Page 60 - Millets Natures NutriGrain

government reports and publications. These sources often reflect
specific governmental perspectives and priorities, which inevitably
influence the findings. To address this limitation, we have made
rigorous efforts to cross-reference data from multiple sources.

3. Temporal Constraints:

The availability of historical data on millet programs may not
encompass the most recent developments or policy changes.

Government policies and agricultural practices can evolve rapidly,
and the data utilized here do not fully capture these dynamic changes.

4. Data Consistency:

Combining data from different sources can sometimes pose
challenges related to consistency. Variations in definitions, metrics,

and reporting standards can complicate the process of data integration
and analysis. Despite our meticulous efforts to harmonize the data,
these inconsistencies can affect the robustness of our findings.

5. Generalizability:

It is important to recognize that the findings of this study, based
on secondary data, are specific to the datasets used and the Indian
context. Extrapolating the results to different regions or agricultural
systems should be done cautiously, as local factors significantly

influence millet production and processing practices.

6. Data Transformation:

As with any research utilizing secondary data, there is the potential

for errors or subjectivity introduced during the data cleaning and
transformation process. We have maintained transparency in our
methodology to minimize these issues.

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