The color distortion effect and its correction using the method presented in this paper.

<p>(a) original image of a young and green leaf; (b) the corresponding color profile at the cross-section indicated by the arrow in (a); (c) image of the same leaf after color distortion correction; (d) corresponding color profile at the exact same cross-section.</p

Two examples of senescence patterns.

<p>(a) and (b) depict similar sized leaf areas of the same plant on different days; in (b) the plant has grown a little larger. Figs (c) and (d) show the same plant (different from (a) and (b)) on different days but at a much later stage of development when more leaves have become senescent and after some senescent leaves have fallen off.</p

Scatter plots of manual inspection scores versus the objectively estimated senescence measure proposed in this paper and that of the machine learning method adapted by the LemnaTec system for a set of chickpea plants.

<p>Manual scoring was performed on two occasions: 2 days after the last imaging day (top panel) and 3 days after the last imaging day (bottom panel).</p

Evaluation of the performance of our senescence analysis algorithm as applied to chickpea images.

<p>Evaluation of the performance of our senescence analysis algorithm as applied to chickpea images.</p

Comparison of senescence estimations using the method proposed here (curves denoted Overall, Mid and Bottom) and a direct application of the color analysis software provided by The Plant Accelerator’s LemnaTec imaging system.

<p>For the Lemnatec results, only a whole-of-plant measure is available with which we compare a corresponding measure, which in turn is broken down into the senescence levels determined in the bottom and middle zones.</p

Zonal assessment of green versus senescence leaf areas in pixels.

<p>Top figures show original images of three Gladius plants each grown under a different level of nitrogen (N1, N3 and N5). The bottom figures show the results of color classification in pixel area as a function of zone, according to our four-category color scheme: dark green, light green, yellow and brown.</p

Example results at the end of each step in the process of ground-truth color estimation.

<p>In sequence: (a) the original image of a young plant; (b) the automatically segmented plant leaves with manual correction; (c) the automatically segmented frame with manual correction; and (d) the estimated image of the young plant after color distortion correction.</p

Results of application of the color correction process on plants exhibiting senescence.

<p>(a) shows the original image, while (b) shows the post processed, restored image. Panels (c) and (e) are enlarged regions of the original image in (a), while (d) and (f) are corresponding enlarged regions of the restored image (b).</p

Whole-of-plant assessment of growth (plant area) and senescence as a function of time for two individual chickpea plants.

<p>Top figure shows the time developments of total projected plant area (all leaves and stems) for the two plants, depicting qualitatively similar but quantitatively different growth behavior. Bottom figure shows the percentage of senescence present in the leaves of these plants relative to their total plant area. The two individual plants exhibit different rates of senescence development.</p

Summary of senescence dependence on nitrogen treatment (<i>N</i>1 − <i>N</i>5, horizontal axis) for the Gladius wheat plant variety.

<p>Shown are mean values of onset determination (days after sowing, DAS, dashed curve and solid triangles, left vertical axis) and final degree of senescence (percentage of total project leaf area, solid curve and open diamonds, right vertical axis). Error bars show the variation across three repeats.</p