Leaf hue measurements: a high-throughput screening of chlorophyll content

Effect of Different Drying Methods on the Phytochemical and Antioxidant Properties of Soursop Leaves at Two Stages of Maturity

Soursop (Annona muricata L.) leaves are a rich source of bioactive compounds and antioxidant properties. However, they are non-economical and rapidly diminish due to insect damage and biochemical degradation. This study investigates the impact of different drying methods, including tray drying (TD), vacuum drying (VD), and freeze-drying (FD), on the phytochemical and antioxidant properties of soursop leaves at two maturity stages (young (YL) and mature (ML)). By analyzing their proximate composition, mineral content, color characteristics, pH, extraction yield, chlorophyll, ascorbic acid, total phenolics, flavonoids, and antioxidant activities, this study aims to optimize and select the appropriate drying techniques for soursop leaves. Results demonstrate that FD samples achieved the highest preservation of moisture-sensitive bioactive compounds and antioxidant properties followed by VD and TD. FD samples retained higher levels of chlorophyll (10.09-16.88 mg/g), ascorbic acid (15.91-19.89 mg/100g), phenolics (111.98-121.43 mg GAE/g), and flavonoids (68.91-72.45 mg QE/g) exhibited minimal browning and maintained stable pH (6.81-7.01) values. VD effectively reduced moisture content (3.03%) and preserved mineral concentrations, while TD led to significant nutrient loss despite its moisture removal efficiency. Additionally, ML consistently displayed higher nutrient and phytochemical concentrations than YL. This study highlights FD as the optimal method for preserving the health benefits of soursop leaves and suggests VD as a viable alternative when FD is not feasible. These findings are significant for developing cost-effective and efficient preservation strategies, enhancing the economic value of soursop leaves in various applications.

Screening of Croatian Native Grapevine Varieties for Susceptibility to Plasmopara viticola Using Leaf Disc Bioassay, Chlorophyll Fluorescence, and Multispectral Imaging

In the era of sustainable grapevine production, there is a growing demand to define differences between Vitis vinifera varieties in susceptibility to downy mildew. Croatia, as a country with a long tradition of grapevine cultivation, preserves a large number of native grapevine varieties. A leaf disc bioassay has been conducted on 25 of them to define their response to downy mildew, according to the International Organisation of Vine and Wine (OIV) descriptor 452-1, together with the stress response of the leaf discs using chlorophyll fluorescence and multispectral imaging with 11 parameters included. Time points of measurement were as follows: before treatment (T₀), one day post-inoculation (dpi) (T₁), two dpi (T₂), three dpi (T₃), four dpi (T₄), six dpi (T₅), and eight dpi (T₆). Visible changes in form of developed Plasmopara viticola (P. viticola) sporulation were evaluated on the seventh day upon inoculation. Results show that methods applied here distinguish varieties of different responses to downy mildew. Based on the results obtained, a phenotyping model in the absence of the pathogen is proposed, which is required to confirm by conducting more extensive research.

Field Phenomics: Will It Enable Crop Improvement?

Field phenomics has been identified as a promising enabling technology to assist plant breeders with the development of improved cultivars for farmers. Yet, despite much investment, there are few examples demonstrating the application of phenomics within a plant breeding program. We review recent progress in field phenomics and highlight the importance of targeting breeders' needs, rather than perceived technology needs, through developing and enhancing partnerships between phenomics researchers and plant breeders.

Natural variation at FLM splicing has pleiotropic effects modulating ecological strategies in Arabidopsis thaliana

Investigating the evolution of complex phenotypes and the underlying molecular bases of their variation is critical to understand how organisms adapt to their environment. Applying classical quantitative genetics on a segregating population derived from a Can-0xCol-0 cross, we identify the MADS-box transcription factor FLOWERING LOCUS M (FLM) as a player of the phenotypic variation in plant growth and color. We show that allelic variation at FLM modulates plant growth strategy along the leaf economics spectrum, a trade-off between resource acquisition and resource conservation, observable across thousands of plant species. Functional differences at FLM rely on a single intronic substitution, disturbing transcript splicing and leading to the accumulation of non-functional FLM transcripts. Associations between this substitution and phenotypic and climatic data across Arabidopsis natural populations, show how noncoding genetic variation at a single gene might be adaptive through pleiotropic effects.

