Incorporation of ascorbic acid in chitosan-based coating combined with plasma-activated water: A technology for quality preservation of red grapes after simulated transportation.

Red grapes possess multiple bioactivities but are highly susceptible to spoilage due to the lack of efficient preservation techniques. Plasma-activated water (PAW) treatment and the incorporation of antioxidants in bio-based coatings are promising methods for preserving produce. In this study, we tested a novel combination by incorporating ascorbic acid (AA) into a chitosan-based edible coating (CH) and combining it with plasma-activated water (PAW) treatment (CA-PAW) before simulating transport vibrations to extend the shelf-life of red grapes. The results from storage at 4 °C for 20 d indicated that the CA-PAW treatment reduced microbial counts by 2.62 log10 CFU/g for bacteria, 1.72 log10 CFU/g for yeasts and molds, and 1.1 log10 CFU/g for coliforms, in comparison to the control group treated with sterile deionized water. Total phenols and total flavonoid content were the highest observed, at 111.2 mg GAE/100 g and 262.67 mg RE/100 g, respectively. This treatment also inhibited water migration and erosion, and reduced damage to cell structure. Microstructural observations revealed that the CH coating on the surface of red grapes diminished the degradation of bioactive components. In conclusion, the CA-PAW treatment effectively inhibited the adverse physiological changes caused by vibration and mechanical damage to red grapes, maintained their nutritional and sensory qualities, and extended the shelf life by at least 8 d.

Transcription factor MdNAC33 is involved in ALA-induced anthocyanin accumulation in apples.

5-Aminolevulinic acid (ALA), as a new natural plant growth regulator, has a significant function in promoting anthocyanin accumulation in many species of fruits. However, the mechanisms underlying remain obscure. In a transcriptome study of our group, it was found that many transcription factors (TFs) including NACs responsive to ALA treatment during anthocyanin accumulation. In the present study, we found a NAC of apple, MdNAC33 was coordinatively expressed with anthocyanin accumulation after ALA treatment in the apple fruits and leaves, suggesting that this TF may be involved in anthocyanin accumulation induced by ALA. We found that the MdNAC33 protein was localized in the nucleus and exhibited strong transcriptional activity in both yeast cells and plants, where its C-terminal contributed to the transcriptional activity. Functional analysis showed that overexpression of MdNAC33 promoted the accumulation of anthocyanin, while the silencing vector of MdNAC33 (RNAi) significantly impaired the anthocyanin accumulation induced by ALA. Yeast one-hybrid (Y1H), luciferase assay and electrophoretic mobility shift assay (EMSA) indicated that MdNAC33 could bind to promoters of MdbHLH3, MdDFR and MdANS to activate the gene expressions. In addition, MdNAC33 specifically interacts with MdMYB1, a positive regulator of anthocyanin biosynthesis, which was then in turn binding to its target genes MdUFGT and MdGSTF12, to promote anthocyanin accumulation in apples. Taken together, our data indicate that MdNAC33 plays multiple roles in ALA-induced anthocyanin biosynthesis. It provides new insights into the mechanisms of anthocyanin accumulation induced by ALA.

Dead Laying Hens Detection Using TIR-NIR-Depth Images and Deep Learning on a Commercial Farm.

