Plant Parameters Research Articles

Efficacy of soil drench and foliar application of iron nanoparticles on the growth and physiology of Solanum lycopersicum L. exposed to cadmium stress.

Cadmium (Cd) can harm the yield and quality of vegetables, threatening food safety. Essential microelements such as iron are crucial for plant growth and can help alleviate heavy metal stress. Recently, nanoparticles have been studied as eco-friendly solutions for mitigating heavy metal stress in plants. In the present study, iron nanoparticles (FeNPs) at 0, 100, and 300mg/L were applied as soil drenches and foliar sprays to tomato plants under cadmium stress. A comparison was made between the application methods of FeNPs by evaluating the growth parameters of tomato plants, including shoot length (SL), root length (RL), number of branches (NB), number of leaves per plant (NL), and leaf area (LA), as well as by assessing biochemical and antioxidant enzyme parameters. In the Cd stress treatment, the protein content decreased by 24.71%, and the phenolic and flavonoid content of the tomato plants also decreased due to cadmium stress, with levels decreasing from 16.07 to 6.9µg and from 0.36 to 0.16µg, respectively. Compared with the soil drench, 100mg/L FeNPs significantly improved the parameters of Cd-stressed plants when used as a foliar spray, leading to increases in shoot length, root length, fruit weight, number of fruits, number of leaves, and number of branches by 42%, 66%, 24%, 66%, 173%, and 45%, respectively. Tomato plants treated with this spray presented increased carotenoid and lycopene contents. FeNP foliar spray also reduced Cd accumulation in plant tissues. This technique shows promise in alleviating Cd stress in vulnerable vegetable plants such as tomatoes.

Induced Phytomanagement of Multi-Metal Polluted Soil with Conocarpus erectus Supported by Biochar, Lignin, and Citric Acid

Induced heavy metals (HMs) phytoextraction from heavily contaminated soils is challenging, as high HM bioavailability causes phytotoxicity and leaching. This study introduces a novel approach for HM immobilization with biochar (BC) and lignin (LN), and later their controlled mobilization with citric acid (CA) in soil. Conocarpus erectus was grown for 120 days in shooting-range soil (SS) polluted with Pb, Cr, Cd, Ni, and Cu. HM concentrations in parts of the plants, their percentage removal, and leaching from SS were measured. Moreover, plant biochemical parameters such as the contents of chlorophyll a (Chl-a), chlorophyll b (Chl-b), protein, ascorbic acid (AsA), amino acids, and total phenolics, along with biophysical parameters such as relative water content (RWC) and water uptake capacity (WUC), were also inspected. Adding BC, LN, and BC+LN to SS improved biomass, as well as the biophysical and biochemical parameters of plants, while efficiently reducing HM concentrations in plant parts, DTPA extract, and leachates compared to the control (CK). However, the greatest amplifications in plant height (82%), dry weight of root (RDW) (109%), and dry weight of shoot (SDW) (87%), plant health, and soil enzymes were noted with the BC+LN+CA treatment, compared with the CK. Moreover, this treatment resulted in Pb, Cr, Cd, Ni, and Cu removal by 68, 30, 69, 59, and 76% from the SS compared to the CK. Surprisingly, each HM concentration in the leachates with BC+LN+CA was below the critical limits for safer water reuse and agricultural purposes. Initial HM immobilization in HM-polluted soils, followed by their secured mobilization during enhanced phytoextraction, can enhance HM removal and reduce their leaching without compromising plant and soil health.

Characterization of Fruit, Seed Traits and Seedling Growth Performance of Different Seed Sources of Calophyllum inophyllum

Calophyllum inophyllum is an oil-bearing tree species with seeds containing 50-70 per cent oil, mainly used for non-edible purposes. Belonging to the Clusiaceae family, it is commonly known as Undi in Kannada. This littoral tropical tree grows above the high-tide mark along coastlines and is frequently found on sandy beaches. Its prominence has increased due to high demand as biofuel and commercialization. The study aimed to examine the fruit and seed traits from various sources and the impact of seed source variation on germination and seedling growth of Calophyllum inophyllum. Experiments were conducted at the College of Forestry, Sirsi, with fruits collected from seven different regions from coastal taluks of Uttara Kannada district, Karnataka. Data on fruit, seed, and plant parameters were recorded. Results revealed that there was no such statistically significant difference was observed in fruit parameters, seed parameters, seedling parameters and germination percentage of Callophyllum inophyllum among the selected seed sources inferring no greater variations. However, the seeds from the Ramangindi (48.66%, 17% higher than the next best region, Ankola) region in Kumta taluk performed better in germination of seeds, fruit and seed traits, as well as growth compared to other sources.

