Crop nitrogen (N) status is a desirable information for crop nutrition management. In addition to the traditional leaf sampling with subsequent laboratory analysis, the use of chlorophyll meters is a well-studied and accepted practice to indirectly measure crop N status. Nevertheless, chlorophyll meters are dedicated devices that still cost at least a few hundred dollars, thus being unsuitable to large scale use among low budget smallholders. Aiming to address this issue, a new low cost smartphone camera adapter device was developed to measure green color intensity levels of leaves. The adapter consists of a conical casing, having side walls allowing diffuse light to enter. An opening at the top receives the lens of the smartphone camera and at the bottom inside the cone there is a plate, providing a pattern of predefined color references and an opening to allow the sample leaf to be introduced and seen from the top. To evaluate this device, a replicated maize pot experiment, with five N levels and all other nutrients at adequate amounts, was established. At crop growth stages V6 and V8, all plants have been evaluated by measuring the middle-blade of the last fully developed leaf with a reference chlorophyll meter and the smartphone camera adapter device. The collected images were batch processed for identifying the reference color scale and the leaf on the images, labeling them and extracting the “RGB” values for the reference and the leaf. The readings were transformed into the “L, a, b” color space, and the “Color  distance” between reference levels and sample leaves was calculated. A quadratic equation was fitted to derive the point of minimum “color distance” between sample leaf and reference. To compare data from the chlorophyll meter and the adapter device, univariate regression analysis have been used and root mean square errors (RMSE) were calculated. In a second evaluation step, three leaves, coming from distinct N levels, were measured with the adapter device, using the cameras of nine different smartphones to evaluate whether there is any dependency of the procedure against different camera devices. The comparison between the values of the chlorophyll meter and the adapter device shows an R² of >0.8 and a RMSE  of  <40 chlorophyll meter units. The measurements made with the different smartphone cameras indicated that the suggested method is largely independent from camera type. In conclusion, the  results show that the low cost adapter device could be a suitable alternative to more expensive chlorophyll meters for the estimation of crop N status in smallholder cropping systems.