High-throughput characterization and phenotyping of resistance and tolerance to virus infection in sweetpotato.

Breeders have made important efforts to develop genotypes able to resist virus attacks in sweetpotato, a major crop providing food security and poverty alleviation to smallholder farmers in many regions of Sub-Saharan Africa, Asia and Latin America. However, a lack of accurate objective quantitative methods for this selection target in sweetpotato prevents a consistent and extensive assessment of large breeding populations. In this study, an approach to characterize and classify resistance in sweetpotato was established by assessing total yield loss and virus load after the infection of the three most common viruses (SPFMV, SPCSV, SPLCV). Twelve sweetpotato genotypes with contrasting reactions to virus infection were grown in the field under three different treatments: pre-infected by the three viruses, un-infected and protected from re-infection, and un-infected but exposed to natural infection. Virus loads were assessed using ELISA, (RT-)qPCR, and loop-mediated isothermal amplification (LAMP) methods, and also through multispectral reflectance and canopy temperature collected using an unmanned aerial vehicle. Total yield reduction compared to control and the arithmetic sum of (RT-)qPCR relative expression ratios were used to classify genotypes into four categories: resistant, tolerant, susceptible, and sensitives. Using 14 remote sensing predictors, machine learning algorithms were trained to classify all plots under the said categories. The study found that remotely sensed predictors were effective in discriminating the different virus response categories. The results suggest that using machine learning and remotely sensed data, further complemented by fast and sensitive LAMP assays to confirm results of predicted classifications could be used as a high throughput approach to support virus resistance phenotyping in sweetpotato breeding.

Active and passive chlorophyll fluorescence measurements at canopy level on potato crops. Evidence of similitude of diurnal cycles of apparent fluorescence yields.

We performed active and passive measurements of diurnal cycles of chlorophyll fluorescence on potato crops at canopy level in outdoors conditions for 26 days. Active measurements of the stationary fluorescence yield (Fs) were performed using Ledflex, a fluorescence micro-LIDAR described in Moya et al. (Photosynth Res 142:1-15, 2019), capable of remote measurements of chlorophyll fluorescence under full sun-light in the wavelength range from 650 to 800 nm. Passive measurements of solar-induced fluorescence (SIF) fluxes were performed with Spectroflex, an instrument based on the method of filling-in in the O2A and O2B absorption bands at 760 nm (F760) and 687 nm (F687), respectively.Diurnal cycles of Fs showed significant variations throughout the day, directly attributed to changes in photosystem II yield. Contrasting patterns were observed according to illumination conditions. Under cloudy sky, Fs varied in parallel with photosynthetically active radiation (PAR). By contrast, during clear sky days, the diurnal cycle of Fs showed a "M" shape pattern with a minimum around noon.F687 and F760 showed different patterns, according to illumination conditions. Under low irradiance associated with cloudy conditions, F687 and F760 followed similar diurnal patterns, in parallel with PAR. Under high irradiance associated with clear sky we observed an increase of the F760/F687 ratio, which we attributed to the contributions in the 760 nm emission of photosystem I fluorescence from deeper layers of the leaves, on one end, and by the decrease of 687 nm emission as a result of red fluorescence re-absorption, on the other end.We defined an approach to derive a proxy of fluorescence yield (FYSIF) from SIF measurements as a linear combination of F687 and F760 normalized by vegetation radiance, where the coefficients of the linear combination were derived from the spectral transmittance of Ledflex. We demonstrated a close relationship between diurnal cycles of FYSIF and Fs, which outperformed other approaches based on normalization by incident light.

Active in situ and passive airborne fluorescence measurements for water stress detection on a fescue field.

Ledflex is a fluorometer adapted to measure chlorophyll fluorescence at the canopy level. It has been described in detail by Moya et al. (2019), Photosynthesis Research. https://doi.org/10.1007/s11120-019-00642-9 . We used this instrument to determine the effect of water stress on the fluorescence of a fescue field under extreme temperature and light conditions through a 12 days campaign during summer in a Mediterranean area. The fescue field formed part of a lysimeter station in "las Tiesas," near Albacete-Spain. In addition to the fluorescence data, the surface temperature was measured using infrared radiometers. Furthermore, "Airflex," a passive fluorometer measuring the filling-in of the atmospheric oxygen absorption band at 760 nm, was installed in an ultralight plane and flown during the most critical days of the campaign. We observed with the Ledflex fluorometer a considerable decrease of about 53% of the stationary chlorophyll fluorescence level at noon under water stress, which was well correlated with the surface temperature difference between the stressed and control plots. Airflex data also showed a decrease in far-red solar-induced fluorescence upon water stress in agreement with surface temperature data and active fluorescence measurements after correction for PS I contribution. Notwithstanding, the results from airborne remote sensing are not as precise as in situ active data.

