Growth dynamics and morphological changers in Solanum lycopersicum induced by rhizobacterial inoculation

This study investigates the effects of lead stress on tomato plants and explores the potential role of plant growth-promoting rhizobacteria (PGPR) to alleviate this stress. The experiment was conducted in pots, introducing varying lead levels (0, 100, 200, 300, 400, and 500 mg kg⁻¹) using lead nitrate. For rhizobacterial inoculation, pre-characterized LTPGP strains S5 Pseudomonas fluorescens A506 and S10 Pseudomonas fluorescens LMG 2189 were used. Data were recorded on growth parameters (shoot and root length, fresh and dry weight), physiological attributes (chlorophyll content, proline content, electrolyte leakage, and lead accumulation), and antioxidant activities (catalase, peroxidase, superoxide dismutase) in tomato plants. Results revealed that lead contamination significantly impaired plant growth, reducing shoot and root lengths by approximately 49.78–57.62%, and negatively impacted physiological attributes and antioxidant enzyme activities. However, inoculation with PGPR strains S5 and S10 led to notable improvements in growth parameters, enhanced physiological traits, and better antioxidant activities, effectively mitigating lead stress. These findings highlights the potential of PGPR to improve tomato plant resilience to lead contamination.

Co-application of organic amendments and Cd-tolerant rhizobacteria for suppression of cadmium uptake and regulation of antioxidants in tomato

Supplemental LED lighting affects the dynamics of tomato fruit growth and composition

The rhizosphere is a hotbed of microbial activity in ecosystems, fueled by carbon compounds from plant roots. Basic questions about the location and dynamics of plant-spurred microbial growth in the rhizosphere are difficult to answer with standard, destructive soil assays mixing a multitude of microbe-scale microenvironments in a single, often sieved, sample. Soil microbial biosensors designed with the luxCDABE reporter genes fused to a promoter of interest enable continuous imaging of the microbial perception of (and response to) environmental conditions in soil. We used the common soil bacterium Pseudomonas putida KT2440 as host to plasmid pZKH2 containing a fusion between the strong constitutive promoter nptII and luxCDABE (coding for light-emitting proteins) from Vibrio fischeri. Experiments in liquid media demonstrated that high light production by KT2440/pZKH2 was associated with rapid microbial growth supported by high carbon availability. We applied the biosensors in microcosms filled with non-sterile soil in which corn (Zea mays L.), black poplar (Populus nigra L.), or tomato (Solanum lycopersicum L.) was growing. We detected minimal light production from microbiosensors in the bulk soil, but biosensors reported continuously from around roots for as long as six days. For corn, peaks of luminescence were detected 1–4 and 20–35 mm along the root axis behind growing root tips, with the location of maximum light production moving farther back from the tip as root growth rate increased. For poplar, luminescence around mature roots increased and decreased on a coordinated diel rhythm, but was not bright near root tips. For tomato, luminescence was dynamic, but did not exhibit a diel rhythm, appearing in acropetal waves along roots. KT2440/pZKH2 revealed that root tips are not always the only, or even the dominant, hotspots for rhizosphere microbial growth, and carbon availability is highly variable in space and time around roots.

Hydroponics culture offers immense benefits in plant research, making it a valuable and versatile tool in scientific investigations across plant biology, agronomy, horticulture and diverse fields of research. The present study has been carried out for the establishment of Brassica alba and Solanum lycopersicum on hydroponic culture in laboratory condition. Firstly, an ideal concentration of macro and micro nutrients was developed for both B. alba and S. lycopersicum seedlings. After germination of both seeds, seedling was carefully monitored over a 15-day observation period on seedling tray. Then transfer of two-week-old seedlings to hydroponic media resulted in successful adaptation for both species. B. alba displayed slow initial growth but progressed significantly with robust development in the long run. In contrast, S. lycopersicum adapted quickly and exhibited continuous growth throughout the observation period. By week 4, both species had matured, with B. alba plants showing larger roots and stems and the onset of flowering. Both B. alba and S. lycopersicum seedlings displayed distinct growth patterns in hydroponic culture. These findings contribute valuable insights into the growth dynamics and viability of these two plant species in hydroponic systems, providing important information for optimizing cultivation practices and improving agricultural productivity. J. Bio-Sci. 31(1): 87-98, 2023

