Retrieval of Crop Variables from Proximal Multispectral UAV Image Data Using PROSAIL in Maize Canopy.

Mapping crop variables at different growth stages is crucial to inform farmers and plant breeders about the crop status. For mapping purposes, inversion of canopy radiative transfer models (RTMs) is a viable alternative to parametric and non-parametric regression models, which often lack transferability in time and space. Due to the physical nature of RTMs, inversion outputs can be delivered in sound physical units that reflect the underlying processes in the canopy. In this study, we explored the capabilities of the coupled leaf-canopy RTM PROSAIL applied to high-spatial-resolution (0.015 m) multispectral unmanned aerial vehicle (UAV) data to retrieve the leaf chlorophyll content (LCC), leaf area index (LAI) and canopy chlorophyll content (CCC) of sweet and silage maize throughout one growing season. Two different retrieval methods were tested: (i) applying the RTM inversion scheme to mean reflectance data derived from single breeding plots (mean reflectance approach) and (ii) applying the same inversion scheme to an orthomosaic to separately retrieve the target variables for each pixel of the breeding plots (pixel-based approach). For LCC retrieval, soil and shaded pixels were removed by applying simple vegetation index thresholding. Retrieval of LCC from UAV data yielded promising results compared to ground measurements (sweet maize RMSE = 4.92 µg/cm2, silage maize RMSE = 3.74 µg/cm2) when using the mean reflectance approach. LAI retrieval was more challenging due to the blending of sunlit and shaded pixels present in the UAV data, but worked well at the early developmental stages (sweet maize RMSE = 0.70m2/m2, silage RMSE = 0.61m2/m2 across all dates). CCC retrieval significantly benefited from the pixel-based approach compared to the mean reflectance approach (RMSEs decreased from 45.6 to 33.1 µg/m2). We argue that high-resolution UAV imagery is well suited for LCC retrieval, as shadows and background soil can be precisely removed, leaving only green plant pixels for the analysis. As for retrieving LAI, it proved to be challenging for two distinct varieties of maize that were characterized by contrasting canopy geometry.

Downscaling of far-red solar-induced chlorophyll fluorescence of different crops from canopy to leaf level using a diurnal data set acquired by the airborne imaging spectrometer HyPlant.

Remote sensing-based measurements of solar-induced chlorophyll fluorescence (SIF) are useful for assessing plant functioning at different spatial and temporal scales. SIF is the most direct measure of photosynthesis and is therefore considered important to advance capacity for the monitoring of gross primary production (GPP) while it has also been suggested that its yield facilitates the early detection of vegetation stress. However, due to the influence of different confounding effects, the apparent SIF signal measured at canopy level differs from the fluorescence emitted at leaf level, which makes its physiological interpretation challenging. One of these effects is the scattering of SIF emitted from leaves on its way through the canopy. The escape fraction ( f esc ) describes the scattering of SIF within the canopy and corresponds to the ratio of apparent SIF at canopy level to SIF at leaf level. In the present study, the fluorescence correction vegetation index (FCVI) was used to determine f esc of far-red SIF for three structurally different crops (sugar beet, winter wheat, and fruit trees) from a diurnal data set recorded by the airborne imaging spectrometer HyPlant. This unique data set, for the first time, allowed a joint analysis of spatial and temporal dynamics of structural effects and thus the downscaling of far-red SIF from canopy ( SIF 760 canopy ) to leaf level ( SIF 760 leaf ). For a homogeneous crop such as winter wheat, it seems to be sufficient to determine f esc once a day to reliably scale SIF760 from canopy to leaf level. In contrast, for more complex canopies such as fruit trees, calculating f esc for each observation time throughout the day is strongly recommended. The compensation for structural effects, in combination with normalizing SIF760 to remove the effect of incoming radiation, further allowed the estimation of SIF emission efficiency ( ε SIF ) at leaf level, a parameter directly related to the diurnal variations of plant photosynthetic efficiency.

Fungicidal Efficacy of Drying Plant Oils in Green Beans against Bean Rust (Uromyces appendiculatus).