Radiation Interception, Conversion and Partitioning Efficiency in Potato Landraces: How Far Are We from the Optimum?

Crop efficiencies associated with intercepted radiation, conversion into biomass and allocation to edible organs are essential for yield improvement strategies that would enhance genetic properties to maximize carbon gain without increasing crop inputs. The production of 20 potato landraces-never studied before-was analyzed for radiation interception ( ε i ), conversion ( ε c ) and partitioning ( ε p ) efficiencies. Additionally, other physiological traits related to senescence delay (normalized difference vegetation index (NDVI) s l p ), tuberization precocity ( t u ), photosynthetic performance and dry tuber yield per plant (TY) were also assessed. Vegetation reflectance was remotely acquired and the efficiencies estimated through a process-based model parameterized by a time-series of airborne imageries. The combination of ε i and ε c , closely associated with an early tuber maturity and a NDVI s l p explained 39% of the variability grouping the most productive genotypes. TY was closely correlated to senescence delay (r P e a r s o n = 0.74), indicating the usefulness of remote sensing methods for potato yield diversity characterization. About 89% of TY was explained by the first three principal components, associated mainly to t u , ε c and ε i , respectively. When comparing potato with other major crops, its ε p is very close to the theoretical maximum. These findings suggest that there is room for improving ε i and ε c to enhance potato production.

Development of an Open-Source Thermal Image Processing Software for Improving Irrigation Management in Potato Crops (Solanum tuberosum L.).

Accurate determination of plant water status is mandatory to optimize irrigation scheduling and thus maximize yield. Infrared thermography (IRT) can be used as a proxy for detecting stomatal closure as a measure of plant water stress. In this study, an open-source software (Thermal Image Processor (TIPCIP)) that includes image processing techniques such as thermal-visible image segmentation and morphological operations was developed to estimate the crop water stress index (CWSI) in potato crops. Results were compared to the CWSI derived from thermocouples where a high correlation was found ( r P e a r s o n = 0.84). To evaluate the effectiveness of the software, two experiments were implemented. TIPCIP-based canopy temperature was used to estimate CWSI throughout the growing season, in a humid environment. Two treatments with different irrigation timings were established based on CWSI thresholds: 0.4 (T2) and 0.7 (T3), and compared against a control (T1, irrigated when soil moisture achieved 70% of field capacity). As a result, T2 showed no significant reduction in fresh tuber yield (34.5 ± 3.72 and 44.3 ± 2.66 t ha - 1 ), allowing a total water saving of 341.6 ± 63.65 and 515.7 ± 37.73 m 3 ha - 1 in the first and second experiment, respectively. The findings have encouraged the initiation of experiments to automate the use of the CWSI for precision irrigation using either UAVs in large settings or by adapting TIPCIP to process data from smartphone-based IRT sensors for applications in smallholder settings.

Canopy chlorophyll fluorescence applied to stress detection using an easy-to-build micro-lidar.

LEDFLEX is a micro-lidar dedicated to the measurement of vegetation fluorescence. The light source consists of 4 blue Light-Emitting Diodes (LED) to illuminate part of the canopy in order to average the spatial variability of small crops. The fluorescence emitted in response to a 5-µs width pulse is separated from the ambient light through a synchronized detection. Both the reflectance and the fluorescence of the target are acquired simultaneously in exactly the same field of view, as well as the photosynthetic active radiation and air temperature. The footprint is about 1 m2 at a distance of 8 m. By increasing the number of LEDs longer ranges can be reached. The micro-lidar has been successfully applied under full sunlight conditions to establish the signature of water stress on pea (Pisum Sativum) canopy. Under well-watered conditions the diurnal cycle presents an M shape with a minimum (Fmin) at noon which is Fmin > Fo. After several days withholding watering, Fs decreases and Fmin < Fo. The same patterns were observed on mint (Menta Spicata) and sweet potatoes (Ipomoea batatas) canopies. Active fluorescence measurements with LEDFLEX produced robust fluorescence yield data as a result of the constancy of the excitation intensity and its geometry fixity. Passive methods based on Sun-Induced chlorophyll Fluorescence (SIF) that uses high-resolution spectrometers generate only flux data and are dependent on both the 3D structure of vegetation and variable irradiance conditions along the day. Parallel measurements with LEDFLEX should greatly improve the interpretation of SIF changes.