Semantics Analysis of Agricultural Experts’ Opinions for Crop Productivity through Machine Learning

Figures & data

Figure 1. Flow of the system.

Table 1. Questions regarding data collection

Sr.	Questions
1	How does soil health affect crop productivity?
2	What are the impacts of certified and uncertified seed in crop productivity?
3	How can insect pest problem be minimized to increase Agriculture Productivity without harming the Environment?
4	What are impact of plant disease and insects/pest on Crop Productivity?
5	How can we resolve water shortage issues and challenges in Agriculture?
6	How does climate change affect agriculture and farmers?
7	How can precision agriculture be helpful in improving Agriculture and Crop Productivity?
8	What are pros and cons of synthetic fertilizer in Agriculture Sector?
9	How can we improve the post-harvest losses of Crops/Fruits/Vegetables?
10	How Government policies affect in sustainable Agriculture Growth?

Figure 2. Word cloud.

Figure 3. Document comparison.

Figure 4. Uni-Gram.

Figure 5. Bi-Gram.

Figure 6. Tri-Gram.

Table 2. Performance evaluation analysis

Algortithm	Precision	Recall	F1 Score
KNN	85.6	85.8	84.4
Naïve Bayes	90.1	87.0	87.0