Shading Conditions Research Articles

Phytochrome-mediated shade avoidance responses impact the structure and composition of the bacterial phyllosphere microbiome of Arabidopsis

The shade avoidance response triggers a dramatic promotion of elongation growth, accompanied by a significant reprogramming of metabolic pathways as plants seek to prevent overtopping and adapt to vegetative shade. Here we demonstrate that simulated vegetative shade results in significant changes in the structure and composition of the phyllosphere bacterial microbiome. Our study uncovered significant shifts in the diversity, occurrence, abundance and activity of bacteria within the phyllosphere microbiome. A comparison of responses in both wild-type plants and phytochrome mutants, which inherently exhibit a shade-avoidance phenotype, revealed both indirect responses to host plant physiology and direct responses to light among the microbiota. Hierarchical clustering of response patterns further suggested that over a third of the taxa constituting the core phyllosphere microbiome in our assay show some degree of response to vegetative shade. Bacteria that increased in abundance on plants with a shade-avoidance phenotype corresponded to genera associated with beneficial traits such as enhanced disease resistance and growth promotion. Our findings suggests that plants manipulate their phyllosphere microbiome under shade conditions as a strategy to optimise fitness when competing for light. We discuss the implications of our findings in terms of furthering our understanding of plant-microbe signalling in the shaping of the phyllosphere microbiome and the possibility of manipulating the phyllosphere microbiome for plant health in an agricultural setting at high planting densities.

Mitigating the Impact of Partial Shading Conditions on Photovoltaic Arrays Through Modified Bridge-Linked Configuration

Global reliance on depleting energy resources is driving the urgent need for alternative solutions to address escalating energy demands. Solar energy, a prominent renewable resource, leverages various configurations and techniques to maximize power output, even under challenging environmental conditions. In photovoltaic (PV) arrays, partial shading conditions (PSCs) significantly hinder efficiency by reducing power extraction across solar panels. Traditionally, configurations such as series, parallel, series-to-parallel, and bridge-linked (BL) are employed to optimize power output; however, each has limitations under PSCs. Here, we introduce a modified bridge-linked (Modified BL) configuration designed to mitigate the adverse effects of partial shading on PV arrays. This approach allows for interconnected solar modules that reduce shading impact across an entire array, thus preserving efficiency by isolating shaded sections and minimizing power loss. The Modified BL configuration not only supports maximum power point tracking (MPPT) but also enhances resilience against shading, ensuring stable power output. Our simulation results underscore the critical influence of irradiance levels on PV electricity generation, suggesting that incorporating irradiance variability as a design parameter is essential in selecting optimal PV interconnection schemes under PSCs. This study contributes to advancing solar array design by providing a robust method to maintain power output in partial shading conditions, ultimately supporting broader efforts in renewable energy optimization.

Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm

Due to environmental factors’ influence, the power–voltage (P–V) curve of a photovoltaic array typically presents multiple peaks. The traditional gravitational search algorithm is inclined to fall into local optimal solutions and demonstrates poor performance in maximum power point tracking. Consequently, this paper proposes applying the PSO algorithm for optimizing the GSA parameters. Meanwhile, introducing the gravitational constant into the GSA algorithm accomplishes the dynamic adjustment of the three key parameters in PSO. Furthermore, the Levy flight step is incorporated to enhance the global search capability. The improved algorithm can improve the search speed and accuracy by adding memory and group interaction to the particle update formula to alleviate oscillation. Simulink modeling and simulation analysis reveals that, compared with traditional algorithms, the improved algorithm can identify the maximum power point of the photovoltaic array more rapidly and stably under static and dynamic shading conditions.

A novel global maximum power point tracking based on flamingo search algorithm for photovoltaic systems

Due to the high dependency of photovoltaic (PV) solar cell’s output on solar irradiance and, the ambient temperature. Maximum power point tracking (MPPT) algorithms are used extensively to operate the system at its full potentials. Moreover, being installed in outdoor spaces, PV modules are inevitably subjected to partial shading conditions, where different parts of the system are receiving different amounts of solar irradiance. In case of occurrence of partial shading conditions on a PV module that is equipped with bypass diodes, the power-voltage (P-V) curve will have multiple peaks. This multi-peak curve requires using an advanced algorithm which track the global maximum power point (GMPP) instead of being deceived and trapped in a local maximum power point. In this paper, the flamingo search algorithm (FSA) is adapted for GMPP tracking for a PV system under partial shading conditions. The FSA algorithm fetch for the GMPP by reading the PV panel power and setting accordingly the duty cycle of the buck converter. To investigate model validity, simulation is performed using the MATLAB/Simulink platform and results demonstrate good tracking performance and fast response that prove the robustness of the system against rapid variations in solar irradiance levels.

