## 2 Materials and Methods
The in-row seed distribution uniformity obtained by computer-aided classification was defined by the values of variation factor (V\({}_{\text{f}}\)) and the goodness criterion (\(\lambda\)). While the Vf value describes how well the data fit a Poisson distribution, the \(\lambda\) value defines the percentage of segments with 1, 2, and 3 seeds or plants. The calculation of the variation factor (V\({}_{\text{f}}\)) and variance (S\({}^{2}\)) of the seed distribution were given below as Equations (1) and (2) given by [20]. In the equations, \(\mu\) is the average number of seeds per segment, x\({}_{\text{i}}\) is the expected number of seeds or plants in the segment, f\({}_{\text{i}}\) is the segment ratio which is the percentage of the segments with different numbers of seeds or plants, and n is the total sample number. \[\text{V}_{\text{f}}=\frac{\text{S}^{2}}{\mu} \tag{1}\]  
\[\text{S}^{2}=\frac{\sum_{\text{i=1}}^{\text{n}}\text{x}_{\text{f}}^{2}\text{ f}_{\text{i}}-\left(\left(\text{x}_{\text{f}}\text{f}_{\text{i}}\right)^{2}/\text{n} \right)}{\text{n}-1} \tag{2}\]  
The seed row spacing pattern was determined based on the \"V\({}_{\text{f}}\)\" values obtained during the experiments. In this definition, if V\({}_{\text{f}}\) > 1.1, it indicates there are undesired misses and multiples within the in-row seed spacing. If 0.9 <V\({}_{\text{f}}\) < 1.1, this indicates the in-row seed spacing matches the Poisson distribution. If V\({}_{\text{f}}\) < 0.9, this indicates the in-row seed spacing may be characterized as precision seeding. The uniformity quality of the in-row seed spacing was determined by a goodness criterion. In this definition, if \(\lambda\) > 72, it indicates the seeding uniformity quality is \"very good\"; if 65 \(\leq\)\(\lambda\) < 72, this indicates the seeding uniformity quality is \"good\"; if 55 \(\leq\)\(\lambda\) < 65, this indicates the seeding uniformity quality is \"moderate\"; and if \(\lambda\) < 55, this indicates the seeding uniformity quality is \"insufficient\". In the goodness criteria evaluation, the average of number of seeds/plants per segment, \(\mu\), was chosen to be \(\mu\) = 2, and the segment length, a, was calculated according to Equation (3) given by the study [18]. \[\text{a}=\frac{100\text{ }\mu\text{ }\sigma}{\text{b N}} \tag{3}\]  
where \(\sigma\) is the thousand-seed mass (g/1000 seeds), b is the row spacing (cm), and N is the seed rate (kg ha\({}^{-1}\)). In the sticky belt experiments, the segment length was calculated to be \(\mu\) = 2. The metering-unit performance in the form of flow uniformity and seed distribution uniformity of the micro-granule applicator were tested based on the three-variable Central \begin{table}
\begin{tabular}{c c} \hline
**CV, \%** & **Evaluation** \\ \hline \textless{}1 & Very good \\
1–2 & Good \\
2–3 & Moderate \\
3–4 & Sufficient \\ \textgreater{}4 & Insufficient \\ \hline \end{tabular}
\end{table} 
Table 2: Qualitative evaluation adjectives corresponding to values of seed flow uniformity. Composite Design (CCD), one of the response-surface methodology designs. Forward speed (X1), seed rate (X2), and seed falling angle (X3) were chosen as independent variables, while variation factor and goodness criteria, which are seed distribution uniformity indices, and also flow uniformity were considered as dependent variables. The seed falling angle is the angle that the seed tube axis makes with the vertical plane. Three-variable CCD requires five levels for each independent variable. These levels were coded as \(\pm\)1.682 (star points), \(\pm\)1, and 0 (center point) [21]. A list of independent variables, and their coded and uncoded factor levels, can be seen in Table 3. The metering unit was operated at five forward speeds, five seed rates, and five seed falling angles for seeding of sage seeds. The experiments were conducted based on the CCD experimental design principles having three replications for determining flow uniformity and seed distribution uniformity.