Plant Growth Analysis Research Articles

Retraction notice: A framework for plant growth analysis and simulation using data analysis techniques

Retraction notice: A framework for plant growth analysis and simulation using data analysis techniques

Plant Growth Analysis using IoT and Reinforcement Learning Techniques for Controlled Environment

The Internet of Thing (IoT) plays a major role for improving the green house plant productivity and generates essential information to yields. Various existing systems introduces a smart approach that utilizes the IoT concept to remotely deliver users with data regarding temperature, humidity, and soil moisture severity. The purpose of this system is to track and evaluate plant circumstances. This paper descries a plant growth analysis using IoT and statical machine learning techniques for broccoli plants. Initially data has collected using IoT modules including various potential parameters such as soil temperature, soil moisture, humidity and plant height on daily interval basis. The experimental analysis has done in controlled environment for 30 days daily records. Finally, system recommends possible decides need to take for improve the yield or productivity.

Effects of mechanical defoliation and pinching applications on plant growth and root system analysis with machine learning in boxwoods

The effects of mechanical defoliation and pinching (1 cm tip cutting) on Buxus plant growth, nutrient mobilization, and root architecture were determined. When 100% defoliation was applied, the highest increase rates of 80.3% in shoots and 88% in leaves were observed compared to the control group. In contrast, the overall effects of defoliation and pinching were negative, with 100% defoliation having the most negative effects. The chlorophyll content of the newly formed young leaves was also 50% lower with 100% defoliation. Leaves and root nutrient mobilization changed significantly, depending on the effects of defoliation and pinching. Apart from a very small increase in root length and number of forks, the effects of the treatments were negative, with 100% defoliation having the greatest negative effect on root development. Most affected was the number of crossings, which was 78% lower than in the control. In addition, machine learning (ML) algorithms were used in the study, including multilayer perceptron, J48, PART, and logistic regression. The input variables were evaluated to model and predict the root features. The performance values of the ML algorithms were noted in the following order: Logistic Regression> PART> J48> MultilayerPerceptron. As the severity of defoliation increased, the losses of the plant also increased. However, boxwood has mechanisms to compensate for these losses even when it suffers complete defoliation.

Fire-deposited charcoal enhances soil microbial biomass in a recently harvested subtropical plantation forest

Charcoal, a byproduct of biomass burning, is widely and heterogeneously distributed in fire-affected ecosystems. However, few field studies have been conducted to evaluate the effects of fire-deposited charcoal on the post-fire soil quality. In this study, we aimed to investigate whether charcoal generated during post timber harvest broadcast burning influenced the recovery of individual soil properties and overall soil quality in subtropical forest plantations. Broadcast burning was conducted on experimental Pinus massoniana plantation timber harvest sites in southern China. Surface soils (0–10 cm) were collected in plots established on the burnt sites five years after the disturbance event. Plots were established immediately after burning with three different levels of charcoal input (C0, removal of all visible charcoal; C1, charcoal retained in-situ; C2, charcoal removed from C0 added to C2) and an unburnt control (UB). Thirty-two soil indicators representing soil physical, chemical, and biological properties were determined. The results showed that 11 indicators exhibited significant differences among the treatments, with significantly lower SOM, microbial biomass carbon (MBC), peroxidase (POD) and leucine aminopeptidase (LAP) activities for the C0 and C1 plots than the UB plots (P < 0.05), while no significant difference was observed between the UB and C2 plot (P > 0.05). The soil available N, P and exchangeable nutrient contents were not significantly different among the treatments (P > 0.05). Our results indicate that SOM and microbial attributes did not recover five years after the disturbance event and that charcoal appeared to play a positive role in the post-fire soil restoration. Whether the accelerated recovery of soil restoration induced by charcoal might contribute to higher forest productivity needs to be testified in combination with plant growth and performance analysis in the future.

Development of New Edible Biodegradable Films Containing Camu-Camu and Agro-Industry Residue.