FLOWERING LOCUS M (FLM) is known as a repressor of Arabidopsis flowering. Here, the authors show that a single intronic substitution of FLM modulates leaf color and plant growth strategy along the leaf economics spectrum, as well as plays a role in plant adaptation.

High-Throughput Phenotyping Analysis of Potted Soybean Plants Using Colorized Depth Images Based on A Proximal Platform

Canopy color and structure can strongly reflect plant functions. Color characteristics and plant height as well as canopy breadth are important aspects of the canopy phenotype of soybean plants. High-throughput phenotyping systems with imaging capabilities providing color and depth information can rapidly acquire data of soybean plants, making it possible to quantify and monitor soybean canopy development. The goal of this study was to develop a 3D imaging approach to quantitatively analyze soybean canopy development under natural light conditions. Thus, a Kinect sensor-based high-throughput phenotyping (HTP) platform was developed for soybean plant phenotyping. To calculate color traits accurately, the distortion phenomenon of color images was first registered in accordance with the principle of three primary colors and color constancy. Then, the registered color images were applied to depth images for the reconstruction of the colorized three-dimensional canopy structure. Furthermore, the 3D point cloud of soybean canopies was extracted from the background according to adjusted threshold, and each area of individual potted soybean plants in the depth images was segmented for the calculation of phenotypic traits. Finally, color indices, plant height and canopy breadth were assessed based on 3D point cloud of soybean canopies. The results showed that the maximum error of registration for the R, G, and B bands in the dataset was 1.26%, 1.09%, and 0.75%, respectively. Correlation analysis between the sensors and manual measurements yielded R2 values of 0.99, 0.89, and 0.89 for plant height, canopy breadth in the west-east (W–E) direction, and canopy breadth in the north-south (N–S) direction, and R2 values of 0.82, 0.79, and 0.80 for color indices h, s, and i, respectively. Given these results, the proposed approaches provide new opportunities for the identification of the quantitative traits that control canopy structure in genetic/genomic studies or for soybean yield prediction in breeding programs.

instaGraminoid, a Novel Colorimetric Method to Assess Herbicide Resistance, Identifies Patterns of Cross-Resistance in Annual Ryegrass

Herbicide resistance in agricultural weeds is a global problem with an increasing understanding that it is caused by multiple genes leading to quantitative resistance. These quantitative patterns of resistance are not easy to decipher with mortality assays alone, and there is a need for straightforward and unbiased protocols to accurately assess quantitative herbicide resistance. instaGraminoid-a computer vision and statistical analysis package-was developed as an automated and scalable method for quantifying herbicide resistance. The package was tested in rigid ryegrass (Lolium rigidum), the most noxious and highly resistant weed in Australia and the Mediterranean region. This method provides quantitative measures of the degree of chlorosis and necrosis of individual plants which was shown to accurately reflect herbicide resistance. We were able to reliably characterise resistance to four herbicides with different sites of action (glyphosate, sulfometuron, terbuthylazine, and trifluralin) in two L. rigidum populations from Southeast Australia. Cross-validation of the method across populations and herbicide treatments showed high repeatability and transferability. Significant positive correlations in resistance of individual plants were observed across herbicides, which suggest either the accumulation of herbicide-specific resistance alleles in single genotypes (multiple stacked resistance) or the presence of general broad-effects resistance alleles (cross-resistance). We used these quantitative estimates of cross-resistance to simulate how resistance development under an herbicide rotation strategy is likely to be higher than expected.