A robust MPPT method based on optimizable Gaussian process regression and high order sliding mode control for solar systems under partial shading conditions

A robust MPPT method based on optimizable Gaussian process regression and high order sliding mode control for solar systems under partial shading conditions

Variability of yield and yield components of 23 hybrid cayenne pepper (Capsicum frutescens) genotypes under shaded and unshaded conditions

Abstract. Putri DRM, Syukur M, Ritonga AW. 2025. Variability of yield and yield components of 23 hybrid cayenne pepper (Capsicum frutescens) genotypes under shaded and unshaded conditions. Biodiversitas 26: 396-406. Cayenne pepper production is challenged by limited agricultural land, necessitating a sustainable intercropping system to meet rising demand. This requires varieties that can grow, develop, and produce under shade-stress conditions. This study aimed to obtain information on the variability of growth, yield components, and physiological traits and to determine yield-related traits in cayenne pepper hybrids obtained from full-diallel crosses under shaded and unshaded conditions. A total of 23 genotypes, consisting of 20 F1 hybrids from five parental lines and three comparisons, were planted using a nested randomized complete block design with two factors: shade and genotype. The results showed that G8 and G27 exhibited superior performance under shade conditions, producing a higher number of fruits per plant, fruit yield per plant, marketable number of fruits, marketable yield fruit, fruit diameter, and fruit weight compared to unshaded conditions. These findings have practical implications for cayenne pepper production, as they can guide the selection of varieties for shaded conditions. Chili was categorized into six clusters under unshaded conditions and four clusters under shaded conditions. Marketable yield fruit, marketable number of fruits, and number of fruits per plant had a significant positive correlation coefficient on fruit yield per plant under unshaded conditions. In contrast, under shaded conditions, there was a significant positive correlation shown on fruit diameter, plant height, marketable yield fruit, number of fruits per plant, marketable number of fruits, and fruit weight.

БИОХИМИЯ И БИОЛОГИЯ ОБРАЗЦОВ ЧЕТЫРЕХ ВИДОВ ЛУКА ЧЕРЕМШИ В КУЛЬТУРЕ В РЕСПУБЛИКЕ БАШКОРТОСТАН

The pape presents the data of a study of 6 samples of wild garlic onion, which were carried out in the South Ural Botanical Garden-Institute of the Ural Federal Research Center of the Russian Academy of Sciences in 2018–2022, (Bashkir Cis-Urals, northern forest-steppe). Plantings of A. ochotense accessions (Syktyvkar and Irkutsk) are located in an open sunny area, plantings of the Syktyvkar accession A. victorialis are located in an open area and in the shade, plantings of A. microdictyon, A. ursinum and A. victorialis (VILAR) are in shade conditions. Biochemical analyzes were performed at the Bashkirsky Agrochemical Service Center according to generally accepted methods. The study of phenology, morphological and reproductive parameters was carried out according to standard methods recommended for botanical gardens. Studies showed that the greatest accumulation of ascorbic acid was noted in the victorious onion (Syktyvkar, 62.91 mg%), the lowest accumulation was in fine-meshed onion (Bashkortostan, 48.74 mg%), based on fresh weight. Victorious onion samples (Irkutsk, VILAR) differed in the maximum content of the following most important biologically active substances: carotene (1.68–2.89 mg/100 g), dry matter (22.81–25.23 %), crude fat (1 .04–1.13 %), protein (3.69–4.38 %), nitrogen (0.59–0.70 %), sugar (4.34–4.79 %), starch (0.41–0.95 %), potassium (0.36–0.4 %), phosphorus (0.11–0.12 %), calcium (0.08-0.09 %) and copper (1.09–1 .65 mg/kg) (based on fresh weight). The content of the minimum amount of the following biologically active substances was noted in bear onion (VILAR): dry matter (10.91 %), crude fat (0.50 %), protein (1.81 %), nitrogen (0.29 %), sugar (2.20 %). In the conditions of the sharply continental climate of the Republic of Bashkortostan, wild garlic onion samples are winter hardy, not damaged by pests and diseases. Seed productivity is satisfactory, vegetative propagation and general condition is good. Out of six samples of four types of wild garlic onion, the samples of A. victorialis have the highest indicators in terms of the content of biologically active substances. The studied samples of wild garlic are promising plants for cultivation in the Republic of Bashkortostan, as well as in the South Ural Region. This allows us to recommend them for expanding the range of useful (vitamin) and ornamental plants.