The use of edible films has garnered significant interest in the food and environmental sectors due to their potential to prevent food deterioration and their biodegradability. This study aimed to develop and characterize edible films based on camu-camu residue, gelatin, and glycerol, evaluating their solubility, thermal, degradability, antioxidant, and water vapor permeability properties of the gelatin matrix. This is the first study incorporating camu-camu into a gelatin and glycerol matrix. The films produced with camu-camu residue were manageable and soluble, with some non-soluble residues, providing a shiny and well-presented appearance. In the biodegradation results, samples 3 and 4 appeared to degrade the most, being two of the three most affected samples in the triplicate. The films showed degradation modifications from the third day of the experiment. In the germination and plant growth analysis, sample 4 exhibited satisfactory development compared to the other samples, emerging as the sample with the best overall result in the analyses, attributed to a 13.84 cm increase in the growth of the upper part of the seedling. These results indicate that the produced materials have potential for food packaging applications.

Growth and yield of Brazilian potato cultivars

The analysis of plant growth of cultivars is useful for understanding the dynamics of accumulation and partition of photoassimilates during the crop cycle, and this information is important for the crop management of each cultivar. The objective of this study was to evaluate potato cultivars BRS Ana, BRSIPR Bel, BRS Clara, BRS F63 (Camila) and Macaca for growth and yield, under subtropical climatic conditions of Southern Brazil. Plant samples were collected every 20 days, beginning 40 days after planting (DAP), totaling five collections, and physiological growth indexes and the dry mass partitioning to plant organs were estimated. ‘BRSIPR Bel’ showed the fastest development of assimilatory system. ‘BRS Ana’ had the most vigorous plants and the largest leaf area, reaching the leaf area index 4.0 at 70 DAP. ‘BRSIPR Bel’ e ‘BRS Ana’ had the highest dry mass yield, 214 g and 206 g of dry mass plant-1, respectively. ‘BRS F63’ (Camila) and ‘BRSIPR Bel’ presented earlier tuberization and were the most efficient cultivars in the partitioning of dry mass to tubers, with the highest coefficient of dry mass partitioning to tubers estimated between 40 and 64 DAP. These two cultivars also showed the highest yield of marketable tubers.

The silicon regulates microbiome diversity and plant defenses during cold stress in Glycine max L.

With climate change, frequent exposure of bioenergy and food crops, specifically soybean (Glycine max L.), to low-temperature episodes is a major obstacle in maintaining sustainable plant growth at early growth stages. Silicon (Si) is a quasi-essential nutrient that can help to improve stress tolerance; however, how Si and a combination of cold stress episodes influence plant growth, plant physiology, and microbiome diversity has yet to be fully discovered. The soybean plants were exposed to cold stress (8-10°C) with or without applying Si, and the different plant organs (shoot and root) and rhizospheric soil were subjected to microbiome analysis. The plant growth, physiology, and gene expression analysis of plant defenses during stress and Si were investigated. We showed that cold stress significantly retarded soybean plants' growth and biomass, whereas, Si-treated plants showed ameliorated negative impacts on plant growth at early seedling stages. The beneficial effects of Si were also evident from significantly reduced antioxidant activities - suggesting lower cold-induced oxidative stress. Interestingly, Si also downregulated critical genes of the abscisic acid pathway and osmotic regulation (9-cis-epoxy carotenoid dioxygenase and dehydration-responsive element binding protein) during cold stress. Si positively influenced alpha and beta diversities of bacterial and fungal microbiomes with or without cold stress. Results showed significant variation in microbiome composition in the rhizosphere (root and soil) and phyllosphere (shoot) in Si-treated plants with or without cold stress exposures. Among microbiome phyla, Proteobacteria, Bacteroidota, and Ascomycota were significantly more abundant in Si treatments in cold stress than in control conditions. For the core microbiome, we identified 179 taxa, including 88 unique bacterial genera in which Edaphobacter, Haliangium, and Streptomyces were highly abundant. Enhanced extracellular enzyme activities in the cold and Si+cold treatments, specifically phosphatase and glucosidases, also reflected the microbiome abundance. In conclusion, this work elucidates cold-mediated changes in microbiome diversity and plant growth, including the positive impact Si can have on cold tolerance at early soybean growth stages - a step toward understanding crop productivity and stress tolerance.

