The feasibility of using canopy temperature (T c ) measured with a hand-operated infrared thermographic camera as a water stress indicator was evaluated in the field during two seasons on citrus and persimmon trees subjected to different levels of deficit irrigation. In both species, which differ in leaf anatomy and stomatal response to environmental conditions, T c was compared with midday stem water potential ( s ) measurements. In persimmon trees, leaf stomatal conductance (g s ) was also measured. T c was the most sensitive indicator of plant water status particularly due to the lower tree-to-tree variability as compared to  s and g s . On the other hand, in citrus trees T c was not always affected by plant water stress. Only in the second experimental season, when air vapour pressure deficit values were below 2.7 kPa and images were also taken from above the canopies, deficit-irrigated trees had higher T c than the control ones, this difference being at most 1.7 ºC. Overall, the results show that hand-operated thermographic cameras can be used to detect plant water stress in both fruit tree species.Nevertheless, the use of T c measurements to detect plant water stress appears to be more precise in persimmon than in orange citrus. This might be because persimmon trees have larger leaf size which determines higher canopy resistance allowing for higher increases in canopy temperature in response to water stress via stomatal closure.3

Evaluating the performance of xanthophyll, chlorophyll and structuresensitive spectral indices to detect water stress in five fruit tree species. Precision Agriculture, 19(1), 178-193.

HighlightLocal root abscisic acid (ABA) accumulation depends on the spatial distribution of soil moisture in potato. Implications for ABA signalling under heterogeneous soil drying are discussed.

Abstract:The present work assessed the usefulness of a set of spectral indices obtained from an unmanned aerial system (UAS) for tracking spatial and temporal variability of nitrogen (N) status as well as for predicting lint yield in a commercial cotton (Gossypium hirsutum L.) farm. Organic, inorganic and a combination of both types of fertilizers were used to provide a range of eight N rates from 0 to 340 kg N ha −1 . Multi-spectral images (reflectance in the blue, green, red, red edge and near infrared bands) were acquired on seven days throughout the season, from 62 to 169 days after sowing (DAS), and data were used to compute structure-and chlorophyll-sensitive vegetation indices (VIs). Above-ground plant biomass was sampled at first flower, first cracked boll and maturity and total plant N concentration (N%) and N uptake determined. Lint yield was determined at harvest and the relationships with the VIs explored. Results showed that differences in plant N% and N uptake between treatments increased as the season progressed. Early in the season, when fertilizer applications can still have an effect on lint yield, the simplified canopy chlorophyll content index (SCCCI) was the index that best explained the variation in N uptake and plant N% between treatments. Around first cracked boll and maturity, the linear regression obtained for the relationships between the VIs and both plant N% and N uptake was statistically significant, with the highest r 2 values obtained at maturity. The normalized difference red edge (NDRE) index, and SCCCI were generally the indices that best distinguished the treatments according to the N uptake and total plant N%. Treatments with the highest N rates (from 307 to 340 kg N ha −1 ) had lower normalized difference vegetation index (NDVI) than treatments with 0 and 130 kg N ha −1 at the first measurement day (62 DAS), suggesting that factors other than fertilization N rate affected plant growth at this early stage of the crop. This fact affected the earliest date at which the structure-sensitive indices NDVI and the visible atmospherically resistant index (VARI) enabled yield prediction (97 DAS). A statistically significant linear regression was obtained for the relationships between SCCCI and NDRE with lint yield at 83 DAS. Overall, this study shows the practicality of using an UAS to monitor the spatial and temporal variability of cotton N status in commercial farms. It also illustrates the challenges of using multi-spectral information for fertilization recommendation in cotton at early stages of the crop.

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Leaf temperature is a physiological trait that can be used for monitoring plant water status. Nowadays, by means of thermography, canopy temperature can be remotely determined. In this sense, it is crucial to automatically process the images. In the present work, a methodology for the automatic analysis of frontal images taken on individual trees was developed. The procedure can be used when cameras take at the same time thermal and visible scenes, so it is not necessary to reference the images. In this way, during the processing in batch, no operator participated. The procedure was developed by means of a non supervised classification of the visible image from which the presence of sky and soil could be detected. In case of existence, a mask was performed for the extraction of intermediate pixels to calculate canopy temperature by means of the thermal image. At the same time, sunlit and shady leaves could be detected and isolated. Thus, the procedure allowed to separately determine canopy temperature either of the more exposed part of the canopy or of the shaded portion. The methodology developed was validated using images taken in several regulated deficit irrigation trials in Persimmon and two citrus cultivars (Clementina de Nules and Navel Lane-Late).Overall, results indicated that similar canopy temperatures were calculated either by means of the automatic process or the manual procedure. The procedure developed allows to drastically reduce the time needed for image analysis also considering that no operator participation was required. This tool will facilitate further investigations in course for assessing the feasibility of thermography for detecting plant water status in woody perennial crops with discontinuous canopies. Preliminary results reported indicate that the type of crop evaluated has an important influence in the results obtained from termographic imagery. Thus, in Persimmon trees there were good 3 correlations between canopy temperature and plant water status while, in Clementina de Nules and Navel Lane-Late citrus cultivars canopy temperature differences among trees could not be related with tree-to-tree variation in plant water status.

To test the hypothesis that root growth at depth is a key trait explaining some genotypic differences in drought tolerance in potato (Solanum tuberosum L.), two varieties (Horizon and Maris Piper) differing in drought tolerance were subjected to different irrigation regimes in pots in a glasshouse and in the field under a polytunnel. In the glasshouse, both cultivars showed similar gas exchange, leaf water potential, leaf xylem ABA concentration and shoot biomass independently of whether plants were grown under well watered or water deficit conditions. Under well watered conditions, root growth was three-fold higher in Horizon compared with Maris Piper, 3 weeks after emergence. Water deficit reduced this difference. In the polytunnel, applying 60% or less irrigation volume compared with full irrigation significantly decreased tuber yield in Maris Piper but not in Horizon. This was coincident with the higher root density of Horizon in deep soil layers (>40 cm), where water content was stable. The results suggest that early vigorous root proliferation may be a useful selection trait for maintaining yield of potato under restricted irrigation or rainfall, because it rapidly secures access to water stored in deep soil layers. Although selecting for vigorous root growth may assist phenotyping screening for drought tolerance, these varieties may require particular environmental or cultural conditions to express root vigour, such as sufficiently deep soils or sufficient water shortly after emergence.