## 4 Results
### Nitrogen Nitrate and Nitrite Content Estimation  
Nitrogen is one of the most important macro nutrients for plants; it directly influences growth, productivity, and development. Nitrogen plays an essential role in the formation of chlorophyll and the synthesis of amino acids, nucleic acids, and proteins in lettuce, spinach, and basil [58]. Nitrogen absorbance is usually in the form of nitrate NO\({}_{3}^{-}\) and ammonium NH\({}_{4}^{+}\). For most agricultural systems, nitrate is a nutrient and a signaling molecule that controls plant growth and metabolism. During the reduction in nitrate to ammonium, nitrite NO\({}_{2}^{-}\) can form, and while the levels are usually low, this compound is important in nitrogen assimilation and metabolic pathways [58]. Once absorbed, nitrate is reduced to nitrite by the enzyme nitrate reductase. Nitrite is then reduced to ammonium by another enzyme called nitrite reductase. Ammonium helps with plant growth by being assimilated into amino acids and protein [58]. This part of the process needs light and temperature because it is energy dependent [58]. The challenge is balancing nitrogen, nitrate, and nitrite to optimize plant growth and health and minimize human consumption risks [59]. Nitrate serves as a storage of nitrogen and supports growth, but too much accumulation of it in leafy greens can be a health concern due to potential conversion into nitrite and nitrosamines in the human body, which have carcinogenic effects [59]. No articles were found for non-destructive nitrite detection in spinach, lettuce, or basil. Also, there are no articles for the estimation of nitrogen and nitrate in basil. As can be seen from Tables 10-14 many methods in the topic of non-destructive nitrogen and nitrate detection reached strong correlations and low error margins, with some reaching R\({}^{2}\) = 0.98 RMSE = 346 [32]. This demonstrates the high level of reliability that is reached for the estimation of those compounds. Such performance suggests that hyperspectral imaging and spectroscopy are not only possible but effective tool for nitrogen and nitrate detection in lettuce and spinach. These techniques have the potential to substitute traditional chemical analysis, which is inherently destructive to the plant. Spectral measurements can offer fa aster and more efficient solution for nutrient monitoring, which can be performed over time on the same plant or leaf.  
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Plant** & **Spectral Range and Instrument** & **Dimensionality Reduction Techniques** & **Accuracy and Technique** & **Number of Samples** & **Ref.** \\ \hline \multirow{3}{*}{Basil} & Hyperspectral camera: & Data dimensionality: Vegetative Indices (ARI, mARI) were calculated from the spectra. & High correlation between VIs (ARI, mARI) and anthocyanins. & \multirow{3}{*}{Not specified} & [19] \\  & 400 nm-1000 nm & ANOVA analysis was used to see the significance of these parameters. & Results: ARI R\({}^{2}\) = 0.82 & & \\ \hline \multirow{3}{*}{Lettuce} & Hyperspectral Camera: & Data dimensionality: Spectral index (ARI) from the HRI & The document does not provide specific accuracy metrics. It discusses the relationships between hyperspectral indices (e.g., CF00, PSRI, and ARI) and physiological indicators of senescence & \multirow{3}{*}{Not specified} & [21] \\ \cline{1-1} \multirow{3}{*}{Lettuce} & Multispectral camera: & Correlation between the most significant VIs and anthocyanin content & & \\  & 475 nm (blue), 560 nm (green), 668 nm (red), & Usage of VIs & BNDT R 0.83 & & \\  & 717 nm (red edge), and 840 nm (NIR). & & GNDVI R 0.81 & & \\ \hline \multirow{6}{*}{Lettuce} & Hyperspectral Camera: & & Model 1 data on