The Plant Growth Analysis of Cucumis sativus L. Affected by Various Types of Organic Matter

Organic matter can be used to increase the growth and metabolism activities of Cucumis sativus L. plants. Plant growth analysis is a simple method that can be used to determine physiological activities that support plant growth. The study aims to describe plant activities through plant growth analysis which is influenced by the use of organic matter. The research was conducted at the Experimental Garden, Faculty of Agriculture, Universitas Perjuangan Tasikmalaya. The study used a Completely Randomized Design - single factor (types of organic matters) i.e. control, rice straw compost, rice husk, leaf green compost, and cow manure. Four replications were used in this study. Based on our study, the application of organic matter significantly affects LAI 2 WAP, LAI 4 WAP, WC 2 WAP, WC 4 WAP, NAR, PGR, and HI. Cow manure, green leaf compost, and rice straw compost can increase LAI, while rice husk, rice straw, and green cow manure can increase WC. Furthermore, the application of rice husk and cow manure was able to increase in NAR, CGR, and HI. The increase NAR, CGR, and HI in this study was positively correlated with r= 0.622 and r= 0.284, respectively.

Effect of vermicompost on soil quality parameters for different land use patterns

Extensive industrialization, urbanization, and excessive use of chemicals in agricultural practices have caused soil quality depletion and reduced its nutritional value. In this context, the present study aimed to evaluate the effect of vermicompost (VC) on different soil properties such as pH, electrical conductivity, soil organic carbon, soil organic matter, total phosphorus, and bulk density to understand the soil enrichment for different land use patterns i.e., agriculture soil (AS), forest soil (FS) and barren soil (BS). The collected soil samples were mixed with VC in different proportions (1:1, 1:2, 1:3, 1:4, and 1:5) and analyzed in terms of aforementioned parameters. Among the investigated soils, the highest microbial biomass was observed for FS samples and noted in the range of 6 – 8 mg/gm of soil. All the original soils, supplemented samples, and VC were also subjected to plant growth analysis. The soil quality index (SQI) was determined using principal component analysis for selected soil samples and resulted mixtures obtained from soil and various proportions of VC. Among all samples, highest SQI was observed as 0.785 for VC. Overall, the result of the study showed that vermicompost can be a potential substitute of chemical fertilizers, thus improving the soil quality and crop yield.

4D hyperspectral surface topography measurement system based on the Scheimpflug principle and hyperspectral imaging.

A four-dimensional (4D) hyperspectral surface topography measurement (HSTM) system that can acquire uniform inelastic signals [three-dimensional (3D) spatial data] and reflection/fluorescence spectra of an object is proposed. The key components of the system are a light-sheet profilometer based on the Scheimpflug principle and a hyperspectral imager. Based on the mapping relationships among the image coordinate systems of the two imaging subsystems and the coordinate system of the real space, the spectral data can be assigned to the corresponding 3D point cloud, forming a 4D model. The spectral resolution is better than 4nm. 700nm, 546nm, and 436nm are selected as the three primary colors of red, green, and blue to restore the color. The 4D hyperspectral surface reconstruction experiments of philodendron and chlorophytum have shown the good performance of the proposed HSTM system and the great application potential for plant phenotype and growth analysis in agriculture.

Influence of arbuscular mycorrhizal fungi density on growth and metabolism of Handroanthus serratifolius (Vahl) S.O. Grose seedlings

AbstractStudies on the relationship between Handroanthus serratifolius and arbuscular mycorrhizal fungi (AMF) are limited in the literature. The influence of AMF spore density on plant development is fundamental information to determining the degree of benefits in this relationship. Therefore, the objective of this study was to investigate the effects of different AMF spore densities on thirty‐day‐old H. serratifolius seedlings, focusing on growth and biochemical parameters using a completely randomized experimental design with three different spore densities and control. The spore densities were classified as low, medium, and high, with 1.54, 3.08, and 12.35 spores g−1, respectively. Plant growth analysis, mycorrhizal colonization, nitrogen compound concentration, and carbohydrate analysis were performed. The medium spore density treatment showed the greatest increases in biomass, height, leaf area, and root volume. Furthermore, greater absorption of phosphorus and better dynamics in nitrogen metabolism were observed in mycorrhizal plants compared to the control since the ammonium and nitrate compounds were rapidly incorporated into protein and chlorophyll compounds. The carbohydrate analysis revealed the influence of source‐sink dynamics on sugar concentration in different plant parts. These findings support the importance of determining the appropriate spore density for assessing the symbiotic relationship between forest species and AMF.

