Increased Gibberellins and Light Levels Promotes Cell Wall Thickness and Enhance Lignin Deposition in Xylem Fibers

Light intensity and hormones (gibberellins; GAs) alter plant growth and development. A fine regulation triggered by light and GAs induces changes in stem cell walls (CW). Cross-talk between light-stimulated and GAs-induced processes as well as the phenolic compounds metabolism leads to modifications in lignin formation and deposition on cell walls. How these factors (light and GAs) promote changes in lignin content and composition. In addition, structural changes were evaluated in the stem anatomy of tobacco plants. GA3 was sprayed onto the leaves and paclobutrazol (PAC), a GA biosynthesis inhibitor, via soil, at different irradiance levels. Fluorescence microscopy techniques were applied to detect lignin, and electron microscopy (SEM and TEM) was used to obtain details on cell wall structure. Furthermore, determination of total lignin and monomer contents were analyzed. Both light and GAs induces increased lignin content and CW thickening as well as greater number of fiber-like cells but not tracheary elements. The assays demonstrate that light exerts a role in lignification under GA3 supplementation. In addition, the existence of an exclusive response mechanism to light was detected, that GAs are not able to replace

Physiological response of Conilon coffee clone sensitive to drought grafted onto tolerant rootstock

O objetivo deste trabalho foi determinar alterações fisiológicas e de tolerância à seca em clones de café Conilon (Coffea canephora) contrastantes quanto à sensibilidade ao deficit hídrico. Foram avaliadas as enxertias recíprocas entre os clones 109A, sensível ao deficit hídrico, e 120, tolerante – 120/109A, 120/120, 109A/120, 109A/109A –, além de seus respectivos pés-francos. As plantas foram cultivadas em vasos de 12 L em casa de vegetação. Após seis meses, metade das plantas foi submetida ao deficit hídrico por meio da suspensão da irrigação, até que as folhas atingissem o potencial hídrico de antemanhã de -3,0 MPa. Quando o clone 120 foi usado como porta-enxerto, as plantas apresentaram sistema radicular mais profundo, mas com menor massa, retardaram por mais tempo a desidratação celular das folhas e apresentaram maior eficiência no uso da água. Sob seca severa, os teores de amido e sacarose decresceram em todos os tratamentos, enquanto os teores de glicose, frutose, aminoácidos totais e prolina aumentaram, particularmente nos tratamentos 109A pé-franco, 109A/109A e 120/109A. Essas plantas apresentaram menor eficiência no uso da água. O acúmulo de solutos não foi associado à tolerância à seca. O uso de porta-enxertos tolerantes à seca contribui para a maior tolerância das plantas ao deficit hídrico.The objective of this work was to determine alterations in physiology and those due to drought tolerance on Conilon coffee (Coffea canephora) contrasting clones regarding the sensitivity to hydric stress. The reciprocal grafting between clones 109A, drought sensitive, and 120, drought tolerant, – 120/109A, 120/120, 109A/120, 109A/109A – along with their ungrafted control plants (109A and 120) were evaluated. Plants were cultivated in 12-L vases in greenhouse. Six months after grafting, half of the plants was subjected to water deficit, by suspending irrigation until leaves reached the hydric potential of -3,0 MPa. When clone 120 was used as rootstock, plants presented deeper roots, although with lower root-biomass, higher ability to postpone leaf dehydration and higher instantaneous water-use efficiency (WUE). Under severe drought, starch and sucrose contents decreased similarly, regardless of the treatment, whereas leaf concentrations of glucose, fructose, total amino acids and proline were higher in non-grafted 109A, 109A/109A, and 120/109A plants. These plants showed the lowest WUE values. Solute accumulation was not primarily related to drought tolerance. The use of drought tolerant rootstocks improves to drought tolerance in coffee