In large-scale laying hen farming, timely detection of dead chickens helps prevent cross-infection, disease transmission, and economic loss. Dead chicken detection is still performed manually and is one of the major labor costs on commercial farms. This study proposed a new method for dead chicken detection using multi-source images and deep learning and evaluated the detection performance with different source images. We first introduced a pixel-level image registration method that used depth information to project the near-infrared (NIR) and depth image into the coordinate of the thermal infrared (TIR) image, resulting in registered images. Then, the registered single-source (TIR, NIR, depth), dual-source (TIR-NIR, TIR-depth, NIR-depth), and multi-source (TIR-NIR-depth) images were separately used to train dead chicken detecting models with object detection networks, including YOLOv8n, Deformable DETR, Cascade R-CNN, and TOOD. The results showed that, at an IoU (Intersection over Union) threshold of 0.5, the performance of these models was not entirely the same. Among them, the model using the NIR-depth image and Deformable DETR achieved the best performance, with an average precision (AP) of 99.7% (IoU = 0.5) and a recall of 99.0% (IoU = 0.5). While the IoU threshold increased, we found the following: The model with the NIR image achieved the best performance among models with single-source images, with an AP of 74.4% (IoU = 0.5:0.95) in Deformable DETR. The performance with dual-source images was higher than that with single-source images. The model with the TIR-NIR or NIR-depth image outperformed the model with the TIR-depth image, achieving an AP of 76.3% (IoU = 0.5:0.95) and 75.9% (IoU = 0.5:0.95) in Deformable DETR, respectively. The model with the multi-source image also achieved higher performance than that with single-source images. However, there was no significant improvement compared to the model with the TIR-NIR or NIR-depth image, and the AP of the model with multi-source image was 76.7% (IoU = 0.5:0.95) in Deformable DETR. By analyzing the detection performance with different source images, this study provided a reference for selecting and using multi-source images for detecting dead laying hens on commercial farms.

ALA induces stomatal opening through regulation among PTPA, PP2AC, and SnRK2.6.

5-Aminolevulinic acid (ALA), as a new natural plant growth regulator, has been proved to regulate protein phosphatase 2A (PP2A) activity to promote stomatal opening in apple (Malus domestica) leaves. However, the molecular mechanisms underlying remain unclear. Here, we cloned and transformed MdPTPA, MdPP2AC, and MdSnRK2.6 of apple into tobaccos (Nicotiana tabacum) and found that over-expression (OE)-MdPTPA or OE-MdPP2AC promoted stomatal aperture while OE-MdSnRK2.6 induced stomatal closure under normal or drought condition. The Ca2+ and H2O2 levels in the guard cells of OE-MdPTPA and OE-MdPP2AC was decreased but flavonols increased, and the results in OE-SnRK2.6 was contrary. Exogenous ALA stimulated PP2A activity but depressed SnRK2.6 activity in transgenic tobaccos, leading to less Ca2+, H2O2 and more flavonols in guard cells, and consequently stomatal opening. OE-MdPTPA improved stomatal opening and plant growth but impaired drought tolerance, while OE-MdSnRK2.6 improved drought tolerance but depressed the leaf P n. Only OE-MdPP2AC improved stomatal opening, leaf P n, plant growth, as well as drought tolerance. These suggest that the three genes involved in ALA-regulating stomatal movement have their respective unique biological functions. Yeast two-hybrid (Y2H) assays showed that MdPP2AC interacted with MdPTPA or MdSnRK2.6, respectively, but no interaction of MdPTPA with MdSnRK2.6 was found. Yeast three-hybrid (Y3H) assay showed that MdPTPA promoted the interactions between MdPP2AC and MdSnRK2.6. Therefore, we propose a regulatory module of PTPA-PP2AC-SnRK2.6 that may be involved in mediating the ALA-inducing stomatal aperture in green plants.

ALA reverses ABA-induced stomatal closure by modulating PP2AC and SnRK2.6 activity in apple leaves.