Tunable Spinel Structure Phosphors: Dynamic Change in Near‐Infrared Windows and Their Applications

AbstractApplications in near‐infrared (NIR) have been explored significantly in many fields, including bioimaging, night vision, plant growth, and chemical analysis. Different emission profiles are required within the same industry. Developing luminescent materials with different tuning methods is reliable for controlling the NIR regions (NIR‐I, 700–1000 nm; NIR‐II, 1000–1700 nm). Spinel phosphors are promising candidates due to their ability to modulate the crystal field. Understanding the parameters that influence the degree of inversion in spinel compounds is crucial to harness the variability of the spinel structure. Cr3+ and Ni2+ are ideal activators for NIR‐I and NIR‐II emissions, respectively. However, there is a need for phosphors that emit in the NIR‐II region when excited by visible light. Although the energy transfer method combining two activators is considered, this review focuses on different types of spinel structures, discussing their types and common strategies to tune the host structure. The goal is to achieve desired shift and broadness of the entire NIR spectrum, highlighting the importance of spectrum tuning for practical applications.

Effects of Phosphorus and Zinc on Net Assimilation Rate (NAR) of Cowpea (&lt;i&gt;Vigna unguiculata&lt;/i&gt; (L.) Walp) Varieties Grown in Bauchi, Nigeria

Plant growth analysis is today studied as it relates to change in capture and efficiency in the use of resources rather than as it relates to relative growth rate in the past. Net assimilation rate (NAR) is the rate of increase in dry matter over unit area of leaf, which represented a measurement of excess of photosynthesis overrespiratory losses of dry matter. Two field experiments were conducted at the Faculty of Agriculture and Agricultural Engineering Research Farm of Abubakar Tafawa Balewa University, Bauchi, North Eastern, Nigeria, between 2006 and 2007 to evaluate the influence of phosphorus (0, 25, 50 kg P/ha) and zinc levels (0, 2.5, 5 kg Zn/ha) on NAR of six cowpea varieties namely: IT90K 277, IT93 455 1, IT89KD 288, IT97K 568 18, IT90K 82 2 and Kanannado. Results obtained showed that NAR was not significantly influenced by P and Zn levels and therefore, 0 kg ha1 SSP and Zn rate produced the highest NAR than higher levels. Neither applications of each of P and Zn at higher levels or their interactions, nor did year or variety were found to have significant effects on NAR; but rather NAR is being determined by number of factors such as nutrient supply, photosynthesis rate, etc and these are never fixed or constant and hence a particular factor e.g., nutrient (P or Zn) cannot dictate NAR alone.

Tracking deuterium uptake in hydroponically grown maize roots using correlative helium ion microscopy and Raman micro-spectroscopy