Physiological changes in potato plants with altered sucrose metabolism

A importância relativa da sacarose na osmorregulação das células- guarda (CG) bem como o papel fisiológico da sintase da sacarose (SuSy) em folhas permanece pouco entendido. Neste trabalho, foram investigadas estas questões via análises dos efeitos da modulação da atividade sacarolítica em CG e, conjuntamente, com uma caracterização fenotípica dos efeitos da redução da expressão do gene da SuSy em plantas transgênicas. Análises de trocas gasosas e de parâmetros biométricos em plantas de batata (Solanum tuberosum L. Désirée) transgênicas antisenso da isoforma SuSy 3, sob controle do promotor constitutivo CaMV 35S, e plantas com superexpressão do gene de invetase de levedura sob controle do promotor S1Δ4, específico de CG, foram investigadas. Por um lado, observou-se redução da condutância estomática (g s ) e uma ligeira redução na taxa da assimilação líquida de CO 2 (A) com a redução na atividade sacarolítica em CG (i.e., plantas SuSy 3 antisenso); o fenótipo oposto foi observado nas plantas transgênicas com aumento da atividade sacarolítica especificamente em CG (i.e., plantas com superexpressão da invertase). Os aumentos em A nas plantas com superexpressão da invertase pôde ser explicado como resultante de menores limitações estomáticas à fotossíntese, em relação aos das plantas-controle. Entretanto, as mudanças em A não foram relacionadas com alterações nas taxas máximas de assimilação do CO 2 derivadas de curvas A/C i daqueles genótipos. A redução moderada em A nas plantas SuSy 3 antisenso foi acompanhada por incrementos na área foliar e massa seca da parte aérea, o quê, provavelmente, poderia estar relacionada com a redução na densidade dos tubérculos. Ainda, plantas SuSy 3 antisenso apresentaram aumentos na atividade da sintase da sacarose-fosfato (SPS) e pirofosforilase da ADP-glicose (AGPase), e um decréscimo na atividade da SuSy e invertases ácidas, refletindo em aumentos nos teores de sacarose e amido nas folhas. Os aumentos nas atividades da SPS e da AGPase podem estar ligados à redução no teores de ortofosfato inorgânico. Não foram observads mudanças significativas na composição da parede celular do limbo foliar. Por outro lado, nas plantas com superexpressão da invertase, nenhuma das mudanças nas atividades enzimáticas e nos níveis de açúcares analisados foi observada. Ressalta-se um incremento nos teores do ácido 3-fosfoglicérico e hexoses-P. Analisando-se em conjunto, estes resultados suportam a hipótese de que mudanças em g s foram principalmente devido a mudanças no metabolismo de sacarose, exclusivamente em CG. Não se obteve evidências, neste trabalho, de que a SuSy 3 possa estar envolvida significativamente na síntese de parede celular nas folhas.The relative importance of sucrose in guard-cell (GC) osmoregulation as well as the physiological role of sucrose synthase (SuSy) in leaves is still not understood. In this work, these questions were addressed by analyzing the effects of modulation of sucrolitic activities in GC, in addition to phenotypically characterizing the effects of its gene expression downregulation in transgenic plants. Detailed analysis of gas exchange and growth parameters of antisense potato plant (Solanum tuberosum L. cv. Désirée) for isoform 3 of SuSy (SuSy 3), under the control of 35S promoter, and sense potato plants expressing yeast invertase under the control of the S1Δ4, GC-specific promoter, were performed. Stomatal conductance (g s ) decreased to a greater extent than the net CO 2 assimilation rate (A) in transgenic plants with reduction in sucrolitic activity in GC (i.e., SuSy 3 antisense plants); an opposite phenotype was found in transgenic plants with increased sucrolitic activity exclusively in GC (i.e., sense invertase plants). The increase in A in sense invertase plants could be explained as a result of smaller stomatal restrictions to photosynthesis than in control plants. However, changes in A were not followed by changes in maximal net carbon assimilation rates, as obtained from A/C i curves. The moderate decrease in A in SuSy 3 antisense plants was accompanied by an increase in leaf both area and dry weight of leaves and stem, which probably could be linked to a reduction in total tuber density. Leaves from SuSy 3 antisense plants showed increases in sucrose-phosphate synthase (SPS) and ADP-glucose pyrophosphorylase (AGPase), and decreases in SuSy and acid invertases activities. The enzymatic changes led to increases in leaf sucrose and starch levels. The increase in SPS and AGPase activities could be linked to a reduction in inorganic orthophosphate content. There were no significant changes in both cellulose levels and cell-wall composition. None of these changes in plants expressing yeast invertase were found, but a significant increase in phosphoglyceric acid and hexoses-P contents was observed. Taken together, these results support the hypothesis that changes in g s is due mainly to changes in sucrose metabolism exclusively in GC; also, no evidence for an important role of SuSy 3 isoform in cell-wall synthesis in leaves could be herein found