5-Aminolevulinic acid (ALA), known as a new natural plant growth regulator, can reverse abscisic acid (ABA)-induced stomatal closure. The protein phosphatase 2A (PP2A) played an important role in regulation of stomatal movement by ALA and ABA; however, the underlying molecular mechanisms remain unclear. Here, we report that ALA promotes MdPP2A activity and gene expression in the leaf epidermis of apple (Malus × domestica Borkh.), and expression of the catalytic subunit MdPP2AC was most significantly correlated with stomatal aperture. Western blotting showed that ALA enhanced MdPP2AC protein abundance and phosphorylation. Y2H (yeast two hybrid), FLC (firefly luciferase complementation imaging) and BiFC (Bimolecular fluorescence complementation) assays showed that MdPP2AC interacted with several other MdPP2A subunits as well as MdSnRK2.6 (Sucrose non-fermenting 1-related protein kinase 2.6), and the latter interaction was further verified by pull-down and MST (microscale thermophoresis) assays. ALA downregulated ABA-induced MdSnRK2.6 gene expression, kinase activity, and protein phosphorylation. In transiently transgenic apple leaves, OE-MdPP2AC promoted stomatal aperture by reducing Ca2+ and H2O2 levels but increasing flavonol levels in guard cells. Conversely, OE-MdSnRK2.6 induced stomatal closure by increasing Ca2+ and H2O2 but reducing flavonols. Partial silencing of these genes had opposite effects on Ca2+, H2O2, flavonols, and stomatal movement. Application of exogenous ALA stimulated PP2A activity, which promoted SnRK2.6 dephosphorylation and lower kinase activity in wild-type and transgenic apple leaves. We therefore propose that PP2AC, which dephosphorylates SnRK2.6 and represses its enzyme activity, mediates ALA signaling to inhibit ABA-induced stomatal closure in apple leaves.

MdMYB110a, directly and indirectly, activates the structural genes for the ALA-induced accumulation of anthocyanin in apple.

5-Aminolevulinic acid (ALA), an essential biosynthetic precursor of tetrapyrrole compounds, promotes the anthocyanin accumulation in many plant species. However, the underlying mechanism of ALA-induced accumulation is not yet fully understood. In this study, we identified an important regulator of the anthocyanin accumulation, MdMYB110a, which plays an important role in the ALA-induced anthocyanin accumulation. MdMYB110a activated the expression of MdGSTF12 by binding to its promoter. Additionally, two interacting MdMYB110a proteins, MdWD40-280 and MdHsfB3a, were isolated and confirmed as positive regulators of the ALA-induced anthocyanin accumulation. Both MdWD40-280 and MdHsfB3a enhanced the ability of MdMYB110a to transcribe MdGSTF12. A yeast one-hybrid assay revealed that MdWD40-280 did not bind to most structural genes in the anthocyanin biosynthetic and transport pathways, thus promoting anthocyanin accumulation by MdWD40-280 to depend on MdMYB110a. However, MdHsfB3a could bind to both the MdDFR and MdANS promoters, thereby directly regulating anthocyanin biosynthesis. Collectively, these results provide new insight into the mechanism of ALA-induced anthocyanin accumulation.

Rabbit manure compost as a peat substitute for compound growing media: Proportioning optimization according to physiochemical characteristics and seedling effects.

A large amount of rabbit manure is produced with the development of the rabbit industry, which will cause environmental pollution without proper treatment. Rabbit manure compost may be suitable for seedling cultivation, considering its low moisture, low heavy metal, high lignocellulose, and good fertilizer effect. In this study, a pre-proportioning test of growing media was conducted to optimize the ratio of perlite and vermiculite with peat/rabbit manure compost according to their physicochemical properties. Then, based on the results of the first proportioning optimization, the mixing ratio of rabbit manure compost and peat was further optimized using a bioassay. In this bioassay, salt-tolerant calendula (Calendula officinalis L.) and salt-intolerant cucumber (Cucumis sativus L.) were selected as test plants. The seedling effects (e.g., seedling emergence percentage, plant growth parameters, plant biomass, and nutrient effects) were evaluated. It was shown in the results that the rabbit manure compound growing media could be used for the seedlings, and suitable seedling performance was obtained with the increase of the total porosity (5.0%-61.2%), organic matter content (8.3%-39.9%), and nutrient elements from the rabbit manure compost. From the perspective of seedling emergence, there was no significant difference between rabbit manure compound media and peat treatment, in which the highest emergence percentages were >90%. At the same time, the nutrient performance of plant aboveground was significantly increased in rabbit manure compound growing media compared to peat treatment. In particular, the contents of P and Mg were increased by 31%-141.4% and 80.4%-107.8% for calendula and by 82.6%-117.4% and 35.1%-67.6% for cucumber, respectively. It was indicated in the two-step optimization that the rabbit manure compost proportion of 30%-50% (that is, 60%-100% instead of peat) was more suitable. Additionally, the greenhouse gas emission could be reduced by using rabbit manure compost replacing peat, and the greenhouse gas emission reduction potential would be 3.65 × 105-4.06 × 108 kg CO2-equivalent/year in China, which has important ecological significance.