BackgroundInvestigations into the growth and self-organization of plant roots is subject to fundamental and applied research in various areas such as botany, agriculture, and soil science. The growth activity of the plant tissue can be investigated by isotope labeling experiments with heavy water and subsequent detection of the deuterium in non-exchangeable positions incorporated into the plant biomass. Commonly used analytical methods to detect deuterium in plants are based on mass-spectrometry or neutron-scattering and they either suffer from elaborated sample preparation, destruction of the sample during analysis, or low spatial resolution. Confocal Raman micro-spectroscopy (CRM) can be considered a promising method to overcome the aforementioned challenges. The substitution of hydrogen with deuterium results in the measurable shift of the CH-related Raman bands. By employing correlative approaches with a high-resolution technique, such as helium ion microscopy (HIM), additional structural information can be added to CRM isotope maps and spatial resolution can be further increased. For that, it is necessary to develop a comprehensive workflow from sample preparation to data processing.ResultsA workflow to prepare and analyze roots of hydroponically grown and deuterium labeled Zea mays by correlative HIM-CRM micro-analysis was developed. The accuracy and linearity of deuterium detection by CRM were tested and confirmed with samples of deuterated glucose. A set of root samples taken from deuterated Zea mays in a time-series experiment was used to test the entire workflow. The deuterium content in the roots measured by CRM was close to the values obtained by isotope-ratio mass spectrometry. As expected, root tips being the most actively growing root zone had incorporated the highest amount of deuterium which increased with increasing time of labeling. Furthermore, correlative HIM-CRM analysis allowed for obtaining the spatial distribution pattern of deuterium and lignin in root cross-sections. Here, more active root zones with higher deuterium incorporation showed less lignification.ConclusionsWe demonstrated that CRM in combination with deuterium labeling can be an alternative and reliable tool for the analysis of plant growth. This approach together with the developed workflow has the potential to be extended to complex systems such as plant roots grown in soil.

Plant Growth Analysis of Costus spectabilis and RAPD Marker Application to Identify Genetic Diversity among Four Selected Costus Species

Plant Growth Analysis of Costus spectabilis and RAPD Marker Application to Identify Genetic Diversity among Four Selected Costus Species

PERUBAHAN BEBERAPA SIFAT KIMIA TANAH PESISIR DAN PENGARUHNYA TERHADAP PERTUMBUHAN CABAI RAWIT (Capsicum frutescens L.) YANG DIBERI ABU SEKAM PADI DAN PUPUK NPK

Beach sandy land has great potential to be used as an agricultural area, because it has a very large area and has not been utilized optimally, especially as a cultivation area. The aims of this study were: To determine the effect of rice husk ash and NPK fertilizer on changes in some of the chemical properties of coastal soils and the growth of cayenne pepper plants. To determine the interaction effect of rice husk ash and NPK fertilizer on changes in several chemical properties of coastal soils and the growth of cayenne pepper plants. This research was conducted at Field Laboratory II, Faculty of Agriculture, University of Halu Oleo. Analysis of soil samples was carried out at the Testing Laboratory of the Department of Soil Science, Faculty of Agriculture, Halu Oleo University. This research was conducted from August 2022 to October 2022. This research used a Randomized Block Design (RBD) consisting of A0 = 0 g polybag-1, A1 = 25 g polybag-1 or equivalent to 5 ton ha-1, A2 = 37, 5 g polybag-1 or the equivalent of 7.5 tons ha-1, B0 = 0 g polybag-1, B1 = 5 g polybag-1 or the equivalent of 1 ton ha-1, B2 = 7.5 g polybag-1 or equivalent to 1.5 tons ha-1. The variables observed included analysis of soil chemical properties and plant growth. The results showed that a mixture of rice husk ash and NPK fertilizer was able to increase the nutrient content of N, P, K, pH, C-Organic in coastal soil, characterized by an increase in plant height and number of leaves of red chili plants and the dose of organic fertilizer that had the best effect, namely 37.5g and 7.5g.Keywords: husk ash, C-organics, soil chemical, sand land, NPK

Deep machine learning for cell segmentation and quantitative analysis of radial plant growth

Plants produce the major part of terrestrial biomass and are long-term deposits of atmospheric carbon. This capacity is to a large extent due to radial growth of woody species – a process driven by cambium stem cells located in distinct niches of shoot and root axes. In the model species Arabidopsis thaliana, thousands of cells are produced by the cambium in radial orientation generating a complex organ anatomy enabling long-distance transport, mechanical support and protection against biotic and abiotic stressors. These complex organ dynamics make a comprehensive and unbiased analysis of radial growth challenging and asks for tools for automated quantification. Here, we combined the recently developed PlantSeg and MorphographX image analysis tools, to characterize tissue morphogenesis of the Arabidopsis hypocotyl. After sequential training of segmentation models on ovules, shoot apical meristems and adult hypocotyls using deep machine learning, followed by the training of cell type classification models, our pipeline segments complex images of transverse hypocotyl sections with high accuracy and classifies central hypocotyl cell types. By applying our pipeline on both wild type and phloem intercalated with xylem (pxy) mutants, we also show that this strategy faithfully detects major anatomical aberrations. Collectively, we conclude that our established pipeline is a powerful phenotyping tool comprehensively extracting cellular parameters and providing access to tissue topology during radial plant growth.