Transformação genética visando resistência à seca: plantas de tabaco transgênicas antisenso do transportador de sacarose apresentam menor condutância estomática e aumento na eficiência do uso da água

It was evaluated the importance of guard cell (GC) sucrose transporter and the role of sucrose as osmotic on GC. We transformed tobacco plants with antisense gene construct for sucrose transporter driven by KST1, GC specific promoter. Transgenic plants GC have less sucrose, more starch and modest increase in K + contents. Low sucrose contents in GC of transgenic lines were associated with low stomatal conductance (g s ), suggesting the importance of sucrose transporter and symplastic sucrose in maintaining low osmotic potential on GC. It was observed rapid starch disappearance when the guard cells are swelling, fact not observed in control plants. By means of low g s tobacco plants demonstrated diffusional (stomatal) restriction of photosynthesis (A), low transpiration rate (E) and low sub-stomatal CO 2 concentration, high A/E and higher carbon rate composition (δ 13 C). However, higher A/E was associated with lower A, consequently, a slower crop growth rate, but not smaller “efficiency index” as showed by relative growth rate. The δ 13 C data confirms the low conductance, showing that it represents a common stomata behavior over all plant development. By means of low g s tobacco plants, we got desiccation postponement phenotype as principal feature of this transformation, being high water saving plants. These results suggest that manipulation of sucrose transport in GC may be developed as a practical mechanism for drought avoidance and water conservation during irrigation. These results illustrate the importance of fine tuning of sucrose metabolism transport and metabolism in the fitness of stomatal function in contributing to plant survival or growth under unfavorable water conditions.Nesse trabalho foi avaliada a importância do transportador de sacarose especificamente em células guarda (CG) e o papel da sacarose sobre os movimentos estomáticos. Utilizou-se plantas de tabaco transformadas com o antisenso do gene do transportador de sacarose sob controle do promotor KST1, específico de GC. As CG das plantas transgênicas apresentaram menores teores de sacarose, maiores nos de amido e um modesto incremento nos de K + . O menor conteúdo de sacarose nas CG das plantas transgênicas esteve associado com menores valores de condutância estomática (g s ). Essa associação sugere a importância da sacarose no simplasto na manutenção de baixos potenciais osmóticos nas CG. Foi observada uma rápida redução nos teores de amido quando os estômatos estavam se abrindo, fato não observado nas plantas não-transformadas. Nas plantas transformadas, com menor g s , foi possível demonstrar uma restrição difusional (estomática) à fotossíntese (A). As plantas transformadas também apresentaram menor taxa de transpiração (E) e menor concentração de CO 2 na câmara sub-estomática, além de maiores valores da razão de composição isotópica (δ 13 C). Entretanto, maiores valores da razão A/E esteve associado com menores valores de A, conseqüentemente, a uma menor taxa de crescimento, porém não a uma menor eficiência baseada nas taxas de crescimento relativas. Os dados de δ 13 C confirmaram a menor g s e reforçam que esse fenótipo se prolongou pelo desenvolvimento das plantas. Por meio de plantas de tabaco com menor g s foi possível demonstrar que o fenótipo de retardamento à seca foi a principal característica desta transformação, proporcionando as plantas transgênicas um menor consumo de água. Os resultados sugerem que a manipulação do transporte de sacarose em CG foi um mecanismo prático e efetivo na aquisição de plantas mais resistentes à seca.Conselho Nacional de Desenvolvimento Científico e Tecnológic

Rapid Quantification Method for Yield, Calorimetric Energy and Chlorophyll a Fluorescence Parameters in Nicotiana tabacum L. Using Vis-NIR-SWIR Hyperspectroscopy