As biorationals, plant oils offer numerous advantages such as being natural products, with low ecotoxicological side effects, and high biodegradability. In particular, drying glyceride plant oils, which are rich in unsaturated fatty acids, might be promising candidates for a more sustainable approach in the discussion about plant protection and the environment. Based on this, we tested the protective and curative efficacy of an oil-in-water-emulsion preparation using drying plant oils (linseed oil, tung oil) and a semi-drying plant oil (rapeseed oil) separately and in different mixtures. Plant oils were tested in greenhouse experiments (in vivo) on green beans (Phaseolus vulgaris L.) against bean rust (Uromyces appendiculatus). We observed that a 2% oil concentration showed no or very low phytotoxic effects on green beans. Both tested drying oils showed a protective control ranging from 53-100% for linseed oil and 32-100% for tung oil. Longer time intervals of 6 days before inoculation (6dbi) were less effective than shorter intervals of 2dbi. Curative efficacies were lower with a maximum of 51% for both oils when applied 4 days past inoculation (4dpi) with the fungus. Furthermore, the results showed no systemic effects. These results underline the potential of drying plant oils as biorationals in sustainable plant protection strategies.

Miscanthus x giganteus Stem Versus Leaf-Derived Lignins Differing in Monolignol Ratio and Linkage.

As a renewable, Miscanthus offers numerous advantages such as high photosynthesis activity (as a C4 plant) and an exceptional CO2 fixation rate. These properties make Miscanthus very attractive for industrial exploitation, such as lignin generation. In this paper, we present a systematic study analyzing the correlation of the lignin structure with the Miscanthus genotype and plant portion (stem versus leaf). Specifically, the ratio of the three monolignols and corresponding building blocks as well as the linkages formed between the units have been studied. The lignin amount has been determined for M. x giganteus (Gig17, Gig34, Gig35), M. nagara (NagG10), M. sinensis (Sin2), and M. robustus (Rob4) harvested at different time points (September, December, and April). The influence of the Miscanthus genotype and plant component (leaf vs. stem) has been studied to develop corresponding structure-property relationships (i.e., correlations in molecular weight, polydispersity, and decomposition temperature). Lignin isolation was performed using non-catalyzed organosolv pulping and the structure analysis includes compositional analysis, Fourier transform infradred (FTIR), ultraviolet/visible (UV-Vis), hetero-nuclear single quantum correlation nuclear magnetic resonsnce (HSQC-NMR), thermogravimetric analysis (TGA), and pyrolysis gaschromatography/mass spectrometry (GC/MS). Structural differences were found for stem and leaf-derived lignins. Compared to beech wood lignins, Miscanthus lignins possess lower molecular weight and narrow polydispersities (<1.5 Miscanthus vs. >2.5 beech) corresponding to improved homogeneity. In addition to conventional univariate analysis of FTIR spectra, multivariate chemometrics revealed distinct differences for aromatic in-plane deformations of stem versus leaf-derived lignins. These results emphasize the potential of Miscanthus as a low-input resource and a Miscanthus-derived lignin as promising agricultural feedstock.

Genotype Specific Photosynthesis x Environment Interactions Captured by Automated Fluorescence Canopy Scans Over Two Fluctuating Growing Seasons.

Photosynthesis reacts dynamic and in different time scales to changing conditions. Light and temperature acclimation balance photosynthetic processes in a complex interplay with the fluctuating environment. However, due to limitations in the measurements techniques, these acclimations are often described under steady-state conditions leading to inaccurate photosynthesis estimates in the field. Here we analyze the photosynthetic interaction with the fluctuating environment and canopy architecture over two seasons using a fully automated phenotyping system. We acquired over 700,000 chlorophyll fluorescence transients and spectral measurements under semi-field conditions in four crop species including 28 genotypes. As expected, the quantum efficiency of the photosystem II (Fv/Fm in the dark and Fq'/Fm' in the light) was determined by light intensity. It was further significantly affected by spectral indices representing canopy structure effects. In contrast, a newly established parameter, monitoring the efficiency of electron transport (Fr2/Fv in the dark respective Fr2'/Fq' in the light), was highly responsive to temperature (R2 up to 0.75). This parameter decreased with temperature and enabled the detection of cold tolerant species and genotypes. We demonstrated the ability to capture and model the dynamic photosynthesis response to the environment over entire growth seasons. The improved linkage of photosynthetic performance to canopy structure, temperature and cold tolerance offers great potential for plant breeding and crop growth modeling.

Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platform.

