, there is no information about the characterization of sugarcane production system. In addition, there are no available economic evaluations that allow measuring returns to investment nor arguing about stability of this production system, much less to understand the involvement of economic variables subjected to changes in climate and the incidence of pests and diseases.
Therefore, the objective of this study was to establish the socioeconomic and productive characteristics of sugarcane farmers in Pastaza province.
Materials and Methods
The current research was developed in Mera, Pastaza and Santa Clara cantons, Pastaza province, Ecuador (figure 1).
Edaphoclimatic characteristics of the studied area. Mera is located at 1,043 m o.s.l. It presents an annual precipitation of 5,580.4 mm and temperature of 20 to 22 ºC. Pastaza is at 960 m o.s.l., with annual precipitation of 4,562 mm and temperature between 19 and 23 ºC. Santa Clara is located at 595 m o.s.l., with an annual precipitation of 3,703 mm and temperature between 18 and 24ºC (Abril 2016). Soils of these regions have a wavy, hilly or broken physiography, with slopes inferior to 40% and correspond to the order of inceptisoles (Valle 2015), hidranteps and haplortox (Abril 2016). They have low fertility and high acidity. They present toxicity by aluminum and phosphorus deficiency, humidity saturation and low fertility, with great accumulation of organic matter (Valle et al. 2015).
The information for this study was obtained from farmers through the application of a formal survey, structured in four components: farmer characteristics, socioeconomic traits and production costs, features of productive areas and farming agronomic management.
To determine sample size, the record of the association of Pastaza sugarcane farmers was used, which contains 229 partners. The number of farmers to survey was obtained by the formula for finite populations (equation 1) (Aguilar 2005). It was considered a confidence level of 95%, with a total of 56 surveys to be carried out and the application of 50:
n = |
sample size (for finite populations) |
N = |
population size |
Z = |
Critical Z value, calculated in the tables of normal curve area (Z=1.96 for a 95% of confidence level) |
p = |
Approximate proportion of the phenomenon under study in the reference population (for the case under study 0.95) |
q = |
proportion of the reference population that does not present the phenomenon under study (for the case under study 0.05) (1 -p) |
d = |
absolute precision level (+/- 0.05) |
For performing this activity, each survey performed in the study area was georeferenced. The database of the Asociación de Cañicultores del Cantón Pastaza (ASOCAPA) was considered, which represents the largest volume of farmers. An amount of 53 surveys were applied in Pastaza, three in Santa Clara and two in Mera, made with four components: socioeconomic features and characteristics of the farmer, of the property and of the production.
Data was included in an Excel matrix and the numerical values were categorized in ranges. Among the quantitative variables, frequency analysis and correlation of Pearson R2 (Camacho 2008) was applied.
In the SPSS program (IBM 2013), a multivariate analysis of multiple correspondence with two-dimensional analysis was applied (Cuadras 2014). Cronbach alpha coefficient was obtained to establish sampling adequacy, according to variables sowing month, harvest month, type of seed, place of acquisition of seed, soil preparation, type of preparation, type of sowing, every how many years is renewed, control of pests and diseases, type of control, type of cutting, purpose of sugarcane production and buyer of production. Through a factorial analysis (Hair et al. 1999), the Kaiser Meyer Olkin (KMO) coefficient was determined to the variables farm area, area dedicated to cultivation, distance to the main road, distance to the production of nearby sugarcane, number of day wages/ha, permanent workers of the farm and hours of weekly work per person. The purpose of this methodology was to determine whether the sample size was adequate or not.
Results and Discussion
Results of the characteristics of the respondent (figure 2) showed that most farmers are between 31 and 70 years old (81.4%), 75.9% are male and 84.5% identified themselves as mestizos. The 41.7% of them have dedicated between 11 and 30 years to sugarcane production and 66.1% have primary instruction level. Among the other activities that are dedicated, tourism (19%) and trade (10.3%) are highlighted. Students (19%) were also included. More than half of the respondents have, at least, three people who depend on the farmer (figure 3). In turn, most of them live alone or with a member of the family (42% and 24%), with a monthly income between 501 and 1,000 USD (53.5%). Of the respondents, 23% reported that their greatest income source depends on sugarcane. However, the highest percentage (34.5%) reported that from 26 to 50% of their income come from sugarcane.