High-throughput and large-scale data are part of a new era of plant remote sensing science. Quantification of the yield, energetic content, and chlorophyll a fluorescence (ChlF) remains laborious and is of great interest to physiologists and photobiologists. We propose a new method that is efficient and applicable for estimating photosynthetic performance and photosystem status using remote sensing hyperspectroscopy with visible, near-infrared and shortwave spectroscopy (Vis-NIR-SWIR) based on rapid multivariate partial least squares regression (PLSR) as a tool to estimate biomass production, calorimetric energy content and chlorophyll a fluorescence parameters. The results showed the presence of typical inflections associated with chemical and structural components present in plants, enabling us to obtain PLSR models with R2P and RPDP values greater than >0.82 and 3.33, respectively. The most important wavelengths were well distributed into 400 (violet), 440 (blue), 550 (green), 670 (red), 700–750 (red edge), 1330 (NIR), 1450 (SWIR), 1940 (SWIR) and 2200 (SWIR) nm operating ranges of the spectrum. Thus, we report a methodology to simultaneously determine fifteen attributes (i.e., yield (biomass), ΔH°area, ΔH°mass, Fv/Fm, Fv’/Fm’, ETR, NPQ, qP, qN, ΦPSII, P, D, SFI, PI(abs), D.F.) with high accuracy and precision and with excellent predictive capacity for most of them. These results are promising for plant physiology studies and will provide a better understanding of photosystem dynamics in tobacco plants when a large number of samples must be evaluated within a short period and with remote acquisition data

A Novel Method for Estimating Chlorophyll and Carotenoid Concentrations in Leaves: A Two Hyperspectral Sensor Approach

Leaf optical properties can be used to identify environmental conditions, the effect of light intensities, plant hormone levels, pigment concentrations, and cellular structures. However, the reflectance factors can affect the accuracy of predictions for chlorophyll and carotenoid concentrations. In this study, we tested the hypothesis that technology using two hyperspectral sensors for both reflectance and absorbance data would result in more accurate predictions of absorbance spectra. Our findings indicated that the green/yellow regions (500–600 nm) had a greater impact on photosynthetic pigment predictions, while the blue (440–485 nm) and red (626–700 nm) regions had a minor impact. Strong correlations were found between absorbance (R2 = 0.87 and 0.91) and reflectance (R2 = 0.80 and 0.78) for chlorophyll and carotenoids, respectively. Carotenoids showed particularly high and significant correlation coefficients using the partial least squares regression (PLSR) method (R2C = 0.91, R2cv = 0.85, and R2P = 0.90) when associated with hyperspectral absorbance data. Our hypothesis was supported, and these results demonstrate the effectiveness of using two hyperspectral sensors for optical leaf profile analysis and predicting the concentration of photosynthetic pigments using multivariate statistical methods. This method for two sensors is more efficient and shows better results compared to traditional single sensor techniques for measuring chloroplast changes and pigment phenotyping in plants

Reflectance Spectroscopy for the Classification and Prediction of Pigments in Agronomic Crops

Reflectance spectroscopy, in combination with machine learning and artificial intelligence algorithms, is an effective method for classifying and predicting pigments and phenotyping in agronomic crops. This study aims to use hyperspectral data to develop a robust and precise method for the simultaneous evaluation of pigments, such as chlorophylls, carotenoids, anthocyanins, and flavonoids, in six agronomic crops: corn, sugarcane, coffee, canola, wheat, and tobacco. Our results demonstrate high classification accuracy and precision, with principal component analyses (PCAs)-linked clustering and a kappa coefficient analysis yielding results ranging from 92 to 100% in the ultraviolet–visible (UV–VIS) to near-infrared (NIR) to shortwave infrared (SWIR) bands. Predictive models based on partial least squares regression (PLSR) achieved R2 values ranging from 0.77 to 0.89 and ratio of performance to deviation (RPD) values over 2.1 for each pigment in C3 and C4 plants. The integration of pigment phenotyping methods with fifteen vegetation indices further improved accuracy, achieving values ranging from 60 to 100% across different full or range wavelength bands. The most responsive wavelengths were selected based on a cluster heatmap, β-loadings, weighted coefficients, and hyperspectral vegetation index (HVI) algorithms, thereby reinforcing the effectiveness of the generated models. Consequently, hyperspectral reflectance can serve as a rapid, precise, and accurate tool for evaluating agronomic crops, offering a promising alternative for monitoring and classification in integrated farming systems and traditional field production. It provides a non-destructive technique for the simultaneous evaluation of pigments in the most important agronomic plants