Root System Architecture Reorganization Under Decreasing Soil Phosphorus Lowers Root System Conductance of Zea mays.

The global supply of phosphorus is decreasing. At the same time, climate change reduces the availability of water in most regions of the world. Insights on how decreasing phosphorus availability influences plant architecture are crucial to understanding its influence on plant functional properties, such as the root system's water uptake capacity. In this study, we investigated the structural and functional responses of Zea mays to varying phosphorus fertilization levels focusing especially on the root system's conductance. A rhizotron experiment with soils ranging from severe phosphorus deficiency to sufficiency was conducted. We measured the architectural parameters of the whole plant and combined them with root hydraulic properties to simulate time-dependent root system conductance of growing plants under different phosphorus levels. We observed changes in the root system architecture, characterised by decreasing crown root elongation and reduced axial root radii with declining phosphorus availability. Modeling revealed that only plants with optimal phosphorus availability sustained a high root system conductance, while all other phosphorus levels led to a significantly lower root system conductance, both under light and severe phosphorus deficiency. We postulate that phosphorus deficiency decreases root system conductance, which could mitigate drought conditions through a more conservative water use strategy, but ultimately reduces biomass and impairs root development and overall water uptake capacity. Our results also highlight that the organisation of the root system, rather than its overall size, is critical for estimating important root functions.

Organomineral fertilization using biomass ash as raw material in the initial growth of Adzuki Bean

The need to find sustainable and viable alternatives for agricultural fertilization has driven research into the use of organo-mineral fertilizers. This study evaluated the initial development of Adzuki beans [Vigna angularis (Willd.) Ohwi & H. Ohashi] with organomineral fertilization, resulting from the combination of biomass ash and synthetic mineral fertilizers. Different doses of organominerals were applied (6.25, 12.5, 18.75 and 25.0 g dm-3), and various plant parameters were assessed. The results indicated that organomineral fertilization, especially at a dose of 25.0 g dm-3, had a positive influence on soil pH, plant height, stem diameter, number of leaves, leaf area, shoot dry mass, root volume and root dry mass. The organomineral proved to be effective in promoting the initial growth of Adzuki beans, offering an alternative to the exclusive use of mineral fertilizers.

Developing an efficient explainable artificial intelligence approach for accurate reverse osmosis desalination plant performance prediction: application of SHAP analysis

In recent decades, securing drinkable water sources has become a pressing concern for populations in various regions worldwide. Therefore, to address the growing need for potable water, contemporary water purification technologies can be employed to convert saline sources into drinkable supplies. Therefore, the prediction of important parameters of desalination plants is a key task for designing and implementing these facilities. In this regard, artificial intelligence techniques have proven to be powerful assets in this field. These methods offer an expedited and effective means of estimating effective parameters, thus catalyzing their implementation in real-world scenarios. In this study, the predictive accuracy of six different machine learning models, including Natural Gradient-based Boosting (NGBoost), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Support vector regression (SVR), Gaussian Process Regression (GPR), and Extremely Randomized Tree (ERT) was evaluated for modelling the parameter of permeate flow as a key element in system efficiency, energy consumption, and water quality using six various input combinations of feed water salt concentration, condenser inlet temperature, feed flow rate, and evaporator inlet temperature. The next phase of this research employed the SHAP interpretability method to illustrate the impact of individual variables on the model's output. Moreover, the predictive performance of the developed frameworks was evaluated using a set of five dependable statistical measures: RMSE, NS, MAE, MAPE and R 2. These indicators were utilized to provide a robust means of gauging the precision of the model's forecasts. A comparative analysis of the outcomes, as measured by the RMSE criteria, revealed that the SVR technique (RMSE = 0.125 L/(h·m2)) exhibited superior performance compared to NGBoost (RMSE = 0.163 L/(h·m2)), AdaBoost (RMSE = 0.219 L/(h·m2)), CatBoost (RMSE = 0.149 L/(h·m2)), GPR (RMSE = 0.156 L/(h·m2)), and ERT (RMSE = 0.167 L/(h·m2)) methodologies in predicting permeate flow rates. The modelling outcomes obtained during the evaluation stage demonstrated the efficacy of the SVR algorithm in enhancing the precision of permeate flow forecasts, utilizing relevant input variables.

