Comparative Analysis Delineates the Transcriptional Resistance Mechanisms for Pod Borer Resistance in the Pigeonpea Wild Relative Cajanus scarabaeoides (L.) Thouars

Enhancing Pigment Phenotyping and Classification in Lettuce through the Integration of Reflectance Spectroscopy and AI Algorithms

In this study, we investigated the use of artificial intelligence algorithms (AIAs) in combination with VIS-NIR-SWIR hyperspectroscopy for the classification of eleven lettuce plant varieties. For this purpose, a spectroradiometer was utilized to collect hyperspectral data in the VIS-NIR-SWIR range, and 17 AIAs were applied to classify lettuce plants. The results showed that the highest accuracy and precision were achieved using the full hyperspectral curves or the specific spectral ranges of 400-700 nm, 700-1300 nm, and 1300-2400 nm. Four models, AdB, CN2, G-Boo, and NN, demonstrated exceptional R² and ROC values, exceeding 0.99, when compared between all models and confirming the hypothesis and highlighting the potential of AIAs and hyperspectral fingerprints for efficient, precise classification and pigment phenotyping in agriculture. The findings of this study have important implications for the development of efficient methods for phenotyping and classification in agriculture and the potential of AIAs in combination with hyperspectral technology. To advance our understanding of the capabilities of hyperspectroscopy and AIs in precision agriculture and contribute to the development of more effective and sustainable agriculture practices, further research is needed to explore the full potential of these technologies in different crop species and environments.

Different responses of two maize cultivars to Spodoptera frugiperda (Lepidoptera: Noctuidae) larvae infestation provide insights into their differences in resistance

Spodoptera frugiperda (Lepidoptera: Noctuidae), a pest with an amazing appetite, damages many crops and causes great losses, especially maize. Understanding the differences in different maize cultivars' responses to S. frugiperda infestation is very important for revealing the mechanisms involved in the resistance of maize plants to S. frugiperda. In this study, a comparative analysis of two maize cultivars, the common cultivar 'ZD958' and the sweet cultivar 'JG218', was used to investigate their physico-biochemical responses to S. frugiperda infestation by a pot experiment. The results showed that the enzymatic and non-enzymatic defense responses of maize seedlings were rapidly induced by S. frugiperda. Frist, the hydrogen peroxide (H₂O₂) and malondialdehyde (MDA) contents of infested maize leaves were significantly increased and then decreased to the level of the control. Furthermore, compared with the control leaves, the puncture force values and the total phenolics, total flavonoids, and 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one contents of infested leaves were significantly increased within a certain time. The superoxide dismutase and peroxidase activities of infested leaves were significantly increased in a certain period of time, while the catalase activities decreased significantly and then increased to the control level. The jasmonic acid (JA) levels of infested leaves were significantly improved, whereas the salicylic acid and abscisic acid levels changed less. Signaling genes associated with phytohormones and defensive substances including PAL4, CHS6, BX12, LOX1, and NCED9 were significantly induced at certain time points, especially LOX1. Most of these parameters changed greater in JG218 than in ZD958. Moreover, the larvae bioassay showed that S. frugiperda larvae weighed more on JG218 leaves than those on ZD958 leaves. These results suggested that JG218 was more susceptible to S. frugiperda than ZD958. Our findings will make it easier to develop strategies for controlling S. frugiperda for sustainable maize production and breeding of new maize cultivars with increased resistance to herbivores.

Classification and Prediction by Pigment Content in Lettuce (Lactuca sativa L.) Varieties Using Machine Learning and ATR-FTIR Spectroscopy

Green or purple lettuce varieties produce many secondary metabolites, such as chlorophylls, carotenoids, anthocyanins, flavonoids, and phenolic compounds, which is an emergent search in the field of biomolecule research. The main objective of this study was to use multivariate and machine learning algorithms on Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR)-based spectra to classify, predict, and categorize chemometric attributes. The cluster heatmap showed the highest efficiency in grouping similar lettuce varieties based on pigment profiles. The relationship among pigments was more significant than the absolute contents. Other results allow classification based on ATR-FTIR fingerprints of inflections associated with structural and chemical components present in lettuce, obtaining high accuracy and precision (>97%) by using principal component analysis and discriminant analysis (PCA-LDA)-associated linear LDA and SVM machine learning algorithms. In addition, PLSR models were capable of predicting Chla, Chlb, Chla+b, Car, AnC, Flv, and Phe contents, with R2P and RPDP values considered very good (0.81−0.88) for Car, Anc, and Flv and excellent (0.91−0.93) for Phe. According to the RPDP metric, the models were considered excellent (>2.10) for all variables estimated. Thus, this research shows the potential of machine learning solutions for ATR-FTIR spectroscopy analysis to classify, estimate, and characterize the biomolecules associated with secondary metabolites in lettuce.

Identification of dynamic microRNA associated with systemic defence against Helicoverpa armigera infestation in Cajanus scarabaeoides

BACKGROUND

Helicoverpa armigera is a major insect pest of several crop plants, including pigeonpea. Resistant gene sources are not available in the cultivated gene pool, but resistance has been observed in its crop wild relative, Cajanus scarabaeoides. Gene regulatory mechanisms governing the systemic immune response of this plant to pod borer infestation have not yet been deciphered. MicroRNA (miRNA) profiles of H. armigera-infested and undamaged adjacent leaves of C. scarabaeoides were compared to gain an insight into the plant-insect interactions and to identify dynamic miRNA molecules potentially acting as mediators of systemic defence responses.

