Light ray tracing through a leaf cross section

Estimation of genetic components, heterosis and combining ability of elite Pakistani wheat varieties for yield attributing traits and stripe rust response

Wheat (Triticum aestivum L.) is a staple food and major source of dietary calories in Pakistan. Improving wheat varieties with higher grain yield and disease resistance is a prime objective. The knowledge of genetic behaviour of germplasm is key. To achieve this objective, elite wheat varieties were crossed in 4 by 3, line × tester design, and tested in 2019 in a triplicate yield trial to estimate genetic variance, general and specific combining ability, mid-parent heterosis and stripe rust (Puccinia striiformis L.). High grain 3358 kg·ha-1 was recorded in F1 hybrid (ZRG-79 × PAK-13). Analysis of variance (ANOVA) revealed significant genotypic variance in grain yield. Broad sense heritability (H2) was recorded in the range of 28 to 100 %. General combining ability (GCA) significant for grain yield in parents except FSD-08 and PS-05 was recorded, while specific combining ability (SCA) was recorded to be highly significant for grain yield only in two crosses (ZRG-79 × NR-09 and ZRG-79 × PAK-13). Mid-parent heterosis was estimated in the range of -28 to 62.6 %. Cross combinations ZRG-79 × PAK-13 depicted highly significant mid-parent heterosis (62.6 %). Highly significant correlation was observed among spike length, spikelets per spike, plant height and 1000-grain weight. Rust resistance index was recorded in the range of 0 to 8.5. These findings suggest exploitation of GCA for higher grain yield is important due to the presence of additive gene action and selection in the filial generations will be effective with improved rust resistance, while cross combinations ZRG-79 × PAK-13 high GCA are best suited for hybrid development.

Human vs. Machine, the Eyes Have It. Assessment of Stemphylium Leaf Blight on Onion Using Aerial Photographs from an NIR Camera

Aerial surveillance could be a useful tool for early detection and quantification of plant diseases, however, there are often confounding effects of other types of plant stress. Stemphylium leaf blight (SLB), caused by the fungus Stemphylium vesicarium, is a damaging foliar disease of onion. Studies were conducted to determine if near-infrared photographic images could be used to accurately assess SLB severity in onion research trials in the Holland Marsh in Ontario, Canada. The site was selected for its uniform soil and level topography. Aerial photographs were taken in 2015 and 2016 using an Xnite-Canon SX230NDVI with a near-infrared filter, mounted on a modified Cine Star—8 MK Heavy Lift RTF octocopter UAV. Images were taken at 15–20 m above the ground, providing an average of 0.5 cm/pixel and a field of view of 15 × 20 m. Photography and ground assessments of disease were carried out on the same day. NDVI (normalized difference vegetation index), green NDVI, chlorophyll index and plant senescence reflective index (PSRI) were calculated from the images. There were differences in SLB incidence and severity in the field plots and differences in the vegetative indices among the treatments, but there were no correlations between disease assessments and any of the indices.

Investigation on the effects of water loss on the solar spectrum reflectance and transmittance of Osmanthus fragrans leaves based on optical experiment and PROSPECT model

Water is the main determinant of the leaf spectral characteristics in the shortwave infrared region, whereas only changing the water content in the PROSPECT model cannot accurately describe the solar spectrum reflectance and transmittance of the dehydrated leaf. To elucidate the effects of water loss, the solar spectrum reflectances and transmittances of the Osmanthus fragrans leaves in the fresh state, natural air-dry state and oven-dry state were measured, and the leaf parameters were predicted by the PROSPECT model inversion. The results revealed that the first effect was to increase the brown pigment content, which led to an increase in leaf absorption and change of the leaf absorption characteristics, and correspondingly, in the visible region, both the reflected and transmitted radiations were decreased and the reflection peak shifted towards a long wavelength. The other two effects were to increase the leaf structure index and refractive index, which resulted in an enhancement of the reflected radiation and an attenuation of the transmitted radiation over the range from 400 to 2500 nm. These findings suggest that if people consider the changes of leaf pigment content, structure and refractive index when water is lost from an actual leaf, it will be expected to improve the monitoring accuracy of the leaf water content based on leaf spectral remote sensing technology.