ALA Upregulates MdPTPA Expression to Increase the PP2A Activity and Promote Stomatal Opening in Apple Leaves.

5-Aminolevulinic acid (ALA) is a new natural plant growth regulator that inhibits abscisic acid (ABA)-induced stomatal closure. Studies have shown that protein phosphatase 2 A (PP2A) is involved in ALA-ABA antagonistically regulating stomatal movement; however, the molecular mechanisms underlying remain unclear. Here, we report that ALA promoted MdPP2A activity and the MdPP2AC expression in the epidermis of apple (Malus × domestica Borkh. cv. Fuji) leaves. Y2H (Yeast two hybrid), BiFC (Bimolecular fluorescence complement), and FLC (Firefly luciferase complementation imaging assay) analysis showed that MdPP2AC interacted with MdPTPA, a phosphortyrosyl phosphatase activator. Furthermore, the transient overexpression or interference-expression of MdPTPA transgenic apple leaves were developed. The results showed that overexpression of MdPTPA promoted stomatal opening by reducing Ca2+ and H2O2 but increasing flavonols in guard cells. Conversely, when the MdPTPA was silenced in transient transgenic apple leaves, the Ca2+, H2O2 and flavonols in guard cells and stomatal movement were completely conversed. In the transgenic apple leaves, exogenous ALA stimulated PP2A but repressed SnRK2.6 activity, while the responses are the same as that in the wild type. Therefore, we propose that MdPTPA, which increases the PP2A activity, mediates ALA signaling to promote stomatal opening in apple leaves.

The Transcription Factor MdERF78 Is Involved in ALA-Induced Anthocyanin Accumulation in Apples.

As a friendly plant growth regulator to the environment, 5-aminolevulinic acid (ALA) has been widely used in plant production, such as fruit coloration, stress resistance, and so on. Previous studies have identified some genes that have a function in the anthocyanin accumulation induced by ALA. However, the regulatory mechanism has not been well revealed. In the current study, we proposed that an ALA-responsive transcription factor, MdERF78, regulated anthocyanin accumulation. MdERF78, overexpressed in apple peels or calli, resulted in a significant increase of anthocyanins, while MdERF78 interference had an opposite trend. Furthermore, the anthocyanin accumulation induced by MdERF78 overexpression was enhanced by exogenous ALA treatment, suggesting that MdERF78 was involved in the ALA-induced anthocyanin accumulation. Yeast one-hybrid and dual luciferase reporter assays revealed that MdERF78 bound to the promoters of MdF3H and MdANS directly and activated their expressions. Additionally, MdERF78 interacted with MdMYB1 and enhanced the transcriptional activity of MdMYB1 to its target gene promoters. Based on these, it can be concluded that MdERF78 has a positive function in ALA-induced anthocyanin accumulation via the MdERF78-MdF3Hpro/MdANSpro and MdERF78-MdMYB1-MdDFRpro/MdUFGTpro/MdGSTF12pro regulatory network. These findings provide new insights into the regulatory mechanism of ALA-promoted anthocyanin accumulation.

MdSCL8 as a Negative Regulator Participates in ALA-Induced FLS1 to Promote Flavonol Accumulation in Apples.

