Nitrogen concentration in plants is normally determined by expensive and time consuming chemical analyses. As an alternative, chlorophyll meter readings and N-NO₃ concentration determination in petiole sap were proposed, but these assays are not always satisfactory. Spectral reflectance values of tomato leaves obtained by visible-near infrared spectrophotometry are reported to be a powerful tool for the diagnosis of plant nutritional status. The aim of the study was to evaluate the possibility and the accuracy of the estimation of tomato leaf nitrogen concentration performed through a rapid, portable and non-destructive system, in comparison with chemical standard analyses, chlorophyll meter readings and N-NO₃ concentration in petiole sap. Mean reflectance leaf values were compared to each reference chemical value by partial least squares chemometric multivariate methods. The correlation between predicted values from spectral reflectance analysis and the observed chemical values showed in the independent test highly significant correlation coefficient (r = 0.94). The utilization of the proposed system, increasing efficiency, allows better knowledge of nutritional status of tomato plants, with more detailed and sharp information and on wider areas. More detailed information both in space and time is an essential tool to increase and stabilize crop quality levels and to optimize the nutrient use efficiency.

Evaluation of crop N status will assist optimal N management of intensive vegetable production. Simple procedures for monitoring crop N status such as petiole sap [NO₃⁻–N], leaf N content and soil solution [NO₃⁻] were evaluated with indeterminate tomato and muskmelon. Their sensitivity to assess crop N status throughout each crop was evaluated using linear regression analysis against nitrogen nutrition index (NNI) and crop N content. NNI is the ratio between the actual and the critical crop N contents (critical N content is the minimum N content necessary to achieve maximum growth), and is an established indicator of crop N status. Nutrient solutions with four different N concentrations (treatments N1–N4) were applied throughout each crop. Average applied N concentrations were 1, 5, 13 and 22 mmol L⁻¹ in tomato, and 2, 7, 13 and 21 mmol L⁻¹ in muskmelon. Respective rates of N were 23, 147, 421 and 672 kg N ha⁻¹ in tomato, and 28, 124, 245 and 380 kg N ha⁻¹ in muskmelon. For each N treatment in each crop, petiole sap [NO₃⁻–N] was relatively constant throughout the crop. During both crops, there were very significant (P < 0.001) linear relationships between both petiole sap [NO₃⁻–N] and leaf N content with NNI and with crop N content. In indeterminate tomato, petiole sap [NO₃⁻–N] was very strongly linearly related to NNI (R² = 0.88–0.95, P < 0.001) with very similar slope and intercept values on all dates. Very similar relationships were obtained from published data of processing tomato. A single linear regression (R² = 0.77, P < 0.001) described the relationship between sap [NO₃⁻–N] and NNI for both indeterminate and processing tomato, each grown under very different conditions. A single sap [NO₃⁻–N] sufficiency value of 1050 mg N L⁻¹ was subsequently derived for optimal crop N nutrition (at NNI = 1) of tomato grown under different conditions. In muskmelon, petiole sap [NO₃⁻–N] was strongly linearly related to NNI (R² = 0.75 – 0.88, P < 0.001) with very similar slope and intercept values for much of the crop (44–72 DAT, days after transplanting). A single linear relationship between sap [NO₃⁻–N] and NNI (R² = 0.77, P < 0.001) was derived for this period, but sap sufficiency values could not be derived for muskmelon as NNI values were >1. Relationships between petiole sap [NO₃⁻–N] with crop N content, and leaf N content with both NNI and crop N content had variable slopes and intercept values during the indeterminate tomato and the muskmelon crops. Soil solution [NO₃⁻] in the root zone was not a sensitive indicator of crop N status. Of the three systems examined for monitoring crop/soil N status, petiole sap [NO₃⁻–N] is suggested to be the most useful because of its sensitivity to crop N status and because it can be rapidly analysed on the farm.