It is a very good question. First, if your agricultural experiment was conducted with the usual standards (influence factors and explained variable, trial repetitions) you can develop some interesting statistics and in this case the non significant results mean that you can not explain your variable with the selected factors of influence. Otherwise, i.e if the agricultural experiment was not conducted in a proper way (errors or lack in data, insufficiency of the repetitions) the non significant results can not lead to pertinent conclusions so that the influence factors can still explain a natural phenomenon or the aimed variable.

If the results are not significantly different due to the application of the experiment in the field of agriculture and repeated more than once, it means that the factors studied are not worthy of attention, which in any case represents an important result to be taken into account in the future, but if the experiment was once, it may be due to the occurrence Errors in the application of experimental factors or errors in analyzes and measurements or errors in the analysis of statistics

A non significant result for an effect can be the result of imprecision in the experiment and is called a false negative if the nonsignificance is not real but the result of poor scientific rigor. Even in a well done experiment it is hard to prove something does not exist. In fact science evaluators rarely find much favor for nonsignificant results. Significance can be found when more replications are used and the scientific methodology is improved or the experiments are run for longer terms. Agricultural results are plagued by field variability and this can be addressed by looking for more uniform fields. Blocking of experiments is one method to minimize the effect of variability in the conducting and analysis of experiment.

a non significant difference is a result that is statistically not meaningfull. This means it can have happened by accident. Usually there are two reasons that your results are not significant. Nr1, there is two much variation in the evironmental and fix factors (e.g. soil, field cultivarion, cover sprays, uneven damage of pest/diseases). Nr2, the design of the experiment was not powerful enough, for example not enough replications, two little variation of the experimental factor (e.g. 100% and 90% application rate of a pesticide). Keep also the capablities of your statistics in mind.

As others said, you must repeat the experiment and see the result. you may still find it insignificant. then you have to analyse it. specially see the relationships between factors. try to understand why it became insignificant. probably other factors may have positive or negative effect on. then try your research under different conditions. probably with more factors that could amplify the main factor effect, or controlling factors that hinder the main factor effect.

If the result is not significant, the experiment needs to be repeated at different locations with in different seasons

Thanks Senesie Swaray

Thanks all for your important responses

That the two factors are independent and not influenced by each other. Need to move-on and not waste time in repeated attempts.

Thanks Emmanuel Vijayanand Murray!!!

Dear Dejene

You asked a general question without giving details of the experiment - its objectives and experimental design. Several comments have been made rightly that flaws in experimental design including inadequate replications and inadequate repetition of the experiment may produce such results. Moreover, the a priori hypothesis might be misleading if factors unlikely to be of significance in explaining variation in the dependent variable were included in the design. Statistical interpretation of non-significance based on proper design is that the factor(s) -major or minor- was not a source of variation in the dependent variable. Such factor(s) could be left out of the experiment if there was enough prior knowledge from theory and empirical evidence that such factor would not make a difference.

Hope this is useful

Mohammad

Thanks Mohammad!

Dear Dejene

The implication of the non significant results depends on your experimentation hypotheses. For example, you experiment is to prove or disapprove the hypothesis that a herbicide in use cause significant loses to your crop stand, the alternative hypothesis is it does not cause significant loss to your crop stand. You two to three years experimentation results, which found that there is no significant difference in crop stand where you applied the herbicides and where there is no application of the that herbicide implies that herbicide is not the cause of observed loses in your crop stand, which means you have to accept alternative hypothesis, which disapprove the believe that the herbicide is the cause. This means both significant and non significant results informs the researchers decision of the recommendation to be made.