## 3 Bibliometric Assessment
### Bibliographic Data
#### 3.2.2 Bibliographic Coupling Links  
The United States, China, Australia, India, the United Kingdom, Germany, Italy, France, The Netherlands and Kenya are among the countries with the highest total link strength for the topics addressed (Figure 3 and Table 3). These countries of affiliation for the researchers reveal the concerns of the scientific community with some specific contexts, such as China and India (considering their population), for example, because of the risks of food insecurity, and where machine learning and agricultural planning may bring relevant contributions. Another context that deserves special attention is Brazil where, despite the technological advances in agriculture and this country being one of the biggest producers of grain, the problems with food insecurity remain, calling for more adjusted policies. In general, the countries with the greatest total link strength have also a high number of documents, citations and normalized citations. The correlations among the total link strength and the average citations and the average normalized citations are not so evident. The average publication year for the top 20 countries ranges between 2019 and 2021. The top five organizations with the greatest relatedness are the following (Figure 4 and Table 4): the University of the Chinese Academy of Sciences, Beijing, China; Agri-Science Queensland, Department of Agriculture & Fisheries (DAF), Warwick, Australia; Bayer Crop Science, United States; the Center for Soybean Research of The State Key Laboratory of Agrobiotechnology and School of Life Sciences, the Chinese University of Hong Kong, Shatin, Hong Kong; and the Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India. The information presented in Figure 4 and Table 4 (and the remaining output from the VOSviewer software) highlight the interest of institutions and the scientific communities in countries, such as China and India, in topics related to food security and machine learning. In this case, the correlations between the total link strength and the other metrics, for the full information, are not so obvious. \begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**All Keywords**} & **Total Link Strength** & \multirow{2}{*}{**Occurrences**} & \multicolumn{2}{c}{**Average Publication Year**} & \multirow{2}{*}{\
\begin{tabular}{c} **Average** \\ **Citations** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Normalized** \\ **Citations** \\ \end{tabular} } \\ \hline machine learning & 4291 & 332 & 2020 & 19 & 1 \\ food supply & 3810 & 249 & 2020 & 15 & 1 \\ food security & 2325 & 186 & 2020 & 15 & 1 \\ crops & 2041 & 126 & 2020 & 13 & 1 \\ remote sensing & 1738 & 113 & 2020 & 17 & 1 \\ decision trees & 1621 & 91 & 2021 & 15 & 1 \\ learning systems & 1505 & 93 & 2020 & 22 & 1 \\ agriculture & 1145 & 73 & 2020 & 20 & 1 \\ climate change & 1041 & 65 & 2020 & 15 & 1 \\ forecasting & 1011 & 63 & 2021 & 12 & 1 \\ deep learning & 994 & 77 & 2021 & 38 & 1 \\ crop yield & 976 & 69 & 2020 & 24 & 2 \\ agricultural robots & 811 & 52 & 2021 & 10 & 1 \\ random forests & 780 & 45 & 2021 & 18 & 1 \\ algorithm & 755 & 42 & 2020 & 21 & 1 \\ mapping & 737 & 42 & 2020 & 19 & 2 \\ learning algorithms & 724 & 49 & 2020 & 13 & 1 \\ support vector machines & 686 & 39 & 2020 & 15 & 1 \\ artificial intelligence & 664 & 40 & 2019 & 23 & 1 \\ satellite imagery & 631 & 40 & 2020 & 22 & 1 \\ \hline \end{tabular}
\end{table} 
Table 2: Top 20 all keywords with the highest total link strength for bibliographic data, considering full counting and 1 as the minimum number of occurrences of a keyword.