Apples (Malus domestica) are rich in flavonols, and 5-aminolevulinic acid (ALA) plays an important role in the regulation of plant flavonoid metabolism. To date, the underlying mechanism of ALA promoting flavonol accumulation is unclear. Flavonol synthase (FLS) is a key enzyme in flavonol biosynthesis. In this study, we found that ALA could enhance the promoter activity of MdFLS1 in the 'Fuji' apple and improve its expression. With MdFLS1 as bait, we screened a novel transcription factor MdSCL8 by the Yeast One-Hybrid (Y1H) system from the apple cDNA library which we previously constructed. Using luciferase reporter assay and transient GUS activity assay, we verified that MdSCL8 inhibits the activity of MdFLS1 promoter and hinders MdFLS1 expression, thus reducing flavonol accumulation in apple. ALA significantly inhibited MdSCL8 expression. Therefore, ALA promoted the expression of MdFLS1 and the consequent flavonol accumulation probably by down-regulating MdSCL8. We also found that ALA significantly enhanced the gene expression of MdMYB22 and MdHY5, two positive regulators of MdFLS. We further demonstrated that MdMYB22 interacts with MdHY5, but neither of them interacts with MdSCL8. Taken together, our data suggest MdSCL8 as a novel regulator of MdFLS1 and provide important insights into mechanisms of ALA-induced flavonol accumulation in apples.

PLS-DA and Vis-NIR spectroscopy based discrimination of abdominal tissues of female rabbits.

Using Vis-NIR spectroscopy to distinguish gestational sac from other abdominal tissues is the key to diagnosing female rabbits' pregnancy by optical means. This study aims to demonstrate the gestational sac and other abdominal tissues (hair, skin, breast, muscle, cecum, small intestine) of rabbits can be identified using Vis-NIR spectroscopy in vitro. These tissues' raw NIR spectra were recorded in the Vis-NIR range (490-940 nm) with interactive mode. The raw spectra of tissues were analyzed by the principal component analysis (PCA), and were pre-processed using five spectral pre-processing techniques (moving average filter (MF), De-trending (DT), first-order derivative (D1), Multivariate scattering correction (MSC), and standard normal variate (SNV)) to reduce signal noises. The raw and pre-processed spectra were classified using partial least squares discrimination analysis (PLS-DA). Two-way and multi-way PLS-DA model was conducted to understand the classification of each tissue from the gestational sac and to understand the classification of all tissues from the gestational sac, respectively. SNV-PLS-DA model had the best performance, and its multi-way accuracy (Ac), determination coefficients (R2), and Q2 were 0.89, 0.91, 0.77, respectively. The successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS) were used to select characteristic wavelengths (CWs). The SNV-SPA-PLS-DA model with eighteen CWs was better than the SNV-CARS-PLS-DA model. The results showed that Vis-NIR spectroscopy technology combined with PLS-DA could discriminate the gestational sac from the abdominal tissues. This study may help develop an optical diagnosis system for pregnant rabbits.

Early pregnancy diagnosis of rabbits: A non-invasive approach using Vis-NIR spatially resolved spectroscopy.

Pregnancy diagnosis is essential for rabbit's reproductive management. The early identification of non-pregnant rabbits allows for earlier re-insemination, increases the service rate, and reduces the laboring interval in commercial operations. The objective of this study was to establish the feasibility of using a Vis-NIR spatially resolved spectroscopy for diagnosing pregnancy in female rabbits. A total of 141 female rabbits, including 67 pregnant female rabbits (PRs) and 74 non-pregnant female rabbits (NPRs), were measured spectrally between 350 and 1000 nm with different source-detector distances (SDD). Different preprocessing methods were used to transform and enhance the spectral signal. A partial least squares-discriminant analysis (PLS-DA) classification model of the original and preprocessed spectra was established. The highest accuracy of the calibration set and prediction set was 91.75% and 86.05%, respectively. Competitive adaptive reweighted sampling (CARS) and successive projection algorithm (SPA) were used to select characteristic wavelengths from the variables of VIP > 1 (Variable importance in projection),and four classification models were established based on selected wavelengths, including PLS-DA, support vector machine (SVM), K-Nearest Neighbor (KNN) and Naïve Bayes. SPA-SVM was the optimal classification model, the sensitivity, specificity, and accuracy of the validation set and prediction set were 93.18%, 94.44%, 93.88%, 86.96%, 90.00%, 90.69% respectively. The results showed that Vis-NIR spatially resolved spectroscopy combined with classification models could discriminate the PRs and NPRs.