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

VIS-NIR-SWIR Hyperspectroscopy Combined with Data Mining and Machine Learning for Classification of Predicted Chemometrics of Green Lettuce

VIS-NIR-SWIR hyperspectroscopy is a significant technique used in remote sensing for classification of prediction-based chemometrics and machine learning. Chemometrics, together with biophysical and biochemical parameters, is a laborious technique; however, researchers are very interested in this field because of the benefits in terms of optimizing crop yields. In this study, we investigated the hypothesis that VIS-NIR-SWIR could be efficiently applied for classification and prediction of leaf thickness and pigment profiling of green lettuce in terms of reflectance, transmittance, and absorbance data according to the variety. For this purpose, we used a spectroradiometer in the visible, near-infrared, and shortwave ranges (VIS-NIR-SWIR). The results showed many chemometric parameters and fingerprints in the 400–2500 nm spectral curve range. Therefore, this technique, combined with rapid data mining, machine learning algorithms, and other multivariate statistical analyses such as PCA, MCR, LDA, SVM, KNN, and PLSR, can be used as a tool to classify plants with the highest accuracy and precision. The fingerprints of the hyperspectral data indicated the presence of functional groups associated with biophysical and biochemical components in green lettuce, allowing the plants to be correctly classified with higher accuracy (99 to 100%). Biophysical parameters such as thickness could be predicted using PLSR models, which showed R2P and RMSEP values greater than >0.991 and 6.21, respectively, according to the relationship between absorbance and reflectance or transmittance spectroscopy curves. Thus, we report the methodology and confirm the ability of VIS-NIR-SWIR hyperspectroscopy to simultaneously classify and predict data with high accuracy and precision, at low cost and with rapid acquisition, based on a remote sensing tool, which can enable the successful management of crops such as green lettuce and other plants using precision agriculture systems

VIS-NIR-SWIR Hyperspectroscopy Combined with Data Mining and Machine Learning for Classification of Predicted Chemometrics of Green Lettuce

VIS-NIR-SWIR hyperspectroscopy is a significant technique used in remote sensing for classification of prediction-based chemometrics and machine learning. Chemometrics, together with biophysical and biochemical parameters, is a laborious technique; however, researchers are very interested in this field because of the benefits in terms of optimizing crop yields. In this study, we investigated the hypothesis that VIS-NIR-SWIR could be efficiently applied for classification and prediction of leaf thickness and pigment profiling of green lettuce in terms of reflectance, transmittance, and absorbance data according to the variety. For this purpose, we used a spectroradiometer in the visible, near-infrared, and shortwave ranges (VIS-NIR-SWIR). The results showed many chemometric parameters and fingerprints in the 400–2500 nm spectral curve range. Therefore, this technique, combined with rapid data mining, machine learning algorithms, and other multivariate statistical analyses such as PCA, MCR, LDA, SVM, KNN, and PLSR, can be used as a tool to classify plants with the highest accuracy and precision. The fingerprints of the hyperspectral data indicated the presence of functional groups associated with biophysical and biochemical components in green lettuce, allowing the plants to be correctly classified with higher accuracy (99 to 100%). Biophysical parameters such as thickness could be predicted using PLSR models, which showed R2P and RMSEP values greater than >0.991 and 6.21, respectively, according to the relationship between absorbance and reflectance or transmittance spectroscopy curves. Thus, we report the methodology and confirm the ability of VIS-NIR-SWIR hyperspectroscopy to simultaneously classify and predict data with high accuracy and precision, at low cost and with rapid acquisition, based on a remote sensing tool, which can enable the successful management of crops such as green lettuce and other plants using precision agriculture systems