Manual phenotyping of tomato plants is time consuming and labor intensive. Due to the lack of low-cost and open-access 3D phenotyping tools, the dynamic 3D growth of tomato plants during all growth stages has not been fully explored. In this study, based on the 3D structural data points generated by employing structures from motion algorithms on multiple-view images, we proposed a 3D phenotyping pipeline, 3DPhenoMVS, to calculate 17 phenotypic traits of tomato plants covering the whole life cycle. Among all the phenotypic traits, six of them were used for accuracy evaluation because the true values can be generated by manual measurements, and the results showed that the R2 values between the phenotypic traits and the manual ones ranged from 0.72 to 0.97. In addition, to investigate the environmental influence on tomato plant growth and yield in the greenhouse, eight tomato plants were chosen and phenotyped during seven growth stages according to different light intensities, temperatures, and humidities. The results showed that stronger light intensity and moderate temperature and humidity contribute to a higher biomass and higher yield. In conclusion, we developed a low-cost and open-access 3D phenotyping pipeline for tomato and other plants, and the generalization test was also complemented on other six species, which demonstrated that the proposed pipeline will benefit plant breeding, cultivation research, and functional genomics in the future.

Mounting-up economic losses to annual crops yield due to micronutrient deficiency, fertiliser inefficiency and increasing microbial invasions (e.g. Xanthomonas cempestri attack on tomatoes) are needed to be solved via nano-biotechnology. So keeping this in view, the authors' current study presents the new horizon in the field of nano-fertiliser with highly nutritive and preservative effect of green fabricated zinc oxide-nanostructures (ZnO-NSs) during Lycopersicum esculentum (tomato) growth dynamics. ZnO-NS prepared via green chemistry possesses highly homogenous crystalline structures well-characterised through ultraviolet and visible spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction and scanning electron microscope. The ZnO-NS average size was found as small as 18 nm having a crystallite size of 5 nm. L. esculentum were grown in different concentrations of ZnO-NS to examine the different morphological parameters includes time of seed germination, germination percentage, the number of plant leaves, the height of the plant, average number of branches, days count for flowering and fruiting time period along with fruit quantity. Promising results clearly predict that bio-fabricated ZnO-NS at optimum concentration resulted as growth booster and dramatically triggered the plant yield.

Toxicity assessment of metal oxide nano-pollutants on tomato (Solanum lycopersicon): A study on growth dynamics and plant cell death

Physiological efficiency during the vegetative stage of tomato crops developed from magnetically treated seeds

CALIBRATION AND VALIDATION OF COMPLEX AND SIMPLIFIED TOMATO GROWTH MODELS FOR CONTROL PURPOSES IN THE SOUTHEAST OF SPAIN

To evaluate the relevance of a simple carbon balance model (Seginer et al., 1994, Scientia Horticulturae 60: 55-80) in source-limiting conditions, the dynamics of growth, respiration and carbohydrate reserves of tomato plants were observed in prolonged darkness. Four days prior to the experiments, plants were exposed to high or low light levels and CO(2) concentrations. The concentration of carbohydrates in vegetative organs was 30-50 % lower in plants that were exposed to low carbon assimilation conditions compared with those exposed to high carbon assimilation conditions. During prolonged darkness, plants with low carbohydrate reserves exhibited a lower whole-plant respiration rate, which decreased rapidly to almost zero after 24 h, and carbohydrate pools were almost exhausted in leaves, roots and flowers. In plants with high carbohydrate reserves, the whole-plant respiration rate was maintained for a longer period and carbohydrates remained available for at least 48 h in leaves and flowers. In contrast, fruits maintained fairly stable and identical concentrations of carbohydrates and the reduction in their rate of expansion was moderate irrespective of the pre-treatment carbon assimilation conditions. The time-course of asparagine and glutamine concentrations showed the occurrence of carbon stress in leaves and flowers. Estimation of source and sink activities indicated that even after low carbon assimilation, vegetative organs contained enough carbohydrates to support fruit growth provided their own growth stopped. The time of exhaustion of these carbohydrates corresponded grossly to the maintenance stage simulated by the model proposed by Seginer et al. (1994), thus validating the use of such a model for optimizing plant growth.