Elimination of Leaf Angle Impacts on Plant Reflectance Spectra Using Fusion of Hyperspectral Images and 3D Point Clouds.

During recent years, hyperspectral imaging technologies have been widely applied in agriculture to evaluate complex plant physiological traits such as leaf moisture content, nutrient level, and disease stress. A critical component of this technique is white referencing used to remove the effect of non-uniform lighting intensity in different wavelengths on raw hyperspectral images. However, a flat white tile cannot accurately reflect the lighting intensity variance on plant leaves, since the leaf geometry (e.g., tilt angles) and its interaction with the illumination severely impact plant reflectance spectra and vegetation indices such as the normalized difference vegetation index (NDVI). In this research, the impacts of leaf angles on plant reflectance spectra were summarized, and an improved image calibration model using the fusion of leaf hyperspectral images and 3D point clouds was built. Corn and soybean leaf samples were imaged at different tilt angles and orientations using an indoor desktop hyperspectral imaging system and analyzed for differences in the NDVI values. The results showed that the leaf's NDVI largely changed with angles. The changing trends with angles differed between the two species. Using measurements of leaf tilt angle and orientation obtained from the 3D point cloud data taken simultaneously with the hyperspectral images, a support vector regression (SVR) model was successfully developed to calibrate the NDVI values of pixels at different angles on a leaf to a same standard as if the leaf was laid flat on a horizontal surface. The R-squared values between the measured and predicted leaf angle impacts were 0.76 and 0.94 for corn and soybean, respectively. This method has a potential to be used in any general plant imaging systems to improve the phenotyping quality.

Transcriptomic Profiling of Apple Calli With a Focus on the Key Genes for ALA-Induced Anthocyanin Accumulation.

The red color is an attractive trait of fruit and determines its market acceptance. 5-Aminolevulinic acid (ALA), an eco-friendly plant growth regulator, has played a universal role in plant secondary metabolism regulation, particularly in flavonoid biosynthesis. It has been widely reported that ALA can up-regulate expression levels of several structural genes related to flavonoid metabolism and anthocyanin accumulation. However, the molecular mechanisms behind ALA-induced expression of these genes are complicated and still far from being completely understood. In this study, transcriptome analysis identified the differentially expressed genes (DEGs) associated with ALA-induced anthocyanin accumulation. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the flavonoid biosynthesis (ko00941) pathway was significantly enhanced in the ALA-treated apple calli at 24, 48, and 72 h after the treatment. Expression pattern revealed that ALA up-regulated the expression of the structural genes related to not only anthocyanin biosynthesis (MdCHS, MdCHI, MdF3'H, MdDFR, MdANS, and MdUFGT) but also anthocyanin transport (MdGST and MdMATE). Two R2R3-MYB transcription factors (MdMYB10 and MdMYB9), which are the known positive regulators of anthocyanin biosynthesis, were significantly induced by ALA. Gene overexpression and RNA interference assays demonstrated that MdMYB10 and MdMYB9 were involved in ALA-induced anthocyanin biosynthesis. Moreover, MdMYB10 and MdMYB9 might positively regulate the transcription of MdMATE8 by binding to the promoter region. These results indicate that MdMYB10 and MdMYB9 modulated structural gene expression of anthocyanin biosynthesis and transport in response to ALA-mediated apple calli coloration at the transcript level. We herein provide new details regarding transcriptional regulation of ALA-induced color development.

Photosynthetic Responses of Canola to Exogenous Application or Endogenous Overproduction of 5-Aminolevulinic Acid (ALA) under Various Nitrogen Levels.

