Shading Conditions Research Articles

Genome-Wide Identification of B-Box Family Genes and Their Potential Roles in Seed Development under Shading Conditions in Rapeseed.

B-box (BBX) proteins, a subfamily of zinc-finger transcription factors, are involved in various environmental signaling pathways. In this study, we conducted a comprehensive analysis of BBX family members in Brassica crops. The 482 BBX proteins were divided into five groups based on gene structure, conserved domains, and phylogenetic analysis. An analysis of nonsynonymous substitutions and (Ka)/synonymous substitutions (Ks) revealed that most BBX genes have undergone purifying selection during evolution. An analysis of transcriptome data from rapeseed (Brassica napus) organs suggested that BnaBBX3d might be involved in the development of floral tissue-specific RNA-seq expression. We identified numerous light-responsive elements in the promoter regions of BnaBBX genes, which were suggestive of participation in light signaling pathways. Transcriptomic analysis under shade treatment revealed 77 BnaBBX genes with significant changes in expression before and after shading treatment. Of these, BnaBBX22e showed distinct expression patterns in yellow- vs. black-seeded materials in response to shading. UPLC-HESI-MS/MS analysis revealed that shading influences the accumulation of 54 metabolites, with light response BnaBBX22f expression correlating with the accumulation of the flavonoid metabolites M46 and M51. Additionally, BnaBBX22e and BnaBBX22f interact with BnaA10.HY5. These results suggest that BnaBBXs might function in light-induced pigment accumulation. Overall, our findings elucidate the characteristics of BBX proteins in six Brassica species and reveal a possible connection between light and seed coat color, laying the foundation for further exploring the roles of BnaBBX genes in seed development.

Growth and Yield of Two Mustard Varieties (Brassica Juncea L.) at Various Shading Levels

Mustard greens are one of the vegetable commodities plants. The part used is the young leaves, which can be processed into traditional medicinal and vegetable ingredients that benefit human health. This research aims to determine the level of shade tolerance on the growth and yield of mustard plants and determine mustard varieties that are tolerant of minimum sunlight conditions. This research was carried out in experimental fields using artificial fields in June – July 2023. This research used a split-plot design with 2 factors. Tafif shade as the main plot consists of no shade 0%, 55%, 70%, and 95%. The sub-plot varieties consist of the Tosakan variety and the Kumala variety. The results of the research indicate that sunlight intensity reduction negatively impacted the growth and yield of mustard plants. However, under 55% shade conditions, there was no significant difference observed in the growth and yield of mustard plants compared to those grown without shade. The Tosakan and Kumala varieties did not show any differences in the growth or yield of mustard plants.

Growth and Yield of Two Mustard Varieties (Brassica Juncea L.) at Various Shading Levels

Mustard greens are one of the vegetable commodities plants. The part used is the young leaves, which can be processed into traditional medicinal and vegetable ingredients that benefit human health. This research aims to determine the level of shade tolerance on the growth and yield of mustard plants and determine mustard varieties that are tolerant of minimum sunlight conditions. This research was carried out in experimental fields using artificial fields in June – July 2023. This research used a split-plot design with 2 factors. Tafif shade as the main plot consists of no shade 0%, 55%, 70%, and 95%. The sub-plot varieties consist of the Tosakan variety and the Kumala variety. The results of the research indicate that sunlight intensity reduction negatively impacted the growth and yield of mustard plants. However, under 55% shade conditions, there was no significant difference observed in the growth and yield of mustard plants compared to those grown without shade. The Tosakan and Kumala varieties did not show any differences in the growth or yield of mustard plants.

Retraction Note: Rigorous reduction of partial shading condition in grid connected solar PV system using discrete time-based PSO controller

Retraction Note: Rigorous reduction of partial shading condition in grid connected solar PV system using discrete time-based PSO controller

Intelligent Solar System for Effective Renewable Energy

Photovoltaic (PV) systems are gaining popularity as a sustainable and renewable energy solution. Charge controllers play a crucial role in maximizing the energy harvested from PV panels and ensuring efficient battery charging. This study presents a comprehensive comparison between Pulse Width Modulation (PWM) and Maximum Power Point Tracking (MPPT) charge controllers, analyzing their performance, efficiency, and suitability for different PV system configurations. The analysis begins with an overview of PWM charge controllers, which regulate the charging process by rapidly switching the PV panel voltage on and off. PWM controllers are known for their simplicity, affordability, and reliability. However, their fixed voltage operation limits their ability to extract maximum power from the PV panels, especially in scenarios with varying solar irradiance and temperature conditions. In contrast, MPPT charge controllers employ advanced algorithms to continuously track the maximum power point (MPP) of the PV panels. By dynamically adjusting the operating voltage and current, MPPT controllers can optimize the power transfer from the PV panels to the battery bank. This capability results in higher energy harvesting, especially in situations with partial shading or non-ideal operating conditions.