Research on reactor power prediction of nuclear power plant based on multivariate optimization GRU model

In the operation of nuclear power plants, the accurate prediction of power change trends is crucial for ensuring safety and stability. In this work, a ML-GRU-RS method, based on model-agnostic meta-learning (MAML), gate recurrent unit (GRU), and random search optimization, is proposed for the long-term prediction of key parameters of nuclear power plants. This method combines the fast adaptability of MAML, the time series data processing capability of GRU, and the optimization efficiency of random search to achieve high-precision predictions under varying power conditions. The results demonstrate that this method can effectively predict the future trends of key parameters in nuclear power plants. The ability of operators to anticipate these trends has been significantly enhanced, contributing to the overall safety of the nuclear power plants.

Effect of BTHWA Biostimulation on Lettuce Using Chlorophyll Fluorescence, Gas Exchange, and Thermography

The aim of this study was to examine lettuce using different concentrations of the biostimulator N-methyl-N-methoxyamide-7-carboxybenzo(1.2.3)thiadiazole (BTHWA), a new benzothiadiazole derivative. Different concentrations of BTHWA during watering and spraying were applied to lettuce. Chlorophyll fluorescence, gas exchange, thermal images, and plant parameter data were used to study physiological process and the growth of lettuce. Chlorophyll fluorescence data showed a strong effect after the first BTHWA application to lettuce. After three applications, the plants were harvested and data were recorded. Similarly, in the second experiment, gas exchange and thermal images were recorded after the first treatment of BTHWA. Our findings showed improved chlorophyll efficiency after the first BTHWA application, and no adverse effects were recorded on the overall photochemistry at any concentration. Regarding growth parameters, spraying BTHWA reduced the fresh weight but decreased the damage index. A lower watering concentration (0.066 mg/L) applied three times did not cause any damage to plants and fresh weight, even after repeated applications. Infrared thermal images showed BTHWA application also significantly affected plant temperature. Gas exchange data revealed that sprayed plants exhibited higher transpiration rates, stomatal conductance, and photosynthetic rates when compared to watered and control plants. This study suggests that application of a low dose of BTHWA is safe to use in agriculture practices in lettuce without compromising its growth and yield.

Study of the features of angular stabilization of spacecraft with flexible struc-tural elements with the use mobile control methods

The development of space power engineering is one of the well-known lines in rocket and space science and innovative technologies which attracts the attention of many scientists and researchers. Engineering solutions in space-based solar power plant design and wireless space-to-Earth and satellite-to-satellite power transmission and power spacecraft control methods have been substantiated theoretically to sufficient depth. However, despite this, there is a need to improve methods for and approaches to the development of an optimal design methodology for power spacecraft. A way to improve existing approaches to the development of space-based solar power plants and power satellites may be the use of mobile control methods in the development of an attitude and orbit control system. Such methods allow one to reduce power consumption for control operations. The goal of this paper is to study the features of mobile control and construct a methodology for the development of solar power satellites’ attitude and orbit control system (AOCS) using mobile control algorithms. The paper considers the features of mobile control algorithm synthesis for the attitude control and stabilization of solar power spacecraft (solar power plants and power satellites). Power spacecraft control tasks are classified, and the expediency of using mobile control methods is justified. An analysis is made for the stability problem that arises in controlling power spacecraft with flexible elements. The paper presents methodological recommendations on determining the AOCS design parameters for space-based solar power plants and power spacecraft for wireless satellite-to-satellite power transmission. This methodology may be used in power satellite development.

Hydro-thermal Power Reserve Allocation Under Outage Uncertainty

In recent decades, the energy sector, namely energy markets have proved to be changing considerably. Most of these changes result in increasing volatility related to global political and environmental factors. This volatility affects all entities operating in the power sector. This paper focuses on the power plant operator’s perspective. First, the global context of the power sector is discussed and the power plant operator’s role is reviewed. Further, the problem of power reserve is discussed revealing the motivations of the presented work. The central contribution of this work lies in the formulation and development of a stochastic model of power reserve coupled with a mixed-integer programming scheduling model. In the results section, we show that the developed model allocates power reserve in an optimal way respecting the technical and economic parameters of the power plants as well as handling the stochastic nature of the power reserve allocation problem by minimizing the mean value of the sum of penalty for not delivering contracted power and lost opportunity.