Genetic dissection of seasonal vegetation index dynamics in maize through aerial based high-throughput phenotyping

Plant phenotyping under field conditions plays an important role in agricultural research. Efficient and accurate high-throughput phenotyping strategies enable a better connection between genotype and phenotype. Unmanned aerial vehicle-based high-throughput phenotyping platforms (UAV-HTPPs) provide novel opportunities for large-scale proximal measurement of plant traits with high efficiency, high resolution, and low cost. The objective of this study was to use time series normalized difference vegetation index (NDVI) extracted from UAV-based multispectral imagery to characterize its pattern across development and conduct genetic dissection of NDVI in a large maize population. The time series NDVI data from the multispectral sensor were obtained at five time points across the growing season for 1,752 diverse maize accessions with a UAV-HTPP. Cluster analysis of the acquired measurements classified 1,752 maize accessions into two groups with distinct NDVI developmental trends. To capture the dynamics underlying these static observations, penalized-splines (P-splines) model was used to obtain genotype-specific curve parameters. Genome-wide association study (GWAS) using static NDVI values and curve parameters as phenotypic traits detected signals significantly associated with the traits. Additionally, GWAS using the projected NDVI values from the P-splines models revealed the dynamic change of genetic effects, indicating the role of gene-environment interplay in controlling NDVI across the growing season. Our results demonstrated the utility of ultra-high spatial resolution multispectral imagery, as that acquired using a UAV-based remote sensing, for genetic dissection of NDVI.

Using Hybrid Artificial Intelligence and Evolutionary Optimization Algorithms for Estimating Soybean Yield and Fresh Biomass Using Hyperspectral Vegetation Indices

Recent advanced high-throughput field phenotyping combined with sophisticated big data analysis methods have provided plant breeders with unprecedented tools for a better prediction of important agronomic traits, such as yield and fresh biomass (FBIO), at early growth stages. This study aimed to demonstrate the potential use of 35 selected hyperspectral vegetation indices (HVI), collected at the R5 growth stage, for predicting soybean seed yield and FBIO. Two artificial intelligence algorithms, ensemble-bagging (EB) and deep neural network (DNN), were used to predict soybean seed yield and FBIO using HVI. Considering HVI as input variables, the coefficients of determination (R2) of 0.76 and 0.77 for yield and 0.91 and 0.89 for FBIO were obtained using DNN and EB, respectively. In this study, we also used hybrid DNN-SPEA2 to estimate the optimum HVI values in soybeans with maximized yield and FBIO productions. In addition, to identify the most informative HVI in predicting yield and FBIO, the feature recursive elimination wrapper method was used and the top ranking HVI were determined to be associated with red, 670 nm and near-infrared, 800 nm, regions. Overall, this study introduced hybrid DNN-SPEA2 as a robust mathematical tool for optimizing and using informative HVI for estimating soybean seed yield and FBIO at early growth stages, which can be employed by soybean breeders for discriminating superior genotypes in large breeding populations.

Assessing Leaf Biomass of Agave sisalana Using Sentinel-2 Vegetation Indices

Biomass is a principal variable in crop monitoring and management and in assessing carbon cycling. Remote sensing combined with field measurements can be used to estimate biomass over large areas. This study assessed leaf biomass of Agave sisalana (sisal), a perennial crop whose leaves are grown for fibre production in tropical and subtropical regions. Furthermore, the residue from fibre production can be used to produce bioenergy through anaerobic digestion. First, biomass was estimated for 58 field plots using an allometric approach. Then, Sentinel-2 multispectral satellite imagery was used to model biomass in an 8851-ha plantation in semi-arid south-eastern Kenya. Generalised Additive Models were employed to explore how well biomass was explained by various spectral vegetation indices (VIs). The highest performance (explained deviance = 76%, RMSE = 5.15 Mg ha−1) was achieved with ratio and normalised difference VIs based on the green (R560), red-edge (R740 and R783), and near-infrared (R865) spectral bands. Heterogeneity of ground vegetation and resulting background effects seemed to limit model performance. The best performing VI (R740/R783) was used to predict plantation biomass that ranged from 0 to 46.7 Mg ha−1 (mean biomass 10.6 Mg ha−1). The modelling showed that multispectral data are suitable for assessing sisal leaf biomass at the plantation level and in individual blocks. Although these results demonstrate the value of Sentinel-2 red-edge bands at 20-m resolution, the difference from the best model based on green and near-infrared bands at 10-m resolution was rather small.