PlantSize Offers an Affordable, Non-destructive Method to Measure Plant Size and Color in Vitro

Plant size, shape and color are important parameters of plants, which have traditionally been measured by destructive and time-consuming methods. Non-destructive image analysis is an increasingly popular technology to characterize plant development in time. High throughput automatic phenotyping platforms can simultaneously analyze multiple morphological and physiological parameters of hundreds or thousands of plants. Such platforms are, however, expensive and are not affordable for many laboratories. Moreover, determination of basic parameters is sufficient for most studies. Here we describe a non-invasive method, which simultaneously measures basic morphological and physiological parameters of in vitro cultured plants. Changes of plant size, shape and color is monitored by repeated photography with a commercial digital camera using neutral white background. Images are analyzed with the MatLab-based computer application PlantSize, which simultaneously calculates several parameters including rosette size, convex area, convex ratio, chlorophyll and anthocyanin contents of all plants identified on the image. Numerical data are exported in MS Excel-compatible format. Subsequent data processing provides information on growth rates, chlorophyll and anthocyanin contents. Proof-of-concept validation of the imaging technology was demonstrated by revealing small but significant differences between wild type and transgenic Arabidopsis plants overexpressing the HSFA4A transcription factor or the hsfa4a knockout mutant, subjected to different stress conditions. While HSFA4A overexpression was associated with better growth, higher chlorophyll and lower anthocyanin content in saline conditions, the knockout hsfa4a mutant showed hypersensitivity to various stresses. Morphological differences were revealed by comparing rosette size, shape and color of wild type plants with phytochrome B (phyB-9) mutant. While the technology was developed with Arabidopsis plants, it is suitable to characterize plants of other species including crops, in a simple, affordable and fast way. PlantSize is publicly available (http://www.brc.hu/pub/psize/index.html).

Disruption of the plant-specific CFS1 gene impairs autophagosome turnover and triggers EDS1-dependent cell death

Cell death, autophagy and endosomal sorting contribute to many physiological, developmental and immunological processes in plants. They are mechanistically interconnected and interdependent, but the molecular basis of their mutual regulation has only begun to emerge in plants. Here, we describe the identification and molecular characterization of CELL DEATH RELATED ENDOSOMAL FYVE/SYLF PROTEIN 1 (CFS1). The CFS1 protein interacts with the ENDOSOMAL SORTING COMPLEX REQUIRED FOR TRANSPORT I (ESCRT-I) component ELCH (ELC) and is localized at ESCRT-I-positive late endosomes likely through its PI3P and actin binding SH3YL1 Ysc84/Lsb4p Lsb3p plant FYVE (SYLF) domain. Mutant alleles of cfs1 exhibit auto-immune phenotypes including spontaneous lesions that show characteristics of hypersensitive response (HR). Autoimmunity in cfs1 is dependent on ENHANCED DISEASE SUSCEPTIBILITY 1 (EDS1)-mediated effector-triggered immunity (ETI) but independent from salicylic acid. Additionally, cfs1 mutants accumulate the autophagy markers ATG8 and NBR1 independently from EDS1. We hypothesize that CFS1 acts at the intersection of autophagosomes and endosomes and contributes to cellular homeostasis by mediating autophagosome turnover.

A nondestructive method to estimate the chlorophyll content of Arabidopsis seedlings

BACKGROUND

Chlorophyll content decreases in plants under stress conditions, therefore it is used commonly as an indicator of plant health. Arabidopsis thaliana offers a convenient and fast way to test physiological phenotypes of mutations and treatments. However, chlorophyll measurements with conventional solvent extraction are not applicable to Arabidopsis leaves due to their small size, especially when grown on culture dishes.

RESULTS

We provide a nondestructive method for chlorophyll measurement whereby the red, green and blue (RGB) values of a color leaf image is used to estimate the chlorophyll content from Arabidopsis leaves. The method accommodates different profiles of digital cameras by incorporating the ColorChecker chart to make the digital negative profiles, to adjust the white balance, and to calibrate the exposure rate differences caused by the environment so that this method is applicable in any environment. We chose an exponential function model to estimate chlorophyll content from the RGB values, and fitted the model parameters with physical measurements of chlorophyll contents. As proof of utility, this method was used to estimate chlorophyll content of G protein mutants grown on different sugar to nitrogen ratios.

CONCLUSION

This method is a simple, fast, inexpensive, and nondestructive estimation of chlorophyll content of Arabidopsis seedlings. This method lead to the discovery that G proteins are important in sensing the C/N balance to control chlorophyll content in Arabidopsis.