Maize biomass yield variations due to diverse nitrogen applications using Aquacrop

AbstractIn the quest to increase crop yields and production intensity to meet the demands of a growing global population, the responsible use of nitrogen (N) applications is paramount. Excessive application of these fertilizers results in economic losses, environmental pollution and reduced N‐use efficiency. To address this challenge, precision agriculture techniques offer promising solutions. This study explored the relationships among applied N, maize crop parameters and the nitrogen nutrition index (NNI) to optimize N application usage and crop performance. The AquaCrop model was used to simulate water productivity and plant parameters accurately. The research establishes equations between the NNI and maize parameters, enabling the use of AquaCrop to simulate crop responses to varying N levels. The results demonstrate that AquaCrop effectively simulates more than 95% of the biomass changes. The findings suggest that applying N based on presented equations optimized the use of N applications, thereby mitigating economic losses and environmental impacts.

The Arabidopsis PIP1;1 Aquaporin Represses Lateral Root Development and Nitrate Uptake Under Low Nitrate Availability.

Nitrate (NO3 -) deficiency decreases root water uptake and root hydraulic conductance. This adaptive response is correlated with reduced abundance and activity of plasma membrane intrinsic protein (PIP) aquaporins. We therefore screened changes in the root architecture of a complete set of Arabidopsis pip loss-of-function mutants grown under NO3 - deficiency to systematically approach the impact of PIPs under these conditions. NO3 - deprivation led to attenuated responses of specific pip single mutants compared to the strongly altered LR parameters of wild-type plants. In particular, pip1;1 exhibited a lower relative reduction in LR length and LR density, revealing that PIP1;1 represses LR development when NO3 - is scarce. Indeed, PIP1;1 compromises root and shoot NO3 - accumulation during early developmental stages. A fluorescent VENUS-PIP1;1 fusion revealed that PIP1;1 is specifically repressed in the pericycle, endodermis and at the flanks of emerging LRs upon NO3 - deficiency. Thus, LR plasticity and NO3 - uptake are affected by an interactive mechanism involving aquaporins (PIP1;1) and nitrate accumulation during seedling development under NO3 --deficient conditions.

Research on the Detection Principle of Coal Ash by X-Ray Transmission Based on FLUKA

This study addresses the timely and accurate measurement of coal ash content by proposing a detection model based on nuclear science technology, which is validated using FLUKA 4-4.0 simulation software. The background provided highlights the fact that coal ash content is a critical sales indicator, and its precise measurement is essential for adjusting production parameters in coal preparation plants. In terms of methodology, this study employs the widely used FLUKA4-4.0 software in the field of nuclear physics to simulate X-ray transmission through coal, investigating the impact of changes in coal type on the accuracy of ash measurements. The results indicate that, when the proportions of high-atomic-number elements in coal remain constant, the ash measurement results are accurate and reliable. However, significant fluctuations occur when these proportions change. The conclusion emphasizes the fact that variations in coal type are the primary cause of inaccuracies in ash measurement, particularly when the ratios of high-atomic-number elements are altered. This research provides a new perspective on the online measurement of coal ash content and offers theoretical support for improving measurement accuracy.

Callus induction, subculture, and browning inhibition of the anticancer plant Taxus media

In order to obtain more effective cell culture parameters of Taxus anticancer plants, we optimized the callus induction and subculture conditions of the explants (stem segments with buds) of the anticancer medicinal plant Taxus media by using the plant tissue culture technology and orthogonal test. Furthermore, we studied the method to inhibit browning in the culture. The results indicated that the optimal conditions for inducing callus was culture in the medium composed of B5+0.25 mg/L 2, 4-D+1.5 mg/L NAA+0.5 mg/L KT in the dark, which showed short induction time and a high induction rate (86.7%). The formula of the optimal medium for subculture was B5+0.5 mg/L 2, 4-D+2.0 mg/L NAA+1.5 mg/L KT.The proliferation multiple of callus cultured by subculture on the 10th day of callus growth was the highest. Activated carbon inhibited the browning in callus subculture, with the optimal inhibitory concentration of 0.8 g/L. The results of this study lay a foundation for the production of taxol by suspension culture of T. media cells.