Regarding the characteristics of the farm (figure 4), the highest percentages of respondents reported farms with an area from 2 to 5 ha (39%) and from 31 to 50 ha (20.4%), which is also reflected in the area dedicated to cultivation, where 88.9% referred from 2 to 5 ha of sugarcane. This extension of cultivation is also the one that is most frequently informed by farmers from Malacato parish, in Loja province, Ecuador (Iñiguez et al. 2018). In this region, the main production also focuses on panela and sugarcane rod. Likewise, the highest percentage of farmers alleged to be the owner of the land, a result that is very similar to 85% obtained in this study. Vargas et al. (2018) stated that the highest percentage of farms in Orellana province, Ecuador, has extensions between 11 and 50 ha. After them, there are farms with less than 10 ha, with topographic characteristics of a flat land (37.9%) and wavy (44.8%), surrounded by pasture (38.9%), forest (22.2%) and other crops (31.5%).
As for access (figure 5), most of the farms have ballast (44.4%) and asphalt (38.9%) roads. Bagasse (59.5%), as a byproduct of ground sugarcane, is used as a coverage for access to the culture area. More than half of the farms (72.6%) have a distance of up to 500 m to the main road and other sugarcane productions (83.7%).
Regarding the preparation of soil and sowing (figure 6), more than 80% perform soil preparation, and the most used methods were making holes with stakes (41.4%) and with machete (34.5%). Sowing is conventional or manual, and, in most cases, sowing renewal is not carried out. It is performed in January (20%), although the majority refers to do it in any season (44.8%).
The agricultural seed (figure 7) used by the 51.8% of surveyed farmers is Limeña variety. The traditional seed type (sugarcane top) is used for propagation, which is acquired in the same farm (43.5%) or in farms of neighbors and relatives (34.8%) of the farmer.
In responses to questions about crop management (figure 8), more than 50% of respondents stated that they do not perform phytosanitary controls, and those who control, use agrochemicals (29%), mainly. Those that do not practice it, alleged that it is due to lack of resources (12%), and because pests do not generate significant damage (8.6%). Most farmers apply fertilization (62.8%). Those who do not use it, explain that it is also due to the absence of resources (15.4%) and because the soil does not require it (9.6%).
All farmers perform manual cut (figure 9), and more than half of the production is dedicated to the sale for panela production (51%). The sale of fruit sugarcane follows (24%). Local traders sold 42% of production, and 95.5% do not maintain contract for sale. As for the harvest season, April and any month were the most informed ones.
The highest percentage of farmers reported volumes from 1 to 5 m3/ha in sugarcane and panela production (table 1). In lower proportions, it was recorded from 1 and 6 to 10 m3/ha for fruit sugarcane, and from 21 to 30 m3/ha for panela. Martín and Pérez (2009) also reported this type of production. They only referred from 6 to 10 m3/ha for spirits. As for the sale, for sugarcane unit and for block panela unit, and a kilogram of granulated panela, the value of a dollar was recorded. For spirits, the highest percentage had a price inferior to one dollar per liter.
Table 1 Production and sale
| Range | % of farmers | ||||
|---|---|---|---|---|---|
| Fruit sugarcane | Panela | Spirits | |||
| Production, m3/ha | < 1 | 5.5 | |||
| 1 to 5 | 25.3 | 10.4 | 1.8 | ||
| 6 to 10 | 5.5 | 1.8 | 1.8 | ||
| 11 to 20 | 1.8 | 1.8 | |||
| 21 to 30 | 3.6 | 8.6 | 1.8 | ||
| 31 to 40 | 1.8 | 1.8 | |||
| > 40 | 3.6 | 3.5 | |||
| Does not produce with that purpose | 32 | 28 | 90 | ||
| Does not have a record of production | 18.9 | 46.1 | 4.6 | ||
| Sale Price in USD per unit (fruit sugarcane and panela in blocks), kg (granulated panela) and litter (spirits) | < 1 | 13.8 | 5.4 | ||
| 1 | 34.5 | 31* | 12.1** | ||
| 1.1 to 2 | 3.4* | 6.9** | |||
| >2 | 3.4* | 1.8** | |||
*panela in blocks
**granulated panela
As table 1 shows, productivity was low, if it is considered that, in the area, 1 m3 of fruit sugarcane is constituted by 400 stems. Therefore, the highest percentage of farmers, which produces from 1 to 5 m3/ha, reaches 20,000 stems. An amount of 40,000 stems/ha, on average, reaches the industrial productions of sugar mills (Cruz et al. 2013).