Limited data are available on the effects of 5-aminolevulinic acid (ALA) on plant photosynthesis in relation to the nitrogen (N) level. In this study, we investigate photosynthetic responses to ALA in canola plants (Brassica napus L.). We used wild-type plants without ALA addition (controls), wild-type plants with exogenous ALA application, and transgenic plants that endogenously overproduced ALA. The plants were grown hydroponically in nutrient solutions with low, middle, and high concentrations of N. Our results indicate that plants in both treatment groups had higher chlorophyll contents and net photosynthetic rates and lower intracellular CO2 concentrations in the leaves, as compared to controls. Furthermore, simultaneous measurement of prompt chlorophyll fluorescence and modulated 820-nm reflections showed that the active photosystem II (PS II) reaction centers, electron transfer capacity, and photosystem I (PS I) activity were all higher in treated plants than controls at all N levels; however, the responses of some photochemical processes to ALA were significantly affected by the N level. For example, under low N conditions only, a negative ΔK peak appeared in the prompt chlorophyll fluorescence curve, indicating a protective effect of ALA on electron donation via activation of the oxygen-evolving complex. Taken together, our findings suggest that ALA contributes to the promotion of photosynthesis by regulating photosynthetic electron transport under various N levels. These findings may provide a new strategy for improving photosynthesis in crops grown in N-poor conditions or reduced N-fertilization requirements.

Stress Distribution Analysis on Hyperspectral Corn Leaf Images for Improved Phenotyping Quality.

High-throughput imaging technologies have been developing rapidly for agricultural plant phenotyping purposes. With most of the current crop plant image processing algorithms, the plant canopy pixels are segmented from the images, and the averaged spectrum across the whole canopy is calculated in order to predict the plant's physiological features. However, the nutrients and stress levels vary significantly across the canopy. For example, it is common to have several times of difference among Soil Plant Analysis Development (SPAD) chlorophyll meter readings of chlorophyll content at different positions on the same leaf. The current plant image processing algorithms cannot provide satisfactory plant measurement quality, as the averaged color cannot characterize the different leaf parts. Meanwhile, the nutrients and stress distribution patterns contain unique features which might provide valuable signals for phenotyping. There is great potential to develop a finer level of image processing algorithm which analyzes the nutrients and stress distributions across the leaf for improved quality of phenotyping measurements. In this paper, a new leaf image processing algorithm based on Random Forest and leaf region rescaling was developed in order to analyze the distribution patterns on the corn leaf. The normalized difference vegetation index (NDVI) was used as an example to demonstrate the improvements of the new algorithm in differentiating between different nitrogen stress levels. With the Random Forest method integrated into the algorithm, the distribution patterns along the corn leaf's mid-rib direction were successfully modeled and utilized for improved phenotyping quality. The algorithm was tested in a field corn plant phenotyping assay with different genotypes and nitrogen treatments. Compared with the traditional image processing algorithms which average the NDVI (for example) throughout the whole leaf, the new algorithm more clearly differentiates the leaves from different nitrogen treatments and genotypes. We expect that, besides NDVI, the new distribution analysis algorithm could improve the quality of other plant feature measurements in similar ways.

Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants.

The normalized difference vegetation index (NDVI) is widely used in remote sensing to monitor plant growth and chlorophyll levels. Usually, a multispectral camera (MSC) or hyperspectral camera (HSC) is required to obtain the near-infrared (NIR) and red bands for calculating NDVI. However, these cameras are expensive, heavy, difficult to geo-reference, and require professional training in imaging and data processing. On the other hand, the RGBN camera (NIR sensitive RGB camera, simply modified from standard RGB cameras by removing the NIR rejection filter) have also been explored to measure NDVI, but the results did not exactly match the NDVI from the MSC or HSC solutions. This study demonstrates an improved NDVI estimation method with an RGBN camera-based imaging system (Ncam) and machine learning algorithms. The Ncam consisted of an RGBN camera, a filter, and a microcontroller with a total cost of only $70 ~ 85. This new NDVI estimation solution was compared with a high-end hyperspectral camera in an experiment with corn plants under different nitrogen and water treatments. The results showed that the Ncam with two-band-pass filter achieved high performance (R2 = 0.96, RMSE = 0.0079) at estimating NDVI with the machine learning model. Additional tests showed that besides NDVI, this low-cost Ncam was also capable of predicting corn plant nitrogen contents precisely. Thus, Ncam is a potential option for MSC and HSC in plant phenotyping projects.

