EXPERIMENTS ON CULTIVATOR S FIELD

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1 EXPERIMENTS ON CULTIVATOR S FIELD N.K.Sharma and P.K. Batra I.A.S.R.I., library Avenue, New Delhi Agricultural research has traditionally been undertaken at research stations where facilities of experimentation are excellent and accessibility to researchers is favorable. Any conclusions based on the results of a group of experiments at research stations cannot be immediately recommended for general adoption under actual farming conditions. This may primarily be due to (i) The number of experimental station are small, (ii) The fertility of soil and the level of management at research stations are superior to those in cultivator s field. Before any promising result obtained by the detailed investigations at agricultural research stations is given to extension workers for adoption by the farming community, it is necessary to test these results under farming conditions. An experimental programme with this objective must be spread over an adequate and representative sample of farmers field and carried out with their participation and assistance. Since the sample of fields selected randomly, it will include major proportion of fields belonging to farmers with limited means and small holdings. The experiments to be laid out must satisfy the following conditions: (1) The experiments should be simple and consist of a small number of treatments say 3 to 6. () The only promising treatments as judged from the past research at experimental station should be taken. (3) The set of treatments in each experiment should have demonstration value. Each set should therefore be self contained in the sense that easily intelligible comparisons of practical value can be made from the experiment. Further all comparisons should be available with farmer normal practice as control. These requirements impose certain restriction on the experimental design to be adopted. Full factorial set of treatments involving 3 or more factors can not be tried as number of treatments becomes large. Ordinary confounding will, however, not be satisfactory for this purpose, as each group of treatments must provide a self-contained demonstration. In the interest of simplicity and on account of small size of fields, any replications with in field will not be advisable or practicable. A fairly extensive programme on cultivators fields based on these principles is in operation in India under the All India Co-ordinated research project on cropping system research (AICRP on CSR). The project is located at Project Directorate of Cropping System research, Modipuram. Planning of Trials As a first step it is necessary to define the area where trials are proposed to be taken. Presently country has been divided into different agroclimatic zones and it would thus be appropriate to develop the technology for these zones separately.

2 Once the target area is selected the methodology adopted for selection of sites where proposed trials are to be carried out involves the combinations of some basic techniques of experimental designs and sample survey. A multistage random sampling design is usually suggested for the selection of ultimate sites where proposed trials are to be conducted. For a given agroclimatic zone, a random sample of few development blocks, out of the totality of blocks in the zone constituting the jurisdiction of researcher is selected in the first stage. From the selected block a random sample of few villages will be selected in the second stage. In the third stage out of the totality of cultivators in each of the selected villages a random sample of few cultivators will be selected. If necessary fields can be selected within cultivators as fourth stage. An unreplicated trial will be carried out at the selected field. An appropriate sample size of these units must be ensured at each stage to get valid estimate of error for different comparisons. The statistical considerations for designing and analysis of experiments on cultivator s fields have been discussed in detail by various research workers like Panse and Sukhatme (1955), Uttam Chand and Abraham (1958), Yates (1959), Panse and Abraham (1960), Narain and Jha (1965) and Jha (1965). In view of the practical difficulty involved in the conduct of experimental programme on cultivator s fields, designs suitable for this type of experimental programme themselves from a class of designs. A design which might appeal to the cultivator would be to divide his field into as many portions as there are treatments, apply the treatments over the whole of each of these portions and harvest plots of given dimensions at harvest time in the presence of experimenter. Thus with an experiment with five treatments a field would be divided into five approximately equal portions. In one portion, crop would be grown according to the cultivator s normal practice and would act as a control treatment for the experiment. In other four portions of the field, the experimenter dressing would be superimposed on cultivator s normal practice viz. Control. Thus, the idea underlying the design would be that the whole field would be cultivated, seeded etc. by cultivator in usual way, but four suitable portions of a given area would have experimental treatments superimposed on the normal. At the time of harvest the plot of given dimension would be marked in random position within different portions and produce from these plots would be weighed and recorded. The above procedure is open to obvious objections on statistical grounds: No replication Non-use of principle of local control in eliminating fertility variation from treatment comparison. Experimental plots for harvest are not contiguous or of a shape considered advantageous in a field experiment at research station. 594