Single-shot common-path off-axis dual-wavelength digital holographic microscopy

A single-shot common-path off-axis self-interference dual-wavelength digital holographic microscopic (DHM) system based on a cube beam splitter is demonstrated to expand the phase range in a stepped microstructure and for simultaneous measurement of the refractive index and physical thickness of a specimen. In the system, two laser beams with wavelengths of 532 nm and 632.8 nm are used. These laser beams are combined to transilluminate the object under study, then the object beam is divided into two beams by using a beam splitter oriented in such a way that both the beams propagate in almost the same direction, with an appropriate lateral separation between them. One of the object beams is spatially filtered at its Fourier plane, using a pinhole to generate a reference spherical beam free from the object information. The reference beam interferes with the object beam to form a digital hologram at the faceplate of the image sensor. The phase information is extracted from a single recorded digital hologram using the phase aberration compensation method that is based on principal component analysis (PCA). Owing to the common-path configuration, the system shows high temporal phase stability and it is less vibration-sensitive compared to counterparts such as a Mach-Zehnder type DHM. The performance of the dual-wavelength DHM system is verified in two different application fields by conducting the experiments using microsphere beads and living plant cells.

Method to Study Gene Expression Patterns During De Novo Root Regeneration from Arabidopsis Leaf Explants

De novo root regeneration (DNRR) is the process in which adventitious roots are regenerated from damaged plant tissues or organs. We have developed a simple DNRR system in which adventitious roots are formed from detached leaf explants of Arabidopsis (Arabidopsis thaliana) on B5 medium without external hormones. In this chapter, we introduce the methods used to observe gene expression patterns during rooting from leaf explants. Usually, β-glucuronidase (GUS) staining is used to visualize gene expression patterns, since fluorescent proteins are difficult to observe because of the high autofluorescence in leaf explants. Here, we describe the use of the ClearSee technique with Congo red staining for deep imaging to observe fluorescent proteins. This method diminishes autofluorescence in leaf explants and preserves the stability of fluorescent proteins, thus allowing us to investigate the endogenous molecular actions guiding DNRR.

In vivo photoprotection mechanisms observed from leaf spectral absorbance changes showing VIS-NIR slow-induced conformational pigment bed changes

Regulated heat dissipation under excessive light comprises a complexity of mechanisms, whereby the supramolecular light-harvesting pigment-protein complex (LHC) shifts state from light harvesting towards heat dissipation, quenching the excess of photo-induced excitation energy in a non-photochemical way. Based on whole-leaf spectroscopy measuring upward and downward spectral radiance fluxes, we studied spectrally contiguous (hyperspectral) transient time series of absorbance A(λ,t) and passively induced chlorophyll fluorescence F(λ,t) dynamics of intact leaves in the visible and near-infrared wavelengths (VIS-NIR, 400-800 nm) after sudden strong natural-like illumination exposure. Besides light avoidance mechanism, we observed on absorbance signatures, calculated from simultaneous reflectance R(λ,t) and transmittance T(λ,t) measurements as A(λ,t) = 1 - R(λ,t) - T(λ,t), major dynamic events with specific onsets and kinetical behaviour. A consistent well-known fast carotenoid absorbance feature (500-570 nm) appears within the first seconds to minutes, seen from both the reflected (backscattered) and transmitted (forward scattered) radiance differences. Simultaneous fast Chl features are observed, either as an increased or decreased scattering behaviour during quick light adjustment consistent with re-organizations of the membrane. The carotenoid absorbance feature shows up simultaneously with a major F decrease and corresponds to the xanthophyll conversion, as quick response to the proton gradient build-up. After xanthophyll conversion (t = 3 min), a kinetically slower but major and smooth absorbance increase was occasionally observed from the transmitted radiance measurements as wide peaks in the green (~ 550 nm) and the near-infrared (~ 750 nm) wavelengths, involving no further F quenching. Surprisingly, in relation to the response to high light, this broad and consistent VIS-NIR feature indicates a slowly induced absorbance increase with a sigmoid kinetical behaviour. In analogy to sub-leaf-level observations, we suggest that this mechanism can be explained by a structure-induced low-energy-shifted energy redistribution involving both Car and Chl. These findings might pave the way towards a further non-invasive spectral investigation of antenna conformations and their relations with energy quenching at the intact leaf level, which is, in combination with F measurements, of a high importance for assessing plant photosynthesis in vivo and in addition from remote observations.