Preparation of Biofertilizers from Banana Peels: Their Impact on Soil and Crop Enhancement

Disposing of banana peels (BPs) as bio-organic waste is an environmental challenge. Rich in potassium, BPs are often discarded despite their agricultural value. Reports on the valorization of BP are increasing, but no review has focused on BP fertilizer preparation methods. This study aims to review and analyze these methods to guide researchers and agriculturists in optimizing BP utilization, promoting sustainable waste management, and effective agricultural practices. This review has uncovered significant findings. A composite of banana and orange peels emerged as the most favoured and widely used approach, closely followed by dried BPs. This study highlighted the substantial impact of fertilizer application methods such as top and basal dressing. Most of the results revealed that the peels significantly improved the growth parameters of various plants. However, for biochar, the plant height was insignificant between treatments, further emphasizing the importance of the application method used. Banana peels are a valuable resource for biofertilizer synthesis. The banana–orange peel composite exhibits outstanding fertilizer properties. More new studies should go beyond the seedling stage, especially to harvest. This would give more information on the performance and viability of BP fertilizers.

Effect of Organic Manures and Chemical Fertilizers on Growth and Yield of Green Gram (Vigna radiata L.)

A field experiment was conducted at experimental farm, Department of Agronomy, Faculty of Agriculture and Veterinary Sciences, Mewar University Gangrar, Chittorgarh (Rajasthan) during Rabi season of 2023-24 to effect of organic manures and chemical fertilizers on growth and yield of green gram, variety “SML-832‟ was used in this study. The required quantities of fertilizers as per treatments were applied. The experiment was laid out in randomized block design with three replications consisting of ten treatments. The data recorded maximum growth parameters like, plant height (51.45 cm), number of branches per plant (4.08) and yield parameters like, number of pods per plant (20.58, number of seeds per pod (8.65), test weight (38.92 g), grain yield (1106.45 kg/ha), straw yield (2583.85 kg/ha) and maximum net return (48100 Rs/ha) and B:C ratio (1.58) was recorded with T9-75% Vermicompost @ 1.25 t per ha. The minimum growth and yield obtained with control treatment. Therefore, concluded that impact of different organic manures and chemical fertilizers on the growth and yield of the green gram. Among different T9-75% RDF + Vermicompost @ 1.25 t per ha registered the maximum production with higher net return. So, it was concluded that the treatment 75% RDF + Vermicompost @ 1.25 t per ha superior among all treatments.

Water Relations and Physiological Traits Associated with the Yield Components of Winter Wheat (Triticum aestivum L.)

Water stress in agricultural systems may occur slowly or abruptly. Plant reactions to stress differ with regard to its level and duration. The level of plant susceptibility to water deprivation primarily depends on the management of the water content and metabolism adjustments. The aim of this study was to determine the correlation between water-based plant parameters and the yield components of 90 genotypes of winter wheat (Triticum aestivum L.). Since the loss of water is frequently used as a selection criterion to assess drought tolerance, the relationships between the yield and leaf water content, osmotic potential, and gas exchange characteristics were examined. Genotypes 1, 25, 34, 36, 42, 43, 46, 57, 66, 73, and 90 showed 33–45% larger numbers of grains/plant, 19–25% higher weights of grains/plant, and 4% higher thousand grain weights compared to other genotypes. The higher values of the yield components were accompanied by 20–30% lower leaf water content, 39–52% lower osmotic potential, and 4–39% lower water use efficiency. The principal component analysis revealed that the wheat genotypes had noticeable differences in a few physiological parameters that depended on the sowing date. Electrolyte leakage showed a substantial correlation with the sowing date, suggesting that it may not be a suitable factor for the prediction of drought tolerance. The factors that distinguished the examined genotypes the most were the leaf water content, osmotic potential, and water use efficiency. In addition, a significant correlation was observed between the mentioned parameters and yield components. As a result, these parameters may be helpful in genotype characterization in relation to water stress susceptibility, offering a trustworthy plant selection test.

Response of growth and chlorophyll fluorescence parameters of mulberry seedlings to waterlogging stress