3 Analysis The analysis of variance of plot yields of a group of experiments involving t treatments at n places with m fields per place is as given in Table 1 Table 1: ANOVA Source df MS E( MS) Treatment t-1.. Places n-1.. Fields within places(blocks) n(m-1).. Places x treatments (n-1)(t-1) s b σ e + σ m Blocks x treatments n(m-1)(t-1) s w σ e The Error Variance per plot of a treatment response will consist of two parts: (1) The Error Variance per plot at a place (σ e ) and () the variance due to interaction of response with places. Thus, the variance of average treatment response is given by: V= ( mσ m + σ e ) / mn Technological Verification Trials The primary objectives of technological verification trial is to compare the performance of the farmers technology and new technology in the farmer s field. A technological verification trial has following distinguishing feature : Farmer field as a test side. Farmer practice as a basis of comparison Farmer practice as the level of management for growing the experimental crop. Selection of Test farms : The test farms for technology verification trials should adequately represent t the farm in target area. Target Area The target area is defined by one or more specific environmental component (Physical, biological, Social and Economic) that are considered critical to the superior performance and eventually adoption of the new technology. Sampling plan The test farm should be the representative of the target area and adequate number of test farm (sample size) must be selected following a valid sampling technique. Experimental design A technological verification trial with k test factors can be viewed as k factorial experiment, two levels of each factor represents the level prescribed in the new technology and level of farmer s practice. For example consider a case where existing farmer practice is to grow rice in kharif season followed by maize in rabi season, new technology consist of same cropping pattern but with different variety, fertilizer rate, weed control, and insect control for rice and different 595

4 insect control and level of field preparation for maize. This new technology differ from existing farmer practice in six test factors (k = 6). Thus technological verification trials is a 6 factorial experiment. Gomez and Gomez (1976) have suggested the following three set of treatments for such type of trials. (i) Set X, consisting of two treatments: the new technology (the test factors are all at new technology level) and farmer practice (The test factors are all at farmer s level). (ii) Set Y, consisting of (k+) treatments: Two treatments of set x plus k unreplicated treatments each of which represents a treatment combination in which all test factors but one are at the new technology level. (iii) The set Z consists of each k complete factorial treatment combination or an appropriate fractional factorial set. Example: The three set of treatments X,Y and Z associated with technological verification trial in Rice three factors : Fertilizer(F), insect control (I), and weed control (W). Treatment number Factor level a Treatments Set Z F I W Set X Set Y Complete fractional b factorial factorial 1 n n n * * * - f n n - * * * 3 n f n - * * * 4 n n f - * * * 5 f f n - - * - 6 f n f - - * - 7 n f f - - * - 8 f f f * * * * a: n: Level of new technology, f: Farmer s level b: 1/( 4 ) fractional factorial Because number of treatments is smallest in set X and largest in set Z the number of farms (n x ) testing the X set of treatments is largest followed by the number of farms testing Y set of treatments. The size of n z is dependent upon the degree of importance of the interaction effects. The proportion of n x : n y : n z commonly used for technology verification trials 3:1:1. References 596

5 Gomez, A.K. and Gomez, A.A. (1976) Statistical procedures for agricultural research. International Rice Research Institute Book, John Willy & Sons. Panse,V.G. and Abraham, T.P. (1960). Simple scientific experiments in farmers fields. Proceeding of the 31st Session of the International Statistical Institute. Panse,V.G. and Sukhatme, P.V.(1955). Statistical Method for Agricultural Workers. Uttam Chand and Abraham, T.P. (1957). Some considerations in the planning and analysis of fertilizer experiments in cultivators fields. Jour. of the Indian Soc. of Agric. Statistics. Yates et al (1959). An exploratory analysis of a large set of 3 x 3 x 3 fertilizer trials in India. Emp. Jour. of Exptl. Agric. 7,