A Universal Visual Detection Method for Camellia oleifera Fruit Picking Robot

ABSTRACTIn recent years, the application of robots in the field of fruit picking has steadily increased. Mechanized methods for harvesting oil tea fruits include comb picking, vibratory picking, and gripping picking, among others. Traditional reliance on a single‐picking method is limited by variability in fruit size, shading, and environmental conditions. To develop a universal vision system suitable for picking robots capable of multiple picking methods and achieve intelligent harvesting of oil tea fruits. This paper proposes an enhanced You Only Look Once v7 (YOLOv7)‐based oil tea fruits recognition method specifically designed for subsequent clamp or comb picking. The network's feature extraction capability is enhanced by incorporating an attention mechanism, an optimized small target detection layer, and an improved training loss function, thereby improving its detection of occluded and small target fruits. An innovative Automatic Assignment (AA) method clusters and subclusters the detected oil tea fruits, providing crucial fruit distribution data to optimize the robot's picking strategy. Additionally, for vibration harvesting, this paper introduces a vibration point detection method utilizing the Pyramid Scene Parsing Network (PSPNet) semantic segmentation network combined with connectivity domain analysis to identify vibration points on the trunks and branches of oil tea trees. Experimental results demonstrate that the generalized visual detection method proposed in this study surpasses existing models in identifying oil tea fruit trees, with the enhanced YOLOv7 model achieving mean average precision, recall, and accuracy of 91.7%, 94.0%, and 94.9%, respectively. The AA method achieves clustering and subclustering of oil tea fruits with a processing delay of under 5 ms. For vibration harvesting, PSPNet achieves branch segmentation precision, recall, and intersection ratio of 97.3%, 96.5%, and 94.5%, respectively. The proposed branch vibration point detection method attains a detection accuracy of 93%, effectively pinpointing vibration points on the trunks and branches of oil tea trees. Overall, the proposed visual method can be implemented in robots using various picking techniques to enable automated harvesting.

Spectral comparison between diffuse PAR irradiance received under the shade of nine trees in different heights and a cloudy day in summer.

Spectral Solar Photosynthetically Photon Flux Density (PPFD) (380-780 nm) reaching the surface in different tree shade conditions and heights has been analyzed in order to better understand the different photosynthetic performance of plants depending on their spatial situation, the canopy density and height with respect to the floor. A comparison between the shadow of nine different trees in a sunny day and the case of a cloudy day in an open space has been studied. A poplar, laurel, amber tree, pine, olive tree, fir tree, cypress, elm tree and magnolia tree have been analyzed. The study has been developed in Valencia (Spain) during July and August 2022. Conditions with higher PPFD received are found to be, apart from those of a sunny day, those for cloudy day, and those for the shade of cypress. The case in which less amount of PPFD is received is that under the shade of olive tree. Both with a spectral maximum in the Blue region. It is also remarkable that the PPFD radiation is proportional to the height of measurement at 10 h, but this relationship changes, and at 13 h the relationship between irradiance received and height of measurement is inversely proportional.