RESULTS

A total of 211 conserved, temporally dynamic miRNA were identified in the unfed adjacent leaves, out of which 98 were found to be differentially expressed in comparison to control leaves. On further analysis, most of the miRNA detected in the adjacent leaves was found to target genes involved in the defence pathways and plant immune response. An overlap of the differentially expressing miRNAs was observed between insect-fed and adjacent unfed leaves, indicating the transmission of signal from the site of infestation to the undamaged parts of the plant, indicative of induction of a systemic defence response.

CONCLUSION

The miRNA response in the unfed leaves had the signatures of induced changes in metabolism and signal transduction for induction of defence pathway genes. This study reveals the participation of miRNAs in imparting pod borer resistance and mounting a systemic defence response against pod borer infestation in C. scarabaeoides. © 2022 Society of Chemical Industry.

Simple, Fast and Efficient Methods for Analysing the Structural, Ultrastructural and Cellular Components of the Cell Wall

Plant cell walls are a fundamental component of plant biology and play an essential role in plant growth and development. The metabolic components of the cell wall can be investigated in a fast, simple, and highly efficient manner using various and distinct microscopy techniques. Here, we report implementing a flowchart to analyse tobacco plants’ structural, ultrastructural, and metabolic components supplemented with far-red light. In addition, biochemical components, such as lignin, cellulose, phenolic compounds, and reducing sugars, present in the plant cell walls were quantified using light, fluorescence, and electron microscopy. Our data were generated from samples prepared via tissue fixation, incorporation in resins, and slicing using microtomes. Moreover, we have used routine staining and contrast techniques to characterise plant cell walls. Here, we describe several protocols that use classic and modern techniques as well as qualitative and quantitative analytical methods to study cell walls, enabling the plant research community to understand and select the most suitable methods for the microscopic analysis of metabolic components. Finally, we discuss specific ideas aimed at new students of plant anatomy and microscopy. This research not only described the structural, ultrastructural, and metabolic components of the plant cell wall, but also explained the strategies for understanding cellular development.

Comparative analysis of herbivory responsive miRNAs to delineate pod borer (Helicoverpa armigera) resistance mechanisms in Cajanus cajan and its wild relative Cajanus scarabaeoides

Comparative analysis of herbivory responsive miRNAs between pod borer susceptible C. cajan and its resistant Crop Wild Relative (CWR) C. scarabaeoides revealed miRNA-based regulation of defense genes and plant-insect interactions. Gram pod borer (Helicoverpa armigera) is one of most devastating pests of pigeon pea (Cajanus cajan) worldwide, responsible for huge losses in crop productivity. The lack of genes conferring resistance to pod borer in pigeon pea has proven to be a bottleneck for its improvement. One of its CWR, C. scarabaeoides has demonstrated resistance to this pest and can be exploited for developing pest resistant crop varieties. Differences in expression patterns of herbivory responsive microRNAs in the susceptible C. cajan and resistant C. scarabaeoides after different time duration of pod borer infestation (2 h, 8 h and 18 h) were identified, characterized and functionally validated to understand their role in insect defense response. A total of 462 conserved and 449 novel miRNAs and 273 conserved and 185 novel miRNAs, were identified in C. cajan and C. scarabaeoides, respectively. Among the identified miRNAs, 65, 68 and 65 miRNAs were found to be differentially expressing between the C. scarabaeoides and C. cajan libraries 2 h, 8 h and 18 h post infestation, respectively. These miRNAs were found to target genes involved in a number of pathways contributing to defense and acquired resistance in C. scarabaeoides against pod borer, indicating miRNA-based regulation of defense pathways. Expression patterns of eight of these miRNAs were validated by qRT-PCR. This study provides novel insights into the miRNA-mediated plant-insect interactions and the mechanisms of regulatory pathways involved in insect defense. These findings can be utilized for further exploring the mechanism of herbivore defense in plant systems.

Comparative TMT Proteomic Analysis Unveils Unique Insights into Helicoverpa armigera (Hübner) Resistance in Cajanus scarabaeoides (L.) Thouars

Pigeonpea [Cajanus cajan (L.) Millspaugh] is an economically important legume playing a crucial role in the semi-arid tropics. Pigeonpea is susceptible to Helicoverpa armigera (Hübner), which causes devastating yield losses. This pest is developing resistance to many commercially available insecticides. Therefore, crop wild relatives of pigeonpea, are being considered as potential sources of genes to expand the genetic base of cultivated pigeonpea to improve traits such as host plant resistance to pests and pathogens. Quantitative proteomic analysis was conducted using the tandem mass tag platform to identify differentially abundant proteins between IBS 3471 and ICPL 87 tolerant accession and susceptible variety to H. armigera, respectively. Leaf proteome were analysed at the vegetative and flowering/podding growth stages. H. armigera tolerance in IBS 3471 appeared to be related to enhanced defence responses, such as changes in secondary metabolite precursors, antioxidants, and the phenylpropanoid pathway. The development of larvae fed on an artificial diet with IBS 3471 lyophilised leaves showed similar inhibition with those fed on an artificial diet with quercetin concentrations with 32 mg/25 g of artificial diet. DAB staining (3,3′-diaminobenzidine) revealed a rapid accumulation of reactive oxygen species in IBS 3471. We conclude that IBS 3471 is an ideal candidate for improving the genetic base of cultivated pigeonpea, including traits for host plant resistance.