This study aimed to investigate the adaptive mechanisms of mulberry (Morus alba) to waterlogged conditions, with a specific focus on the development of adventitious roots (ARs), alteration of growth strategies, and adjustment of chlorophyll fluorescence parameters. To achieve this goal, 4-year-old potted mulberry plants were selected for research, and a waterlogging simulation method was implemented. Four treatments were established to investigate the effects of varying water conditions on leaf waterlogging damage, the number of ARs, plant height, chlorophyll fluorescence parameters, and proton motive force (pmf) parameters in mulberry plants. These treatments included the control group (CK), shallow submerged group (SS), half-submerged group (HS) and deep submerged group (DS). Our results showed that (1) The number of ARs in each group increased with increasing waterlogging time. (2) Waterlogging stress inhibited the height growth of mulberry, and the changes in plant height in the HS and DS groups were significantly lower than those in the CK and SS groups. (3) The maximum photochemical quantum yield (Fv/Fm) in the HS and DS groups decreased significantly under waterlogging stress. The nonphotochemical quenching (NPQt) of mulberry leaves in the submergence group increased significantly in the early stage of waterlogging stress, and the NPQt in the submergence group increased continuously with increasing waterlogging time. (4) Thylakoid conductivity to protons (gH+) in the leaves of mulberry decreased significantly under waterlogging stress, whereas the steady-state rate of proton flux (vH+) and total electrochromic shift (ECSt) increased significantly. The morphological, physiological, and ecological responses of mulberry plants to waterlogging stress include the timely generation of ARs at the stem base, the adjustment of plant growth strategies, and the repair of photosynthetic response centers in leaves through heat dissipation and thylakoid acidification mechanisms.

Methodical and algorithmic aspects of mathematical modeling of a screw aircraft power plant

The article describes the solution of a scientific problem that consists in expanding the functionality of the program “Calculation of the traction-economic and mass-specific characteristics of the power plant and aircraft motion parameters” through the introduction of additional algorithms and mathematical models for calculating the altitude-speed characteristics of screw aircraft power installations. At the same time, an internal calculation of the aircraft propeller thrust is used according to experimental aerodynamic coefficients, which makes it possible to increase the efficiency and reliability of complex theoretical studies of power plants of various types as part of aircraft at the stage of external design. A description is given of the developed algorithms: an algorithm for converting power on the output shaft of a gas turbine engine into thrust of an aircraft power plant; a mathematical model of a propeller that provides calculation of its thrust from experimental aerodynamic coefficients; an algorithm for determining the thrust of the power plant, taking into account the compressibility of the air and the interaction of the propeller and the elements of the airframe of the aircraft. Some features of the mathematical modeling of an aircraft propeller are revealed, in particular, the principle of propeller control by influencing the blade angle and rotational speed depending on the aircraft flight speed and a method for constructing the field of aerodynamic characteristics of an aircraft propeller in a wide range of blade angle and speed coefficient. In conclusion, the results of verification of the modified program are presented with an analysis of the obtained altitude-speed characteristics.

Estimation Network for Multiple Chemical Parameters of Astragalus Leaves Based on Attention Mechanism and Multivariate Hyperspectral Features

In the context of smart agriculture, accurately estimating plant leaf chemical parameters is crucial for optimizing crop management and improving agricultural yield. Hyperspectral imaging, with its ability to capture detailed spectral information across various wavelengths, has emerged as a powerful tool in this regard. However, the complex and high-dimensional nature of hyperspectral data poses significant challenges in extracting meaningful features for precise estimation. To address this challenge, this study proposes an end-to-end estimation network for multiple chemical parameters of Astragalus leaves based on attention mechanism (AM) and multivariate hyperspectral features (AM-MHENet). We leverage HybridSN and multilayer perceptron (MLP) to extract prominent features from the hyperspectral data of Astragalus membranaceus var. mongholicus (AMM) leaves and stems, as well as the surface and deep soil surrounding AMM roots. This methodology allows us to capture the most significant characteristics present in these hyperspectral data with high precision. The AM is subsequently used to assign weights and integrate the hyperspectral features extracted from different parts of the AMM. The MLP is then employed to simultaneously estimate the chlorophyll content (CC) and nitrogen content (NC) of AMM leaves. Compared with estimation networks that utilize only hyperspectral data from AMM leaves as input, our proposed end-to-end AM-MHENet demonstrates superior estimation performance. Specifically, AM-MHENet achieves an R2 of 0.983, an RMSE of 0.73, an MAE of 0.49, and an RPD of 7.63 for the estimation of CC in AMM leaves. For NC estimation, AM-MHENet achieves an R2 value of 0.977, an RMSE of 0.27, an MAE of 0.16, and an RPD of 6.62. These results underscore AM-MHENet’s effectiveness in significantly enhancing the accuracy of both CC and NC estimation in AMM leaves. Moreover, these findings indirectly suggest a strong correlation between the development of AMM leaves and stems, as well as the surface and deep soil surrounding the roots of AMM, and directly highlight the ability of AM to effectively focus on the relevant spectral features within the hyperspectral data. The findings from this study could offer valuable insights into the simultaneous estimation of multiple chemical parameters in plants, thereby making a contribution to the existing body of research in this field.