Application of Flower Pollination Algorithm and its Comparative Analysis for MPPT of Solar Panels Under Partial Shading Conditions

Application of Flower Pollination Algorithm and its Comparative Analysis for MPPT of Solar Panels Under Partial Shading Conditions

Voltage Unbalance Control Strategy for Local Shading Photovoltaic Grid-Connected System

In view of the sudden grid voltage distortions, such as voltage sags and unbalances, that may occur in photovoltaic (PV) grid-connected systems under local shading conditions, this paper proposes a control strategy integrating a linear active disturbance rejection controller (LADRC)-based virtual synchronous generator (VSG) and an active disturbance rejection controller (ADRC)-based dynamic voltage restorer (DVR). To enhance the stability and response speed of the PV inverter system, a novel LADRC-based voltage–current dual closed-loop control strategy with pre-synchronization is designed, ensuring stable operation of the inverter and load. To address the overshooting issues found in traditional PI control under local shading, the ADRC-based DVR compensates for PV system voltage fluctuations, achieving rapid voltage distortion compensation and ensuring grid-connected system safety. Simulink experiments verify the feasibility and effectiveness of the proposed control strategy in improving transient voltage quality in PV systems affected by local shading. The total harmonic distortion rates of voltage and current are both less than 0.5%, which significantly improves the performance compared to existing research.

An Approach Based on Golden Eagle Optimization Algorithm for Maximum Power Point Tracking of PV Panel Under Partial Shading Conditions

This study introduces an innovative Maximum Power Point Tracking (MPPT) technique utilizing the Golden Eagle Optimization (GEO) method, specifically designed to enhance the efficiency of photovoltaic (PV) systems under partial shading conditions. Unlike traditional MPPT approaches that struggle with local peaks in power-voltage curves caused by shading, the GEO method leverages the hunting behavior-inspired algorithm to accurately locate the global maximum power point (GMPP). The effectiveness of the GEO MPPT technique is demonstrated through extensive simulations across three diverse case scenarios, each representing different partial shading patterns. In all scenarios, the GEO method outperforms conventional MPPT techniques, showcasing its adaptability and superior performance in challenging conditions. The successful implementation of GEO MPPT leads to substantial improvements in PV panel energy extraction efficiency, even when faced with the complexities of partial shading. This research contributes significantly to the advancement of solar PV systems, enhancing their reliability and performance in real-world environments. By mitigating the impact of partial shading, this work promotes the wider adoption of solar energy as a viable and sustainable power solution.

Characterization of feeding damage by tea mosquito bug, Helopeltis theivora Waterhouse (Hemiptera: Miridae) on Hainan Dayezhong tea cultivar.

The tea mosquito bug, Helopeltis theivora Waterhouse (Hemiptera: Miridae), is a devastating piercing-sucking pest in tropical tea plantations. The Hainan Dayezhong (HNDYZ) is a large-leaf tea cultivar widely cultivated around the Hainan tea region in South China. However, information regarding the feeding damage of H. theivora on the HNDYZ tea plant remains scarce. Here, we first describe the morphology of H. theivora in Hainan tea region. Subsequently, we investigate the feeding biology of H. theivora on HNDYZ tea shoots under laboratory conditions. Additionally, we survey the infestations of H. theivora in a small-leaf Jinxuan tea plantation and three large-leaf HNDYZ tea plantations under varying shaded conditions. The results indicated that the morphological features of eggs, nymphs, and adults of H. theivora in the Hainan tea region were similar to those of the same species reported in other tropical tea regions. Nymphs and adults of H. theivora primarily fed on tender leaves and produced a subcircular spot within 2 to 4 minutes. This feeding spot would gradually turn dark brown within 24 hours. Furthermore, the adjacent scattered spots would connect after 48 hours, resulting in a necrotic patch on the leaves by 72 hours. The peak feeding time for H. theivora occurred at night, specifically from 7:00 PM to 1:00 AM. The most preferred feeding site was at the second leaf position, accounting for 70.94 ± 3.68% of daily feeding spots. During the feeding peak, adults H. theivora produced more feeding spots than nymphs, with females and 5th-instar nymphs creating the largest feeding areas among all life stages. Field investigations showed that damage caused by H. theivora on the large-leaf HNDYZ tea cultivar was significantly greater than that on the small-leaf Jinxuan tea cultivar. More serious infestations of H. theivora were observed in the high-shade HNDYZ tea plantation compared to the medium-shade and no-shade HNDYZ tea plantations. This suggests that the different tea cultivars and shade conditions in tea plantations may influence the population of H. theivora in the field. These findings provide new insights for further research related to the feeding strategy of H. theivora on the HNDYZ tea cultivar.

