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Revista Ciencias Técnicas Agropecuarias

versión On-line ISSN 2071-0054

Rev Cie Téc Agr vol.26 no.1 San José de las Lajas ene.-mar. 2017

 

Revista Ciencias Técnicas Agropecuarias, 26(1): 40-49, 2017, ISSN: 2071-0054

 

ORIGINAL ARTICLE

 

Zoning of the Territory to Apply Conservation Tillage Mechanics Using the Evaluation Approach

 

Zonificación del territorio para aplicar labranza de conservación mecanizada utilizando el enfoque de evaluación multicriterio

 

 

M.Sc. Lizardo Reyna-Bowen,I M.Sc Mauricio Reyna-Bowen,II Dr. Lenin Vera-Montengro,I

IEscuela Superior Politécnica de Manabí, Facultad de Ingeniería Agrícola, Campus Politécnico, Calceta, Manabí, Ecuador.
IIUniversidad Técnica de Manabí, Facultad de Ingeniería Agrícola, Campus Lodana vía Santa Ana, Manabí, Ecuador.

 

 


ABSTRACT

The province of Manabi is one of the main farming areas of Ecuador, and it has seen an increase in land use in response to the demand for food. Unfortunately, this area growth has brought problems such as inadequate field planting techniques and forest destruction. Alternative techniques or processes to improve productivity in the medium and long term should be the guidance for farmers. Soil conservation practices using mechanized tillage, or conservation tillage (CT), could be an effective option. The objective of this research was to determine areas suitable for mechanized conservation tillage using the method of multi-criteria evaluation (ME).\ A group of specialists from the area, previously selected by area of expertise, appraised land use based on physical characteristics observed through geographic information system (GIS). \Following the appraisal of different maps, various levels of adequacy were found, and a final zoning map for mechanized conservation tillage was created. Multi-criteria evaluation showed that Manabi province has 8.68% of total area at the suitable level for mechanized conservation tillage when using crop rotation.

Key words: weights, remote perception, NDVI, crops, zones.


RESUMEN

La provincia de Manabí representa una de las principales zonas de actividad agropecuaria del Ecuador, lo que ha permitido incrementar las superficies de uso, respondiendo a la demanda de los productos alimentarios. Pero este crecimiento de frontera ha traído consigo problemas como: técnicas de siembra de campo inadecuadas y destrucción del bosque. La existencia de alternativas de técnicas o procesos que permitan mejorar la productividad a mediano y largo plazo debe ser la orientación para los productores agrícolas, es allí donde las prácticas de conservación de suelo usando mecanización de siembra directa o labranza de conservación (LC) podría ser la opción efectiva. El objetivo de la presente investigación fue determinar las zonas aptas para la labranza de conservación mecanizada, utilizando el método de la evaluación multicriterio (EM), que consistió en un grupo de especialistas del área previamente seleccionados y cuyas ponderaciones se realizaron sobre la base de la experiencia, teniendo las características físicas como factor principal en el uso del suelo, por medio del sistema de información geográfica (SIG). Los resultados presentan diferentes niveles de aptitudes tras la combinación de distintos mapas ponderados que permitió el logro del mapa de zonificación para la labranza de conservación mecanizada. Se concluye la efectividad de la evaluación multicriterio que describe a la provincia de Manabí con 8,68 % de superficie total para la labranza de conservación mecanizada en el nivel apto, cuando se utilizan cultivos de rotación.

Palabras clave: ponderaciones, percepción remota, NDVI, cultivos, zonas.


 

 

INTRODUCTION

Manabí province is one of the most important agricultural regions in Ecuador, representing 15.84% of the nation’s agricultural surface areas. The necessity to increase food production to meet population demand has led to a horizontal increase in agricultural areas, according to INEC (2010). Inadequate planting techniques Reyes (1996), increased agricultural territory, and forest destruction are the consequences of not applying alternative systems of natural resource conservation.

An alternative system is conservation tillage, which consists of a series of techniques to conserve, improve, and efficiently use natural resources through the integrated management of soil, water, biological agents, and external inputs FAO (2002). The benefits of this system are: productivity, decrease in erosion, conservation of soil moisture, greater soil biological activity, and reduction in production costs.

Application of this system can be determined by the multicriteria method, a tool that assists in decision making in complex development projects, where the best solution alternative is chosen by consensual agreement (Grajales-Quintero et al., 2013). The decision process requires comparison among several alternatives to face a certain dilemma. According to Saaty y Sagir (2009), this method breaks down a complex problem into a structure of various levels, objectives, criteria, subcriteria, and alternatives. The literature demonstrates the use of this methodology of consensual agreements to find alternative solutions in the agricultural sector (Lee, 2005; Abdulai et al., 2011; Mariano et al., 2012; Roco et al., 2012; Vera-Montenegro et al., 2014).

