Yield gap analysis of rice cultivation in Kanyakumari district

Introduction

India's food grain output since the 1960s has grown significantly as a result of expanding arable land, large-scale cultivation of high-yielding semi-dwarf varieties, and increasing use of pesticides, fertilizers, and irrigation. India has achieved gross food security during the past three decades as a result of increased food production. However, the growing population in India, is posing a threat to food security. India's population is predicted to increase from its current 1.1 billion to 1.6 billion by 2050. This suggests a higher demand for food. To meet the estimated future demand, agricultural production must be enhanced in an environmentally sustainable manner in the context of increasing competition for water, land and labour, as well as the constantly evolving threat from abiotic and biotic stresses, and under potentially more extreme weather conditions associated with climate change. Despite the fact that there may be enough food for everyone, socioeconomic and political forces would demand for production locally. As there is little scope for easy expansion of agricultural land or irrigation, reducing the 'yield gap has to be accomplished to meet the demand. This study is about the yield gap analysis of different paddy variants and to find out the reasons for less productivity in rice in Kanyakumari district.

Methodology

Yield gap analysis is a method for estimating the difference between the potential yield of paddy and the average yield achieved on farms. It can help identify the factors that limit yield and improve food production. 'Yield gap', is defined as the difference between potential yield and average onfarm yield obtained by farmers (Saito et al., 2013; van Ittersum et al., 2013) [6,4] . 'Potential yield' is defined as the maximum yield that can be obtained from a crop in a given environment as often determined by crop simulation models with plausible physiological and agronomic assumptions (Evansand Fischer, 1999) [2] . Under irrigated conditions, potential yield is determined by climate (solar radiation and temperature), varietal characteristics and crop establishment methods, including sowing date and density. The yield gap analysis is carried out in two broad categories, focusing on 1. Quantification of yield gaps and 2. Identification of causes for the yield gaps.

Quantification of yield gaps

Quantification of yield is the first step that was carried out to record the yield of different varieties in rice. Then the areas of higher rice yield is identified and the climatic conduction of the areas are assessed. The first step was to identify areas where large increases in rice yield can be achieved and to quantify yield and yield gap. Furthermore, spatially explicit yield gaps and to assess the reasons for major yield gaps suggest interventions for higher yields. The existing productivity gap is conceptualized as the difference between the highest potential yield that can be obtained in farmers field and the actual farm yield obtained. The yield gap might be due to lag in transfer of technology to farmers and deficiencies in adoption of various technologies by the farmers i.e. inter farm difference in application of technologies. The yield gap exists mainly due to biological and socio-economic constraints.

Computation of yield gaps

International Rice Research Institute method of yield gap analysis was employed. Computation of yield gaps Yield gap was estimated using the methodology developed by the International Rice Research Institute, Manila, Philippines. Various yield gaps were estimated using the following formula The average paddy yield will be calculated by taking the average of the actual yield recorded in rice fields and the yield gap was calculated.

Extension Gap= Demonstration Yield -Farmers yield

Selection of the study area

The present study will be undertaken for TPS 5 rice variety in Kanyakumari district of Tamil Nadu. In Kanyakumari district paddy is grown in all the blocks. From among the eight blocks four blocks with maximum area under rice cultivation were selected and proportionate random sampling method was used for selection of respondents. The blocks identified were Thovalai, Rajakamangalam, Agastheeswaram and Kurunthancodu blocks. From these blocks farmers has been identified with proportionate sampling method.

Sampling Design

A total of 128 paddy farmers were selected by proportionate random sampling. A well-structured interview schedule was used for collecting data. Potential yield, actual yield obtained were recorded. Suitable statistical tools were utilized for analysis.

Data collection

The study was based upon both primary and secondary data gathered during the course of investigation.

Data collection Tool

A pretested interview schedule was used for collecting the required data from the sample farmers

Results and discussion

Though the production level of rice has increased, there still exists a gap between what is achieved and what actually could be achieved in farmers' fields through interventions. It is therefore needed that an attempt is made to analyse the magnitude of the gaps in attainable yields and to explore the possibilities of relaxing existing constraints in order to reduce the yield gaps and to assess the efficiency levels of farmers resource use. In other varieties the area grown was lesser and potential yield was low. There is vast scope for increasing the potential yield by improved production technologies in these major ruling varieties which has recorded higher yield. A stable high potential yield was observed in TPS 5 variety. The Technological index (TI) of TPS 5 rice cultivation was found to be 2.44% which is a very low "technology gap". This implies better performance of the variety in the field and this variety is more suitable to the climatic condition and crop management practices of the farmers. The performance of TPS 5 variety indicates that it is best suited for the climatic conditions in the district and can be upscaled The demonstration yield of rice TPS 5 in the district was 3480 kg/ac and average yield was 2408kg/ac. An Extension Gap of (1072kg/ ac) was 2.68 t/ha which means that this variety yielded 2.68 t/ha higher than the average yield obtained by farmers. Yield Gap index (YGI) of TPS 5 variety was 31.84% which means that there was more scope for achieving untapped potential yield through improved production technologies to obtain an additional yield of 772kg/ac. (1.9t/ha).

Factors influencing yield gap in rice cultivation

Socio-economic factors are crucial for limiting access to technology, farmers' income levels, and credit availability that impact farmers' ability to implement improved technologies. Analysis was done for finding out the relationship between the factors that impact yield gap and the results are presented below.

Multiple linear regression

The backward stepwise method is used to produce an initial screening of the predictors. The multiple linear regression analysis shows that Experience and Annual income are significant @0.05% level of significance This can be interpreted that every unit increase in X6 (Annual Income) limits the yield gap. This means that increase in annual income reduces yield gap index. Annual income has impacted yield gap index of individuals. Similarly for increase in experience there is decrease in yield gap index. The analysis interprets that for higher socio-economic status combined with age and experience has reduced yield gap in rice. Transplanting can be recommended to prevent yield loss due to direct seeded rice cultivation and suitable package of practice can be suggested for slushy field or swampy/marshy wetland conditions. ASD 16 with highest yield gap and has to be replaced with new varieties. TPS 5 variety with Technological index (TI) and Extension gap can be upscaled to flood prone areas due to its non-lodging feature.

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