DC series arc fault detection method using LDA-CatBoost for PV system under shaded condition

Abstract Detecting DC series arc faults (SAFs) in photovoltaic (PV) systems is challenging due to shaded conditions. A detection method for SAFs in PV systems focusing on shaded conditions is proposed in this paper. By analyzing voltage–current characteristics under different shaded scenarios and the interaction of arc and PV sources to ignite arc faults, the DC SAFs are classified into three types: strong, weak, and intermittent arcs, and then the DC arc features under various shaded conditions are investigated from the current signals. Then, a linear discriminant analysis (LDA)-CatBoost method is proposed to detect and identify SAFs using the features from extracting both time- and frequency-domain current signals. Experimental results demonstrate that the detection and identification accuracy is 98% under various shaded conditions. It significantly improves SAF detection applicability compared with other methods.

A Hybrid Dual-Axis Solar Tracking System: Combining Light-Sensing and Time-Based GPS for Optimal Energy Efficiency

Fixed solar panels face significant energy loss as they cannot consistently capture optimal sunlight. Because of that, the overall efficiency of the PV panel will be reduced, and the installation requires larger land space to generate appropriate power; this stems from the use of a dual-axis solar tracking system, which can significantly increase overall energy production. The system is based on the combination of two approaches to precisely track the sunlight: first, using multiple LDRs (light-dependent resistors) as photo sensors to track the position of the sun by balancing the resistivity using a proportional integral deprival (PID) controller, and the second approach using the time-based control for cloudy days when sunlight is diffused, getting the time GPS coordinates and time to calculate the accurate position of the sun by determining the azimuth and altitude angle. This dual system significantly improves energy production by 33.23% compared to fixed systems and eliminates errors during shaded conditions while reducing unnecessary energy use from continuous GPS activation. The prototype uses two linear actuators for both angles and a 100-watt solar panel mounted on the dual-axis platform.

Maximum power point tracking control of photovoltaic systems using a hybrid improved whale particle swarm optimization algorithm

ABSTRACT Maximum power point tracking (MPPT) control techniques are commonly employed to maximize the benefits and enhance the operational efficiency of photovoltaic systems in challenging outdoor environments. However, when the photovoltaic array is subjected to partial shading conditions, the conventional MPPT methods exhibit inadequate global maximum power point (GMPP) tracking performance. To this end, in this study, an effective MPPT control method for photovoltaic systems is proposed based on a hybrid improved whale particle swarm optimization algorithm (IWPOA). The control method integrates the advantages of the Improved Whale Optimization Algorithm (IWOA) and the Particle Swarm Algorithm (PSO) with additional control and stochastic elements. Validation analysis under a variety of conditions reveals that IWPOA significantly improves MPPT, achieving a tracking speed of approximately 0.13 s, which represents a 18.75–53.57% enhancement over other comparative algorithms. The mean tracking accuracy of IWPOA is 99.21%, and it offers superior tracking stability, making it suitable for diverse applications in MPPT.

Retrieval of Vegetation Indices and Vegetation Fraction in Highly Compact Urban Areas: A 3D Radiative Transfer Approach

Vegetation indices, especially the normalized difference vegetation index (NDVI), are widely used in urban vegetation assessments. However, estimating the vegetation abundance in urban scenes using the NDVI has constraints due to the complex spectral signature related to the urban structure, materials and other factors compared to natural ground surfaces. This paper employs the 3D discrete anisotropic radiative transfer (DART) model to simulate the spectro-directional reflectance of synthetic urban scenes with various urban geometries and building materials using a flux-tracking method under shaded and sunlit conditions. The NDVI is calculated using the spectral radiance in the red (0.6545 μm) and near-infrared bands (0.865 μm). The effects of the urban material heterogeneity and 3D structure on the NDVI, and the performance of three NDVI-based fractional vegetation cover (FVC) inversion algorithms, are evaluated. The results show that the effects of the building material heterogeneity on the NDVI are negligible under sunlit conditions but not negligible under shaded conditions. The NDVI value of building components within synthetic scenes is approximately zero. The shaded road exhibits a higher NDVI value in comparison to the illuminated road because of scattering from adjacent pixels. In order to correct the effects of scattering caused by building geometry, the reflectance of the Landsat 8/OLI image is corrected using the sky view factor (SVF) and then used to calculate the FVC. Jilin-1 satellite images with high spatial resolution (0.5 m) are used to extract the vegetation cover and then aggregated to 30 m spatial resolution to calculate the FVC for validation. The results show that the RMSE is up to 0.050 after correction, while the RMSE is 0.169 before correction. This study makes a contribution to the understanding of the effects of the urban 3D structure and material reflectance on the NDVI and provides insights into the retrieval of the FVC in different urban scenes.