In the zoning of a territory, modern agriculture uses specific tools such as geographic information systems (GIS), which in conjunction with logical and physical elements, saves and processes georeferenced data to produce useful information for decision making.

The current agricultural situation requires an improvement in production systems to increase the productivity and conservation of natural resources in the medium and long term. To this end, the current investigation proposes to define the zones adequate for mechanized conservation tillage as an alternative tool, using the method of multi-criteria evaluation (ME).

 

METHODS

Manabi, one of the major provinces in Ecuador, is located in the coastal region. Located at latitude 1º3’8”S and longitude 80º27’20”W, Manabi has climatic conditions that oscillate between subtropical dry and tropical wet. The wet season, beginning at the start of December and ending in May, is hot due to the influence of the warm ocean current el Niño.

The dry season, from June to December, is less hot and is influenced by the cold current Humboldt. The temperature is not uniform throughout the province: the mean temperature in the mainland capital, Portoviejo, is around 25ºC, while it is around 23ºC in the coastal port city, Manta (Gobierno Provincial de Manabí, 2012).

The principal sources of information used in this study were SIN (Sistema Nacional de Information) and FAO. These allowed us to obtain documents, land use plans, and satellite images (Landsat, corresponding to 2003), which served as data inputs for the generation of new information. Information about conservation tillage was obtained in a similar way as the FAO database.

The following describes the cartographic information used:

Macro Zonification

-Map of the soil at a national level showing attributes such as water tables, slope, stoniness, effective depth, and texture in .shp format scaled at 1: 200,000

-Contour maps of all Ecuador.

Micro Zonification

-Coverage and land use maps scaled 1:25,000 of two cantons in Manabi: 24 de mayo and Pajan.

-Image Landsat 5 of 2003.

Additionally, our investigation procedures relied on work completed by the project “Geo-información” which consisted of the digitalization of the official map (CLERSEN 2011).

The procedures including the multicriteria evaluation method are outlined in the flowchart below (Figure 1).

 

Reference System

Having obtained the inputs for the maps and official cartography, they were applied to the same spatial reference system using the software Arcgis 10 with the Project tools; the maps were found at Datum Psad 56 and changed to Datum WGS84 using number 6 in Project tools to adjust the transformation constant to improve the transformations. No problems were encountered in the analysis of various layers in continuous maps.

Multiriteria Group

Experts opinions in the areas related to this study were obtained through an internet survey. The collaborators are listed below.

-Specialist in sustainable agriculture

-Specialist in soil

-Specialist in Water resources

-Specialist in Agricultural mechanization

-Specialist in agronomy

Each expert selected from the group of specialists evaluated the soil attributes in a qualitative manner, creating hierarchies of soil attributes. With this hierarchical order, values between 0 and 100 simulated a percentage system. The principal variables were determined by their respective quantitative values and qualitative descriptions. The same evaluation on the scale of 0 to 100 was then made with the attributes of each variable. To equalize the variables, each variable was divided into 4 attributes and applied to a decision tree representing each of the equal parts. In this manner, an equitable decision could be made without unfairly favoring any variable.

Maps as Limiting Factor

Limiting factors were applied to prevent the software from making decisions in those areas, and to make better distributions of the evaluations of attributes and variables. The variables were the following: national parks, natural reserves, populated areas, shrimp farms, mechanizable zone, and agricultural zone with perennial crops.

Individual maps of each area were generated; such maps of populated zones, shrimp farms, national parks, and natural reserves were coded 0, while maps of mechanizable zone and agricultural zone were coded 1. These maps were transformed to a raster graph and then united with a tool in Software ILWIS 3.3: operations - raster operations - cross. Thus, a single map was created named “limitation.” The map of mechanizable zones was created using a maps of slopes, where slopes up to 12% received code 1 and any higher percentages received code 0. All of these maps were passed through the raster tool with only two numerical attributes, or codes, where the software could calculate the areas with code 1 and could not calculate the restricted areas with code 0.

Agricultural Areas of Crop Rotation

The agricultural attributes were grouped by a criterion of conservation and divided into two groups: Agricultural rotation zone and Not applicable. The following attributes were included in the Agricultural rotation group: short rotation cycle crops, cultivated grains/grasses, rice crops, corn crops, and others. The Not applicable group included the following attributes: primary forest, secondary forest, planted forest, perennial crops, cocoa, coffee, forest plantations, bodies of water, and shrimp farms. Attributes that were found to be mixed were classified into the group with a majority composition; for example, an attribute with the composition 70% forest and 30% cultivated grain/grass would be classified to the Not applicable group. After classification into the two groups, a map of agricultural zones was generated. It was then verified by data obtained with the image Landsat 5 from 2013 through visual interpretation using the software ILWIS 3.3 with Índice de Vegetación (NDVI).