As for staff costs (table 2), the highest percentage of respondents estimated a price between 101 to 500 USD per hectare for the preparation stage (48.9%) and sowing (46%). In most farms, there is a permanent worker (30.8%), and two people (32.7%) spend from 5 to 8 h a week in the farm. Two wages are preferably used for cutting and hauling, at a cost from 101 to 500 USD/ha for cutting, and between 51 and 100 USD/ha for hauling. Regarding average costs per hectare, the preparation reported 1,032 USD/ha and 2,260 USD/ha for sowing. These two first values are considered only once in the life cycle of the crop, since it becomes perennial, without performing these tasks again in the same area. With regard to the daily cost of crop maintenance, 15.6 USD is reported as average, and 343.2 USD per month. Only one farmer referred to make mechanized haul and harvest, with costs of 30 and 20 USD/ha, respectively. Manual harvest and hauling registered an average cost of 215 USD/ha and 83.7 USD/ha, respectively.
Table 2 Human resources
| Cost | |||||
|---|---|---|---|---|---|
| Production | Cutting and hauling | ||||
| Cost (USD) | Percentage of surveyed farmers | Cost (USD) | Percentage of surveyed farmers | ||
| Preparation (ha) | < 100 | 17.0 | Cutting | without cost | 3.9 |
| 101 to 500 | 48.9 | < 20 | 7.8 | ||
| 501 to 1000 | 10.6 | 20 to 50 | 13.7 | ||
| 1001 to 3000 | 14.9 | 51 to 100 | 17.6 | ||
| > 3000 | 8.5 | 101 to 500 | 56.9 | ||
| Sowing/ha | < 100 | 8.0 | >500 | 3.9 | |
| 101 to 500 | 46.0 | Hauling | without cost | 4.3 | |
| 501 to 1000 | 16.0 | >20 | 19.6 | ||
| 1001 to 5000 | 24.0 | 20 to 50 | 23.9 | ||
| >5000 | 6.0 | 51 to 100 | 37.0 | ||
| Daily work | Up to 10 USD | 13.2 | 101 to 500 | 15.2 | |
| 11 to 20 | 79.3 | ||||
| 21 to30 | 7.6 | ||||
| Staff | |||||
| Permanent workers | Percentage of surveyed farmers | Hours of work per person, per week | Percentage of surveyed farmers | Number of wages /ha cutting and hauling | Percentage of surveyed farmers |
| 1 | 30.8 | 4 hours | 3.7 | 1 | 17.4 |
| 2 | 32.7 | 5 to 8 | 50 | 2 | 26.1 |
| 3 | 17.3 | 9 to 16 | 9.3 | 3 | 17.4 |
| 4 | 7.7 | 30 to 40 | 24.1 | 4 | 15.2 |
| 5 | 3.9 | >50 | 8.5 | 5 | 8.7 |
| 6 to10 | 3.9 | 6 to 10 | 6.5 | ||
| >10 | 3.9 | >10 | 8.7 | ||
Regarding machinery and equipment (table 3), the highest percentage of respondents reported having 1 and 2 manual fumigation pumps, 22.4% each. Costs between 51 and 100 USD were recorded, with average cost of 62 USD. Only a 13.8% informed having a motor fumigation pump.
Table 3 Tools, equipment and machinery
| ITEM | Amount | Percentage of farmers that reported | Cost (USD) | Percentage of farmers that reported | ITEM | Amount | Percentage of farmers that reported | Cost (USD) | Percentage of farmers that reported |
|---|---|---|---|---|---|---|---|---|---|
| Manual pump | 1 | 22.4 | 10 to 20 | 6.9 | Tools | 1 | 9.3 | <10 | 18.6 |
| 2 | 22.4 | 21 to 30 | 13.8 | 2 | 9.3 | 11 to 20 | 16.3 | ||
| 3 | 5.2 | 31 to 50 | 8.6 | 3 | 30.2 | 21 to 30 | 14 | ||
| 5 | 3.4 | 51 to 100 | 20.7 | 4 | 9.3 | 31 to 50 | 14 | ||
| <10 | 1.7 | >100 | 5.2 | 5 | 7 | 51 to 100 | 16.3 | ||
| Motor pump | 1 | 13.8 | <100 | 6.8 | 6 a 10 | 23.3 | 101 to 500 | 11.6 | |
| 3 | 1.7 | 100 to 500 | 3.4 | 11 to 20 | 9.3 | 501 to 1,000 | 9.3 | ||
| 5 | 1.7 | 501 to 1,000 | 3.4 | > 20 | 2.3 | ||||
| 20 | 1.7 | > 1,000 | 5.2 | Boiling pan | 1 | 6.9 | < 100 | 1.7 | |
| Stationary pump | 1 | 6.9 | <100 | 1.7 | 2 | 1.7 | 500 to 1,000 | 5.2 | |
| 3 | 1.7 | 101 to 500 | 5.2 | 3 | 5.2 | ||||
| 4 | 1.7 | 501 to 1,000 | 1.7 | 4 | 5.2 | 1,001 to 5,000 | 15.5 | ||
| >1,000 | 1.7 | 5 | 6.9 | ||||||
| Sugar mill | 1 | 27.6 | > 100 | 1.7 | Truck | 1 | 8.6 | 6,000 | 1.7 |
| 500 to 1,000 | 6.8 | 10,000 to 15,000 | 5.2 | ||||||
| 1,001 to 5,000 | 13.8 | ||||||||
| 2 | 1.7 | 10,000 | 3.4 | 2 | 1.7 | 15,001 to 20,000 | 3.4 | ||
| 20,000 | 1.7 | ||||||||
| 80,000 | 1.7 | 30,000 | 1.7 |
Out of the surveyed farmers, 6.8% have invested less than 100 USD in motor pumps. The 5.2% has spent more than 1,000 USD in motor pumps, with average cost of 936 USD. Of the farmers, 6.9% said having a stationary pump, with investment from 101 to 500 USD. The 8.6% of the farmers have a truck, with a value range between 10,000 and 15,000 USD and average cost of 13,574 USD. The 27% have a sugar mill, with a value between 1,001 and 5,000 USD, with a general average cost of 9,175 USD. For panela manufacturing, farmers have from one to five boiling pans. The largest investment range in this field is from 1,001 to 5 000 USD, and an average of 2,460 USD is invested in boiling pans.