Dynamics of fruit growth and photoassimilate translocation in tomato plants (Lycopersicon esculentum Mill.) as affected by irradiation and day/night air temperature were analyzed in relation to respiration, photosynthesis and transpiration of the fruit and the leaf. Fruit growth was explained by about 80% of sap flux imported into the fruit and was scarcely affected by transpirational water loss from the fruit. Irradiation clearly enhanced fruit growth and photoassimilate translocation, and about 70% of fruit growth and about 80% of photoassimilate translocation were brought during the light period with highly activated leaf photosynthesis and fruit respiration under day/night air temperature of 25/15°C. In particular, when air temperature around fruits rose to 25°C in the light period, remarkable increases in fruit growth and photoassimilate translocation were found with the activated fruit respiration. On the other hand, decreases in fruit growth and photoassimilate translocation were found during the dark period without effects of air temperature. From these results, it was suggested that energy-dependent transport process of sugar in fruits is one of the determinant processes regulating fruit growth and photoassimilate translocation in tomato plants under light.

In order to analyse root system architectures (RSAs) from captured images, a variety of manual (e.g. Data Analysis of Root Tracings, DART), semi-automated and fully automated software packages have been developed. These tools offer complementary approaches to study RSAs and the use of the Root System Markup Language (RSML) to store RSA data makes the comparison of measurements obtained with different (semi-) automated root imaging platforms easier. The throughput of the data analysis process using exported RSA data, however, should benefit greatly from batch analysis in a generic data analysis environment (R software). We developed an R package (archiDART) with five functions. It computes global RSA traits, root growth rates, root growth directions and trajectories, and lateral root distribution from DART-generated and/or RSML files. It also has specific plotting functions designed to visualise the dynamics of root system growth. The results demonstrated the ability of the package’s functions to compute relevant traits for three contrasted RSAs (Brachypodium distachyon [L.] P. Beauv., Hevea brasiliensis Mull. Arg. and Solanum lycopersicum L.). This work extends the DART software package and other image analysis tools supporting the RSML format, enabling users to easily calculate a number of RSA traits in a generic data analysis environment.

In this study, we developed a model of tomato (Solanum lycopersicum L.) fruit growth integrating cell division, cell growth and endoreduplication. The fruit was considered as a population of cells grouped in cell classes differing in their initial cell age and cell mass. The model describes fruit growth from anthesis until maturation and covers the stages of cell division, endoreduplication and cell growth. The transition from one stage to the next was determined by predefined cell ages expressed in thermal time. Cell growth is the consequence of sugar import from a common pool of assimilates according to the source-sink concept. During most parts of fruit growth, potential cell growth rate increases with increasing cell ploidy and follows the Richards growth function. Cell division or endoreduplication occurs when cells exceed a critical threshold cell mass:ploidy ratio. The model was parameterised and calibrated for low fruit load conditions and was validated for high fruit load and various temperature conditions. Model sensitivity analysis showed that variations in final fruit size are associated with variations in parameters involved in the dynamics of cell growth and cell division. The model was able to accurately predict final cell number, cell mass and pericarp mass under various contrasting fruit load and most of the temperature conditions. The framework developed in this model opens the perspective to integrate information on molecular control of fruit cellular processes into the fruit model and to analyse gene-by-environment interaction effects on fruit growth.

The research objectives were to determine the effect of nitrogen dose and weed-free period on the competitiveness of tomato plants with weeds. The research used 6 x 4 Factorial Randomized Group Design. The first factor was the weed-free period (P) which consisted of six levels, namely weeds during tomato growth (P0), weed-free two weeks after planting (P1), weed-free four weeks after planting. (P2), weed-free six weeks after planting (P3), weed-free eight weeks after planting (P4), and weed free until harvest (P5). The second factor was the dose of nitrogen (N) consisting of 4 levels, namely: without fertilization (N0), fertilizing 50 kg N ha−1 (N1), fertilizing 100 kg N ha−1(N2) and fertilizing 150 kg N ha−1 (N3). The variable of observation was analyzed univariately using the F test and continued with the (Student-Newman-Keul) SNK test with a test level of 0.05. The plants growth rate weeds were analyzed by regression in the form of a curve as a function of time to see the dynamics of weed growth. The amount of competition between weeds and tomatoes were done through the competition index value approach. The results showed that the was a change in the value of competition between tomato plants with weeds at each level of nitrogen dose and weed-free period, this change decreased with increasing nitrogen dose. The highest yield was obtained when weed-free during tomato growth, namely 25.88 tons ha−1 with a fertilizer dose of 100 kg ha−1.