Non-invasive quantification of foliar pigments: Possibilities and limitations of reflectance- and absorbance-based approaches

Established reflectance-based approaches for estimation of foliar pigment contents assume close relationship between leaf absorbance and reflectance. Complex organization and high pigment content of leaves may lead to violation of the essential assumptions under Kubleka-Munk theory relating reflectance and absorbance. We compared relationships of absorbance and reciprocal reflectance vs. pigment content in leaves collected across species, developmental stages and physiological states. As a result, limitations of reflectance-based spectroscopy for pigment quantification were revealed. We deduced in situ absorbance of foliar chlorophylls, carotenoids, and flavonoids (including red-colored anthocyanins) and introduced a concept of specific spectral response of the optical properties to each pigment group. Quantitative criteria of spectral range selection for the absorbance- and reflectance-based techniques yielding effect of each pigment on the background of other pigment absorption were suggested and validated. We argue that absorbance- and reflectance-based approaches to pigment estimation complement each other and can be used synergistically in advanced models for accurate estimating foliar pigments. The study provides a deeper insight into interception of light by photosynthetic and photoprotective pigments as function of physiological condition and developmental stage, which is important for plant biology as well as knowledge-driven selection of spectral bands for noninvasive pigment estimation models.

Assessing the influence of structural disorder on the plant epidermal cells' optical properties: a numerical analysis

Many plant surfaces, such as rose petals, display lens-like epidermal cells that are known to assist the collection and focusing of the sunlight. Those cells form an array with a high degree of structural irregularities including disorder in the height and orientation of the cells, and in their arrangement. In this study, we numerically analyze the influence of structural disorder on the optical properties of a 3D modeled epidermal cell array using ray tracing simulations. We conclude that the anti-reflection properties of such structures are almost unperturbed by disorder effects, although the latter can notably broaden the propagation angle distribution of the collected light. Those results also have a direct implication on the design of plant-inspired light management structures. This aspect is illustrated by introducing the example of a thin-film solar cell covered by a light harvesting epidermal cells replica and simulated for each of the three disorder types considered.

ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging

Imaging techniques for visualizing and analyzing precise morphology and gene expression patterns are essential for understanding biological processes during development in all organisms. With the aid of chemical screening, we developed a clearing method using chemical solutions, termed ClearSee, for deep imaging of morphology and gene expression in plant tissues. ClearSee rapidly diminishes chlorophyll autofluorescence while maintaining fluorescent protein stability. By adjusting the refractive index mismatch, whole-organ and whole-plant imaging can be performed by both confocal and two-photon excitation microscopy in ClearSee-treated samples. Moreover, ClearSee is applicable to multicolor imaging of fluorescent proteins to allow structural analysis of multiple gene expression. Given that ClearSee is compatible with staining by chemical dyes, the technique is useful for deep imaging in conjunction with genetic markers and for plant species not amenable to transgenic approaches. This method is useful for whole imaging for intact morphology and will help to accelerate the discovery of new phenomena in plant biological research.