Regarding tools, the machete was the most used, and farmers reported three tools with the highest percentage. With an investment cost from less than 10 and up to 100 USD, between six and ten tools were included. The cost of land hectare without improvements (figure 10) ranged, mostly, between 1,001 and 5,000 USD, and from 20, 001 to 30,000 USD, with a mean of 18,755 USD.
Table 4 shows the costs of fertilization and phytosanitary controls, where the most used items are insecticides, with cost range of 11 to 15 USD/ha (5.7%) and an average value of herbicides with less than 5 USD/ha (13.3%). In chemical fertilizers, the highest percentage of respondents indicated to spend between 40.1 and 50 USD/ha (5.7%), and, in biological fertilizers, between 101 and 50 USD/ha (11.9%). For phytosanitary, application costs had higher percentages, with reports between 11 and 30 USD/ha. Meanwhile, in chemical fertilizers, 98% of farmers did not consider application cost. In the biological fertilizers, the range between 11 to 50 USD/ha was the most informed.
Table 4 Fertilization and phytosanitary controls
| Cost of product USD/ha | Percentage of surveyed farmers | Mean cost, USD | Application cost, USD/ha | Percentage of surveyed farmers | Mean cost, USD | ||
|---|---|---|---|---|---|---|---|
| Phytosanitary | Fungicides | 5 | 1.9 | 0.69 | 0 | 1.9 | 3.4 |
| Insecticides | < 10 | 1.9 | 2.61 | 1 to 5 | 3.4 | 1.7 | |
| 11 to 15 | 5.7 | 6 to 10 | 1.9 | ||||
| Herbicides | < 5 | 13.3 | 5.9 | 11 to 20 | 6.9 | 3.4 | |
| 6 to 10 | 5.7 | 21 to 30 | 5.2 | ||||
| 11 to 20 | 1.9 | 31 to 50 | 3.4 | ||||
| 21 to 30 | 1.9 | 51 to 100 | 3.4 | ||||
| 50 to 90 | 1.9 | ||||||
| >100 | 1.9 | > 100 | 3.4 | 0 | |||
| Coadjuvant | 1.31 | 1.9 | 0.35 | ||||
| Fertilizer | Chemical | > 5 | 3.8 | 19.2 | 0 | 98.3 | 10.8 |
| 5.1 to 10 | 3.8 | ||||||
| 10.1 to 20 | 1.9 | 140 | 1.9 | ||||
| 40.1 to 50 | 5.7 | ||||||
| Biological | <1 | 1.9 | 122 | 0 | 8.5 | 28 | |
| 1 to 5 | 1.9 | <1 | 3.4 | ||||
| 5.1 to 10 | 3.4 | 1 to 5 | 3.4 | ||||
| 11 to 50 | 1.9 | ||||||
| 51 to 100 | 1.9 | 11 to 50 | 10.2 | ||||
| 101 to 500 | 11.9 | ||||||
| > 500 | 3.4 |
KMO test resulted in a value of 0.772, which is considered as adequate (Cuadras 2014), with which the used sample size is justified. The principal component analysis (table 5), carried out with the characteristics of the property and production costs, showed the formation of a single component in the explained total variance, with eigenvalues superior to the unit, which reports 54.4% of variance. In turn, the matrix of components (table 6) showed that the main factors that influenced on the variance of the survey were property extension and sowing area.