Having classified the attributes into two groups, a map was generated for each attribute using the tool in ArcGis 10, Arc Toolbox - Data Management Tools - Generalization - Dissolve. Using the Resample tool, all images were resized to the same cell size in order to overlay the maps in the same reference system. A visual analysis was conducted in homogenous groups to improve the interpretations. The groups consist of the following:

-Forest

-Population

-Shrimp Farm

-Agriculture zone

-National Park

Only anthropized/cultivated zones, those which use crop rotation, were prioritized, as the intrinsic objective of this project was to optimize these areas for increased productivity at the medium and long term while maintaining the soil sustainably for future generations.

Landsat Image Processing

The majority of the required data about surface coverage were extracted from the image using the índice de vegetación (NDVI), which highlighted and differentiated vegetation coverage. To verify that the attributes of the map corresponded with the satellite image, a map of coverage and land use from 2002 was superimposed over our map to verify the zones with greatest biomass. This verification procedure was adequate as our study focuses on the areas already anthropized/cultivated.

The use of índice de vegetación is a fundamental tool for this type of data extraction, which consists of the combination of the satellite band image LandSat 5, Band 4 found in the near-infrared spectral range TM 0.76-0.90 and Band 3 found in the visible red spectral range TM 0.63-0.69. The combination of these bands allows the most vigorous vegetation mass to reflect as white; the result is in the range -1 to 1, where 1 indicates the most vigorous vegetation and -1 represents bodies of water. The formula x=(B4-B3)/(B4+B3) was executed in Map-calculator to process the combination of bands.

Multicriteria Tree for Zoning

With all data gathered and processed, the final step was multicriteria evaluation in the Software ILWIS 3.3. A decision tree was created using the decision tree tool and map data inputs such as Texture, Depth, Stoniness, Slope, and Water Table Level. Using the raw values of appraisals from the expert surveys and interviews, average values were calculated for each variable and attribute. These average values were put in columns to create a map of each variable, with each map showing the attribute values of each variable. Factors and limitations were added using a direct evaluation/weighted method with the tools of Software ILWIS 3 3 - operations - Raster operations - Spatial Multi-criteria Evaluation. The weights were standardized automatically to obtain only one value between 0 and 1 for each variable. With these data, a final output map was obtained, with values ranging from 1, representing the most appropriated zones for mechanized conservation tillage, to 0, not apt.

 

RESULTS AND DISCUSSION

Determination of Agricultural Areas

Table 1 shows the classifications obtained according to the associated agricultural attributes. A greater proportion is occupied by Rotational Agriculture Zone. This may be due to the presence of soil of sedimentary origin, which is more fertile for agricultural activity. This finding supports the data from INEC (2010), which demonstrated that Manabí province has become one of the main agricultural producers.

Weighting Variables of Multicriteria Group

Aptness of each attribute for conservation tillage in percent and fraction form is shown in Tables 2 and 3. The values were divided by the greatest value in the sum of attributes. Slope was a limiting factor, as the maximum slope for mechanized agricultural labor is 12%. Other limiting factors included populated areas, national parks, shrimp farms, and protected areas like parks and national reserves.

Multicriteria Decision Tree for Zoning Mechanized Conservation Tillage

The area suitable for mechanized conservation tillage in Manabi is 165,683 ha, or 8.68% of the province area. It is such a small area due to the fact that the majority of the province has a slope greater than 12%, as it is seen in Figure 2.

In the table 4 the legend of the map of zonification of conservation farm is represented.

 

CONCLUSIONS

It was found that Manabi province, with 1,105,000 ha of rotational agriculture zones, representing 59% of the total area, has an area of 165,683 ha suitable for mechanized conservation tillage, which is 8.68% of the total area.

The most important, significant and dominant variable in the hierarchical order or percentage is slope, as determined by the results of expert evaluations. The method of multicriteria evaluation was found to be effective for decision making in the zoning of mechanized conservation tillage.

 

ACKNOWLEDGEMENTS

Agradecemos principalmente al grupo de experto que por motivo de muchas ocupaciones laborales, igual manera prestaron la ayuda necesaria para compartir sus experiencias en este proyecto. We would like to thank the group of experts who contributed their time and effort in sharing their experiences in this project.

 

NOTES

1 RHADADES, R.: Las múltiples facaetas del investigador agrícola, en socio-economía, problemas de definición de objetivos, SNT-3P, 1994.

*La mención de marcas comerciales de equipos, instrumentos o materiales específicos obedece a propósitos de identificación, no existiendo ningún compromiso promocional con relación a los mismos, ni por los autores ni por el editor.

 

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Received: 08/05/2015
Approved: 14/11/2016

 

 

Lizardo Reyna-Bowen, Profesor Escuela Superior Politécnica de Manabí, Facultad de Ingeniería Agrícola, Campus Politécnico, Calceta, Manabí, Ecuador. Email: lizadorb2021@gmail.com

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