Summary: The optical clearing reagent ClearSee improves the multicolor imaging of fluorescent proteins and dyes and allows the structural analysis of gene expression patterns in multiple plant tissues.

Normalized Difference Vegetation Index as a tool for wheat yield estimation: a case study from Faisalabad, Pakistan

For estimation of grain yield in wheat, Normalized Difference Vegetation Index (NDVI) is considered as a potential screening tool. Field experiments were conducted to scrutinize the response of NDVI to yield behavior of different wheat cultivars and nitrogen fertilization at agronomic research area, University of Agriculture Faisalabad (UAF) during the two years 2008-09 and 2009-10. For recording the value of NDVI, Green seeker (Handheld-505) was used. Split plot design was used as experimental model in, keeping four nitrogen rates (N₁ = 0 kg ha⁻¹, N₂ = 55 kg ha⁻¹, N₃ = 110 kg ha⁻¹, and N₄ = 220 kg ha⁻¹) in main plots and ten wheat cultivars (Bakkhar-2001, Chakwal-50, Chakwal-97, Faisalabad-2008, GA-2002, Inqlab-91, Lasani-2008, Miraj-2008, Sahar-2006, and Shafaq-2006) in subplots with four replications. Impact of nitrogen and difference between cultivars were forecasted through NDVI. The results suggested that nitrogen treatment N₄ (220 kg ha⁻¹) and cultivar Faisalabad-2008 gave maximum NDVI value (0.85) at grain filling stage among all treatments. The correlation among NDVI at booting, grain filling, and maturity stages with grain yield was positive (R² = 0.90; R² = 0.90; R² = 0.95), respectively. So, booting, grain filling, and maturity can be good depictive stages during mid and later growth stages of wheat crop under agroclimatic conditions of Faisalabad and under similar other wheat growing environments in the country.

Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves

Leaf chlorophyll content provides valuable information about physiological status of plants. Reflectance measurement makes it possible to quickly and non-destructively assess, in situ, the chlorophyll content in leaves. Our objective was to investigate the spectral behavior of the relationship between reflectance and chlorophyll content and to develop a technique for non-destructive chlorophyll estimation in leaves with a wide range of pigment content and composition using reflectance in a few broad spectral bands. Spectral reflectance of maple, chestnut, wild vine and beech leaves in a wide range of pigment content and composition was investigated. It was shown that reciprocal reflectance (R lambda)-1 in the spectral range lambda from 520 to 550 nm and 695 to 705 nm related closely to the total chlorophyll content in leaves of all species. Subtraction of near infra-red reciprocal reflectance, (RNIR)-1, from (R lambda)-1 made index [(R lambda)(-1)-(RNIR)-1] linearly proportional to the total chlorophyll content in spectral ranges lambda from 525 to 555 nm and from 695 to 725 nm with coefficient of determination r2 > 0.94. To adjust for differences in leaf structure, the product of the latter index and NIR reflectance [(R lambda)(-1)-(RNIR)-1]*(RNIR) was used; this further increased the accuracy of the chlorophyll estimation in the range lambda from 520 to 585 nm and from 695 to 740 nm. Two independent data sets were used to validate the developed algorithms. The root mean square error of the chlorophyll prediction did not exceed 50 mumol/m2 in leaves with total chlorophyll ranged from 1 to 830 mumol/m2.

Three-dimensional radiation transfer modeling in a dicotyledon leaf

The propagation of light in a typical dicotyledon leaf is investigated with a new Monte Carlo ray-tracing model. The three-dimensional internal cellular structure of the various leaf tissues, including the epidermis, the palisade parenchyma, and the spongy mesophyll, is explicitly described. Cells of different tissues are assigned appropriate morphologies and contain realistic amounts of water and chlorophyll. Each cell constituent is characterized by an index of refraction and an absorption coefficient. The objective of this study is to investigate how the internal three-dimensional structure of the tissues and the optical properties of cell constituents control the reflectance and transmittance of the leaf. Model results compare favorably with laboratory observations. The influence of the roughness of the epidermis on the reflection and absorption of light is investigated, and simulation results confirm that convex cells in the epidermis focus light on the palisade parenchyma and increase the absorption of radiation.