BACKGROUND: Phenotyping is a bottleneck for the development of new plant cultivars. This study introduces a new hyperspectral phenotyping system, which combines the high throughput of canopy scale measurements with the advantages of high spatial resolution and a controlled measurement environment. Furthermore, the measured barley canopies were grown in large containers (called Mini-Plots), which allow plants to develop field-like phenotypes in greenhouse experiments, without being hindered by pot size. RESULTS: Six barley cultivars have been investigated via hyperspectral imaging up to 30 days after inoculation with powdery mildew. With a high spatial resolution and stable measurement conditions, it was possible to automatically quantify powdery mildew symptoms through a combination of Simplex Volume Maximization and Support Vector Machines. Detection was feasible as soon as the first symptoms were visible for the human eye during manual rating. An accurate assessment of the disease severity for all cultivars at each measurement day over the course of the experiment was realized. Furthermore, powdery mildew resistance based necrosis of one cultivar was detected as well. CONCLUSION: The hyperspectral phenotyping system combines the advantages of field based canopy level measurement systems (high throughput, automatization, low manual workload) with those of laboratory based leaf level measurement systems (high spatial resolution, controlled environment, stable conditions for time series measurements). This allows an accurate and objective disease severity assessment without the need for trained experts, who perform visual rating, as well as detection of disease symptoms in early stages. Therefore, it is a promising tool for plant resistance breeding.

Diagnosing ozone stress and differential tolerance in rice (Oryza sativa L.) with ethylenediurea (EDU).

Rising tropospheric ozone concentrations in Asia necessitate the breeding of adapted rice varieties to ensure food security. However, breeding requires field-based evaluation of ample plant material, which can be technically challenging or very costly when using ozone fumigation facilities. The chemical ethylenediurea (EDU) has been proposed for estimating the effects of ozone in large-scale field applications, but controlled experiments investigating constitutive effects on rice or its suitability to detect genotypic differences in ozone tolerance are missing. This study comprised a controlled open top chamber experiment with four treatments (i) control (average ozone concentration 16 ppb), (ii) control with EDU application, (iii) ozone stress (average 77 ppb for 7 h daily throughout the season), and (iv) ozone stress with EDU application. Three contrasting rice genotypes were tested, i.e. the tolerant line L81 and the sensitive Nipponbare and BR28. The ozone treatment had significant negative effects on plant growth (height and tillering), stomatal conductance, SPAD value, spectral reflectance indices such as the normalized difference vegetation index (NDVI), lipid peroxidation, as well as biomass and grain yields. These negative effects were more pronounced in the a priori sensitive varieties, especially the widely grown Bangladeshi variety BR28, which showed grain yield reductions by 37 percent. EDU application had almost no effects on plants in the absence of ozone, but partly mitigated ozone effects on foliar symptoms, lipid peroxidation, SPAD value, stomatal conductance, several spectral reflectance parameters, panicle number, grain yield, and spikelet sterility. EDU responses were more pronounced in sensitive genotypes than in the tolerant L81. In conclusion, EDU had no constitutive effects on rice and partly offset negative ozone effects, especially in sensitive varieties. It can thus be used to diagnose ozone damage in field grown rice and for distinguishing tolerant (less EDU-responsive) and sensitive (more EDU-responsive) genotypes.

Genetic dissection of ozone tolerance in rice (Oryza sativa L.) by a genome-wide association study.

Tropospheric ozone causes various negative effects on plants and affects the yield and quality of agricultural crops. Here, we report a genome-wide association study (GWAS) in rice (Oryza sativa L.) to determine candidate loci associated with ozone tolerance. A diversity panel consisting of 328 accessions representing all subgroups of O. sativa was exposed to ozone stress at 60 nl l(-1) for 7h every day throughout the growth season, or to control conditions. Averaged over all genotypes, ozone significantly affected biomass-related traits (plant height -1.0%, shoot dry weight -15.9%, tiller number -8.3%, grain weight -9.3%, total panicle weight -19.7%, single panicle weight -5.5%) and biochemical/physiological traits (symptom formation, SPAD value -4.4%, foliar lignin content +3.4%). A wide range of genotypic variance in response to ozone stress were observed in all phenotypes. Association mapping based on more than 30 000 single-nucleotide polymorphism (SNP) markers yielded 16 significant markers throughout the genome by applying a significance threshold of P<0.0001. Furthermore, by determining linkage disequilibrium blocks associated with significant SNPs, we gained a total of 195 candidate genes for these traits. The following sequence analysis revealed a number of novel polymorphisms in two candidate genes for the formation of visible leaf symptoms, a RING and an EREBP gene, both of which are involved in cell death and stress defence reactions. This study demonstrated substantial natural variation of responses to ozone in rice and the possibility of using GWAS in elucidating the genetic factors underlying ozone tolerance.