PhD

The study was carried out with the objective of developing a ‘spatial crop suitability model’ through participatory and integrated land evaluation approach in a selected watershed with diversified agro-ecological situation and to evaluate the response of Agricultural Officers towards land evaluation for sustainable agriculture development. Besides, the utility of the model as perceived by the farmers was also studied.

The locale of the study was Thiruvananthapuram district of Kerala with all the Agricultural Officers working in the district as respondents for studying their response towards land evaluation. A selected watershed area namely ‘Aruvipuram watershed’ of 3109.12 hectares within Neyyar river basin having diverse agro-ecological situation was identified for developing the spatial crop suitability model and 30 progressive farmers of the selected watershed area was used as respondents for studying the perceived utility of the spatial crop suitability model.

The dependent variables were awareness, knowledge and attitude. The selected 17 profile characteristics of Agricultural Officers formed the independent variables.

The most important biophysical and socio-economic factors of land evaluation for the study were identified using Pusa rank sheet for Q-sort through ranking by selected judges. Primary spatial data base of biophysical factors were generated using secondary data, remote sensing data and ground truth. Participatory land evaluation of biophysical factors were carried out through Participatory Appraisal of Natural Resources (PANR). Integrated land evaluation was fulfilled by deriving the spatial crop suitability model through Geographic Information System (GIS). With help of the spatial model supported by participatory crop wise land evaluation of socio-economic factors, crop suitability recommendations for the watershed area was arrived at in line with the ‘factor rating’ method of FAO for crop suitability at S1, S2 and S3 levels (highly suitable, moderately suitable and marginally suitable respectively). Focus group interview was adopted to study the perceived utility of the model by the farmers. The awareness, knowledge and attitude of Agricultural Officers towards land evaluation were studied through a teacher-made test, knowledge test and attitude scale respectively developed for the purpose of the study. Mean, percentage analysis and correlation analysis were the major statistical tools employed.

The study helped in identifying thirteen biophysical factors namely slope, rainfall, physiography, soil depth, soil texture, soil drainage, soil erosion, temperature, elevation, presence of rocks/stones/gravels, soil pH, ground water and major nutrients. The six identified socio-economic factors were economic viability, economic feasibility, infra-structural facilities, market demand, social acceptability and farming experience.

Majority of respondents (Agricultural Officers) were in medium category with respect to their awareness and knowledge on land evaluation. Majority of respondents had favourable attitude towards land evaluation. There existed significant and positive relation between the dependent variables. Also significant positive and negative relationship existed between some independent and dependent variables.

Analysis of biophysical factors of the watershed revealed that the area was suitable for a wide range of humid tropical crops (both perennial and seasonal). Participatory land evaluation of socio-economic factors revealed that the area was unsuitable for four crops namely pineapple, cocoa, mango and sapota.
Integration of the primary spatial database of biophysical factors using GIS (ARC/INFO package) helped in generating the spatial crop suitability model on 1:10,000 scale with 1508 land mapping units (LMUs). The area of LMUs ranged from 0.201 hectares to 37.411 hectares. Crop suitability recommendation with the help of crop suitability model revealed that as per the S1 class the maximum watershed area can be put under coconut and as per both S2 and S3 classes the maximum area is suitable for rubber. The crop suitability recommendations derived through spatial crop suitability model will help for sustainable agriculture development.

With regard to the use of remote sensing technology, while the aerial photos on 1:15000 scale were found to be very useful for micro watershed level studies, IRS (LISS III) satellite images on 1:50,000 scale only partially supported micro level studies due to the limitation of resolution.

As perceived by the farmers, the spatial crop suitability model will help the planners, farmers and officers of the Department of Agriculture in decision making on the right selection of crops and its management for each locality. The content of participatory land evaluation of socio-economic factors will make the model socially acceptability also. As opined by the respondents the major constraints expected for the utility of the model were lack of political will, fluctuation in market price, untimely supply of inputs, lack of irrigation water, high labour charges and vanishing landlord-labourer relationship.