Hybrid salp swarm maximum power point tracking algorithm for photovoltaic systems in highly fluctuating environmental conditions

The maximum power delivered by a photovoltaic system is greatly influenced by atmospheric conditions such as irradiation and temperature and by surrounding objects like trees, raindrops, tall buildings, animal droppings, and clouds. The partial shading caused by these surrounding objects and the rapidly changing atmospheric parameters make maximum power point tracking (MPPT) challenging. This paper proposes a hybrid MPPT algorithm that combines the benefits of the salp swarm algorithm (SSA) and hill climbing (HC) techniques. As long as the rate of change of irradiance does not exceed a specific limit, the HC mode is applied to track the global maximum power point (GMPP). Once a high rate of change in irradiation is detected, the SSA mode is activated. Moreover, the proposed algorithm employs the concept of boundary conditions to handle fast and slow fluctuating irradiance patterns. A comprehensive comparative evaluation of the proposed hybrid SSA-HC with state-of-the-art MPPT algorithms has been undertaken. Four distinct cases have been examined, including irradiance conditions with varying rates of change and partial shading conditions. The proposed hybrid SSA-HC algorithm has been validated and tested using a developed hardware setup, simulated in MATLAB for solar photovoltaic (PV) systems, and compared with standard SSA and HC. The performance of the tracking capability of this proposed hybrid technique at both steady-state and dynamic conditions under rapid and gradual irradiance changes demonstrates its superiority over recent state-of-the-art algorithms.

Global maximum power point tracking for photovoltaic systems under partial and complex shading conditions using a PID based search algorithm (PSA)

AbstractIn scenarios of partial shading, the effectiveness of power transmission within a photovoltaic system experiences a notable decline, potentially leading to hotspots within the photovoltaic array. While incorporating bypass diodes can mitigate this challenge, it may lead to numerous power peaks along the power–voltage (P–V) characteristics, thus complicating the task of maximum power tracking. Addressing this issue, using metaheuristic algorithms for maximum power point tracking (MPPT) offers promising outcomes by circumventing convergence towards local power peaks and easing the computational strain on the microcontroller. This study presents a fresh approach to MPPT technique utilizing the proportional–integral–derivative‐based search algorithm to effectively identify the MPP under varying partial shading conditions. Compared to existing methods, the proposed algorithm demonstrates superior performance in power tracking efficiency, tracking time, stability with fewer fluctuations, and achieving higher maximum power output. Evaluation against state‐of‐the‐art algorithms like particle swarm optimization and JAYA confirms the effectiveness of the proposed MPPT technique. MATLAB/Simulink software‐based analysis and its validation using real‐time analysis from the typhoon based hardware‐in‐the‐loop (HIL‐402) emulator support its efficacy.

Solar radiation alters heat balance and thermoregulation in a flying desert bee.

Solar radiation is an important environmental variable for terrestrial animals, but its impact on the heat balance of large flying insects has been poorly studied. Desert bees are critical to ecosystem function through their pollination services, and are exposed to high radiant loads. We assessed the role of solar radiation in the heat balance of flying desert Centris pallida bees by calculating heat budgets for individuals in a respirometer in shaded versus sunny conditions from 16 to 37°C air temperatures, comparing the large and small male morphs and females. Solar radiation was responsible for 43 to 54% of mean total heat gain. Bees flying in the sun had thorax temperatures 1.7°C warmer than bees flying in the shade, storing a very small fraction of incident radiation in body tissues. In most cases, flight metabolic rate was not suppressed for bees flying in the sun, but evaporative water loss rates more than doubled. The most dramatic response to solar radiation was an increase in convection, mediated by a more than doubling of convective conductance, allowing thermoregulation while conserving body water. In large morph males and females, the increased convective conductance in the sun was mediated by increased heat transfer from the thorax to abdomen. Because convection is limited as body temperatures approach air temperatures, solar radiation combined with warming air temperatures may cause endothermic flying bees to reach a tipping point at which increases in non-sustainable evaporation are necessary for survival.