Table 5 Total variance explained in the analysis of principal components
| Component | Initial values | Squares of the sums of load extraction | ||||
|---|---|---|---|---|---|---|
| Total | Variance percentage | Accumulated percentage | Total | Variance percentage | Accumulated percentage | |
| 1 | 3.807 | 54.38 | 54.38 | 3.81 | 54.38 | 54.38 |
| 2 | 0.999 | 14.28 | 68.66 | |||
| 3 | 0.771 | 11.01 | 79.67 | |||
| 4 | 0.696 | 9.95 | 89.62 | |||
| 5 | 0.435 | 6.21 | 95.83 | |||
| 6 | 0.163 | 2.33 | 98.163 | |||
| 7 | 0.129 | 1.834 | 100.00 | |||
Extraction method: analysis of principal components
Table 6 Matrix of components
| Parameter | Component |
|---|---|
| Property extension | 0.934 |
| Area dedicated to sowing | 0.908 |
| Distance to the main road | 0.739 |
| Distance to the nearby sugarcane production | 0.833 |
| Number of wages for cutting/ha | 0.534 |
| Number of permanent workers | 0.711 |
| Labor hours per person, per week | -0.282 |
The correlation coefficient (table 7) shows that farm extension was the variable with more significant correlations for 0.01, with the area dedicated to sowing, distance to the main road and distance to the nearby sugarcane production, number of wages for cutting/ha and number of permanent workers, and for 0.05 with the cost of cut. The area dedicated to sowing also expressed correlations at 0.01, with the distance to the main road, distance to the nearby sugarcane production, cost of sowing/ha and number of wages /ha. The distance to the main road showed correlation of 0.01, with the distance to the nearby sugarcane production and number of wages for cutting/ha. Panela production in m3/ha had correlation at 0.05, with hauling cost and number of labor hours per person, per week.
Table 7 Correlation coefficient
| Area dedicated to sowing | Distance to the main road | Distance to the nearby sugarcane production | Sowing cost USD/ha | Number of wages for cutting/ha | Cutting cost/ha | Hauling cost | Permanent workers | Panela m3/ha | Fruit sugarcane m3/ha | |
|---|---|---|---|---|---|---|---|---|---|---|
| Extension, ha | 0.54** | 0.64** | 0.57** | 0.17 | 0.53** | 0.36* | 0.13 | 0.48** | 0.37 | 0.08 |
| Area dedicated to sowing, ha | 0.61** | 0.74** | 0.72** | 0.49** | 0.04 | -0.08 | 0.27 | -0.16 | 0.27 | |
| Distance to the main road | 0.46** | -0.11 | 0.44** | 0.13 | 0.17 | 0.27 | 0.43 | -0.19 | ||
| Distance to the nearby sugarcane production | 0.30 | 0.24 | -0.13 | -0.07 | 0.44** | 0.09 | -0.02 | |||
| Soil preparation cost | 0.17 | 0.31* | 0.33* | -0.06 | -0.20 | -0.13 | ||||
| Hauling cost | 0.16 | 0.55* | 0.18 | |||||||
| Labor hours per person, per week | 0.52* | -0.09 | ||||||||
| Panela production, m3/ha | 0.78* |
*.**. Correlation is significant at level 0.01 (2 lines)
Correlation is significant at level 0.05 (2 lines)
The analysis of reduction of dimensions in the total two-dimensional model, which analyzed the qualitative variables related to cultivation and marketing, reported a Cronbach Alpha coefficient of 0.9, which indicates good internal consistency of the survey (González and Pazmiño 2015 and Oviedo and Campo 2005). As for the respondents, the dimensional reduction analysis (figure 11) showed the formation of a concentric grouping, and a second more dispersed formation, except one respondent, who was not included in the two previously mentioned groups. Out of the evaluated variables, the centroid was placed in the question to the buyer of the production, being this the one with the lowest variability.
Conclusions
In sugarcane production, there is a predominance of mestizo farmers with primary instruction, which have, in the majority, more than ten years dedicated to production, although this is not their main income source.
Manual labors predominate in production, and investment costs in tools do not exceed 100 USD.
Properties have extensions of up to 5 ha, also intended for sowing. For the most part, they are located at a distance of 500 m with respect to the main road and to other productions.
The culture is sown only once, without renewal being carried out. It focuses, mainly, in the production of fruit sugarcane and panela. Less than 30% of farmers have the required equipment for panela processing and for its transportation.
Most farmers do not carry out phytosanitary controls. The use of herbicides and biological fertilizers stands out. The product is mainly sold to local merchants.