Genome-wide identification and comparative analysis of GST gene family in apple (Malus domestica) and their expressions under ALA treatment.

Anthocyanins, a subclass of flavonoids, are synthesized at the cytoplasmic surface of the endoplasmic reticulum (ER), which then accumulate in vacuoles. Plant glutathione S-transferase (GST) genes are involved in anthocyanin transportation. Here, a total of 52, 42, 50, and 29 GST genes were identified from apple, pear, peach, and strawberry, respectively, through a comprehensive genome-wide survey. Based on phylogenetic analyses, the GST proteins of the four crops could be divided into the classes Phi, Tau, DHAR, TCHQD, and Lambda. The structure and chromosomal distribution of apple GST genes were further analyzed. The GST gene family expansion in apple likely occurred through tandem duplications, and purifying selection played a pivotal role in the evolution of GST genes. Synteny analysis showed strong microsynteny between apple and Arabidopsis/strawberry, but no microsynteny was detected between apple/strawberry/Arabidopsis and rice. Aminolevulinic acid (ALA), a key precursor of tetrapyrrole compounds, can significantly improve anthocyanin accumulation in fruits, Using RNA-seq and qRT-PCR analysis, we found that ALA treatment led to the differential expression of GST genes in apples. MdGSTF12 was strongly induced by ALA, suggesting that MdGSTF12 may play a role in ALA-induced anthocyanin accumulation. These results provide a detailed overview of GST genes in four Rosaceae species and indicate that GSTs are involved in ALA-induced anthocyanin accumulation.

LeafScope: A Portable High-Resolution Multispectral Imager for In Vivo Imaging Soybean Leaf.

Portable devices for measuring plant physiological features with their isolated measuring chamber are playing an increasingly important role in plant phenotyping. However, currently available commercial devices of this type, such as soil plant analysis development (SPAD) meter and spectrometer, are dot meters that only measure a small region of the leaf, which does not perfectly represent the highly varied leaf surface. This study developed a portable and high-resolution multispectral imager (named LeafScope) to in-vivo image a whole leaf of dicotyledon plants while blocking the ambient light. The hardware system is comprised of a monochrome camera, an imaging chamber, a lightbox with different bands of light-emitting diodes (LEDs) array, and a microcontroller. During measuring, the device presses the leaf to lay it flat in the imaging chamber and acquires multiple images while alternating the LED bands within seconds in a certain order. The results of an experiment with soybean plants clearly showed the effect of nitrogen and water treatments as well as the genotype differences by the color and morphological features from image processing. We conclude that the low cost and easy to use LeafScope can provide promising imaging quality for dicotyledon plants, so it has great potential to be used in plant phenotyping.

Transcriptomic Analysis of Ficus carica Peels with a Focus on the Key Genes for Anthocyanin Biosynthesis.

Fig (Ficus carica L.), a deciduous fruit tree of the Moraceae, provides ingredients for human health such as anthocyanins. However, little information is available on its molecular structure. In this study, the fig peels in the yellow (Y) and red (R) stages were used for transcriptomic analyses. Comparing the R with the Y stage, we obtained 6224 differentially expressed genes, specifically, anthocyanin-related genes including five CHS, three CHI, three DFR, three ANS, two UFGT and seven R2R3-MYB genes. Furthermore, three anthocyanin biosynthetic genes, i.e., FcCHS1, FcCHI1 and FcDFR1, and two R2R3-MYB genes, i.e., FcMYB21 and FcMYB123, were cloned; sequences analysis and their molecular characteristics indicated their important roles in fig anthocyanin biosynthesis. Heterologous expression of FcMYB21 and FcMYB123 significantly promoted anthocyanin accumulation in both apple fruits and calli, further suggesting their regulatory roles in fig coloration. These findings provide novel insights into the molecular mechanisms behind fig anthocyanin biosynthesis and coloration, facilitating the genetic improvement of high-anthocyanin cultivars and other horticultural traits in fig fruits.