Nondestructive measurement of chlorophyll pigment content in plant leaves from three-color reflectance and transmittance

We propose a nondestructive or optical method of measuring the chlorophyll content in a leaf after constructing a mathematical model of reflectance and transmittance of plant leaves as a function of their chlorophyll pigment content. The model is based on the Kubelka-Munk theory and involves the modeling of the multiple reflection of light in a leaf that is assumed to be composed of a stack of four layers. It also includes the assumption that the scattering coefficient and the absorption coefficient of the Kubelka-Munk theory can be expressed as a linear function of the pigment content of a plant leaf. In the proposed method, the chlorophyll content is calculated from reflectances and transmittances at three bands whose center wavelengths are 880,720, and 700 nm. Experiments were performed to confirm the applicability of the model and the method. Reflectance and transmittance calculated with the model showed good agreement with measured values. Furthermore, several unmeasurable constants necessary in the calculation were determined by a least-squares fit. We also confirmed that these results were consistent with several well-known facts in the botanical field. The method proposed here showed a small estimation error of 6.6 microg/cm (2) over the 0-80 microg/cm(2) chlorophyll content range for all kinds of plant tested.

Specular, diffuse, and polarized light scattered by two wheat canopies

Using polarization measurements, the reflectance factor R(theta(i),phi(i),theta(r),phi(r)) of two wheat canopies is divided into components due to specularly and diffusely reflected light. The data show that two key angles may be predicted, the angle of the polarizer for minimum flux and the angle of incidence of sunlight specularly reflected by a leaf to a sensor. The results show that specular reflection is a key aspect to radiation transfer by two canopies. Results suggest that the advent of heading in wheat may be remotely sensed from polarization measurements of the canopy reflectance.

Radiative heating and cooling with spectrally selective surfaces

Matter continuously exchanges energy with its surroundings. This exchange can be dominated by radiation, conduction, or convection. In this brief review we discuss how proper design of radiative surface properties can be used for heating and cooling purposes. The desired properties can be understood once it is realized that solar and terrestrial radiation take place in different wavelength ranges and that only part of the solar spectrum is useful for vision and for photosynthesis in plants. These facts allow the possibility of tailoring the spectral absorptance, emittance, reflectance, and transmittance of a surface to meet different demands in different wavelength intervals, i.e., to take advantage of spectral selectivity. One example is the selective surface for efficient photothermal conversion of solar energy, which has high absorptance over the solar spectrum but low emittance for the longer wavelengths relevant to thermal reradiation. Below we discuss the pertinent spectral radiative properties of our ambience. These data are then used as background to the subsequent sections treating four examples of spectrally selective surfaces. The first example is the previously mentioned selective surface for converting solar radiation to useful heat. The second example considers surfaces capable of reaching low temperatures by benefiting from the spectral emittance of the clear night sky. The third example concerns two related types of transparent heat mirror. The fourth example, finally, treats radiative cooling of green leaves; this part is included since it gives a nice example of how nature solves a difficult problem in an elegant and efficient way. This example hence provides an interesting background to the other cruder types of artificial selective surfaces. Throughout our discussion we treat the ideal spectral properties, give an illustrative experimental example of how well this goal can be realized, and-where this is possible-show a corresponding theoretical curve indicating to what extent the measured results can be theoretically understood.

Leaf optical system modeled as a stochastic process

A stochastic leaf radiation model based upon physical and physiological properties of dicot leaves has been developed. The model accurately predicts the absorbed, reflected, and transmitted radiation of normal incidence as a function of wavelength resulting from the leaf-irradiance interaction over the spectral interval of 0.40-2.50 microm. The leaf optical system has been represented as Markov process with a unique transition matrix at each 0.01-microm increment between 0.40 microm and 2.50 microm. Probabilities are calculated at every wavelength interval from leaf thickness, structure, pigment composition, and water content. Simulation results indicate that this approach gives accurate estimations of actual measured values for dicot leaf absorption, reflection, and transmission as a function of wavelength.