Optimizing Alternative Substrate for Tomato Production in Arid Zone: Lesson from Growth, Water Relations, Chlorophyll Fluorescence, and Photosynthesis

Soilless culture is considered the mostpromising, intensive, and sustainable approach with various advantages for plant production in terms of saving water and nutrients. It can provide consumers with sufficient and high-quality food. However, the commonly used growing substrate for soilless cultivation, coconut fiber (CF), is usually imported and expensive or even unavailable. The objectives of this study were to investigate the impact of local organic farm resources substrates on tomato (Solanum lycopersicum L.) plant growth, water relations, photosynthesis, chlorophyll fluorescence, and phytochemical analysis of fruits in a hydroponics culture system. Two growth substrates were evaluated: date-palm waste composted with animal manure (7:3 w/w) (DPAM) and date-palm trunk compost (DPT). CF and local soil were utilized as positive and negative controls, respectively, in randomized blocks. The results revealed that DPAM substrate enhanced plant growth and physiology: shoot development, leaves tissues hydration, and photosynthetic parameters, as well as chlorophyll fluorescence. However, DPT and CF improved fruit quality: water, mineral, sugar, and protein content. The antioxidant activity of the fruit extract was the greater in DPAM, reaching 13.8 mg GAEg-1 DW. This value wasdecreased in soil by 40%. Photosynthesis activity was the most important in DPAM with 12 µmol CO2 m-2 s-1, and only 6.4 µmol CO2 m-2 s-1 in the soil condition. However, regarding the non-photochemical quenching, the dissipated light energy was greater in soil (0.096 ± 0.02) than in DPAM (0.025 ± 0.04). Date-palm waste-based substrates improved tomato vegetative growth and fruit quality as compared to soil-based culture. Date-palm waste-based substrates supplemented with manure appear to be promising and less expensive alternatives to the coconut fiber substrate extensively used in soilless crops in North Africa.

Relative growth rate (RGR) and other confounded variables: mathematical problems and biological solutions.

Relative growth rate (RGR) has a long history of use in biology. In its logged form, RGR = ln[(M + ΔM)/M], where M is size of the organism at the commencement of the study, and ΔM is new growth over time interval Δt. It illustrates the general problem of comparing non-independent (confounded) variables, e.g. (X + Y) vs. X. Thus, RGR depends on what starting M(X) is used even within the same growth phase. Equally, RGR lacks independence from its derived components, net assimilation rate (NAR) and leaf mass ratio (LMR), as RGR = NAR × LMR, so that they cannot legitimately be compared by standard regression or correlation analysis. The mathematical properties of RGR exemplify the general problem of 'spurious' correlations that compare expressions derived from various combinations of the same component terms X and Y. This is particularly acute when X >> Y, the variance of X or Y is large, or there is little range overlap of X and Y values among datasets being compared. Relationships (direction, curvilinearity) between such confounded variables are essentially predetermined and so should not be reported as if they are a finding of the study. Standardizing by M rather than time does not solve the problem. We propose the inherent growth rate (IGR), lnΔM/lnM, as a simple, robust alternative to RGR that is independent of M within the same growth phase. Although the preferred alternative is to avoid the practice altogether, we discuss cases where comparing expressions with components in common may still have utility. These may provide insights if (1) the regression slope between pairs yields a new variable of biological interest, (2) the statistical significance of the relationship remains supported using suitable methods, such as our specially devised randomization test, or (3) multiple datasets are compared and found to be statistically different. Distinguishing true biological relationships from spurious ones, which arise from comparing non-independent expressions, is essential when dealing with derived variables associated with plant growth analyses.

A Review on Plant Growth Analysis and Disease Detection

A Review on Plant Growth Analysis and Disease Detection