Advanced particle swarm optimization for efficient and fast global maximum power point tracking under partial shading conditions

Partial shading (PS) is a common issue in photovoltaic systems (PVs), and it can significantly reduce the system's output power. This paper presents the advanced particle swarm optimization (APSO) algorithm. APSO is designed to alleviate the challenges posed by PS in PVs in from where of effectiveness and stability speed so that it works to achieve and maintain the global maximum power point (GMPP) under PS conditions. It leverages persistent variables to store and track system states and iterations; it also includes checks to ensure that the duty cycle remains within specified bounds facilitating more effective optimization. Additionally, APSO optimizes solar panel duty cycles and velocities to converge toward an optimal solution to improve overall power generation efficiency and settling time. The results evaluation involves testing the performance of photovoltaic panels under three different shading scenarios and comparative analysis against recent Heuristic-optimization-based GMPP techniques, this study and comparative analyses demonstrate APSO's effectiveness and superiority in terms of high efficiency that reaches 99.85% and fast settling time of GMPP at less than 0.01 second across all test cases. APSO presents a promising solution for maximizing PV power output in the presence of partial shading.

Genome-wide identification and expression analysis of phytochrome-interacting factor genes during abiotic stress responses and secondary metabolism in the tea plant

Phytochrome-interacting factors (PIFs) are pivotal transcriptional regulators controlling photomorphogenesis, environmental responses, and development in plants. However, their specific roles in coordinating adaptation towards abiotic stress and metabolism remain underexplored in tea plants. Here, we identified seven PIF members from four distinct clades (PIF1, PIF3, PIF7, and PIF8). Promoter analysis implicated CsPIFs in integrating light, stress, hormone, and circadian signals. Most CsPIFs exhibited rapid increase in expression under shading, especially CsPIF7b/8a, which displayed significant changes in long-term shading condition. Under drought/salt stress, CsPIF3b emerged as a potential positive regulator. CsPIF3a was induced by low temperature and co-expressed with CsCBF1/3 and CsDREB2A cold response factors. Dual-luciferase assays confirmed that act as negative regulator of the CBF pathway. Expression profiling across 11 tea cultivars associated specific CsPIFs with chlorophyll biosynthesis and accumulation of anthocyanins, flavonols, and other metabolites. In summary, this study highlights the significance of CsPIFs as central coordinators in managing intricate transcriptional reactions to simultaneous abiotic stresses and metabolic adjustments in tea plants. This insight informs future strategies for enhancing this economically crucial crop through crop improvement initiatives.

The Effect of Climate on Strongly Disturbed Vegetation of Bait Sites in a Central European Lower Montane Zone, Hungary

Human landscape-transforming activities contribute to the global change in vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We investigated the vegetation dynamics over several years in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). Important background factors are the changes in precipitation and temperature. Our results confirm that weed infestation is detectable at bait sites over a long period. The seasonal changes in field weed vegetation, as well as the increase in the number and coverage of weed species at the end of summer, resulting from lifestyle characteristics, were generally detectable in all years and locations, especially in the case of open and more strongly degraded clearings. Meteorological factors played a role in the degree of weed infestation in each year. Degradation was more significant in drought years, while regeneration was also observed in wetter periods. At baits located in the clearing, we showed a positive correlation between the amount of summer precipitation and the total coverage of weed species, as well as between the average spring temperature and the coverage of certain weed species. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. Considering that there are approx. 30,000 bait sites in the country, and they are used regularly and very intensively, they can serve as major infection hotspots for alien species in a network.

The light intensity in the cultivation environment and the impact of glyphosate on plants of the Urochloa genus

The variation in light within the environment triggers morphophysiological changes in plants and can lead to distinct responses in sun-exposed or shaded plants to glyphosate. The response of Urochloa genotypes subjected to desiccation with 2160, 1622.4, 1080, 524.4, 273.6, and 0.0 g ha−1 of glyphosate was evaluated in full sun and shade conditions. Cayana grass, mulato II grass, and sabiá grass – hybrids recently launched on the market, in addition to palisade grass and congo grass were evaluated. Under full sun, we achieved control of congo grass using 1080 g ha−1 of glyphosate, while the other grasses required 2160 g ha−1. In the low-light environment, sabiá grass was effectively controlled with 524.4 g ha−1 of glyphosate, but the other grasses needed 273.6 g ha−1. In shading, compared to full sun, the savings with glyphosate were 75 and 76% for the control of congo grass and sabiá grass, respectively, and 87% for palisade grass, mulato II grass and cayana grass. Increasing glyphosate doses leads to a decline in the quantum efficiency of photosystem II and in the electron transport rate, especially in the shade. Urochloa genotypes are more sensitive to glyphosate in the shade, which must be considered when determining the herbicide dose.

Application of circle search algorithm for solar PV maximum power point tracking under complex partial shading conditions

Solar photovoltaic (SPV) energy exhibits a potential role in the world for generating electricity and avoiding the block out in the power system. However, the hardest task in the PV system is to track the global maxima power (GPP) instead of local peak power (LPP) under partial shading conditions (PSC). To track the GPP, a new circle search algorithm (CSA) is implemented in this paper and is executed in MATLAB/SIMULINK environment. This method is examined at various irradiation conditions and compared their performance with other studied methods in terms of tracking time, settling time and efficiency. The simulation outcome of the CSA method efficiencies 99.96 % in case 1, 99.74 % in case 2, and 99.94 % in case 3. For checking the robustness and stability of the system statistical analysis was done on the proposed methods. It is found that the suggested method exhibits higher performance than the other methods.

A modified invasive weed optimization for MPPT of PV based water pumping system driven by induction motor

A novel approach called Modified Invasive Weed Optimization (MIWO) technique has been developed and combined with the Perturb and Observes (P&O) algorithm to enhance the extraction of maximum power from photovoltaic (PV) panels in the presence of partial shading conditions. The conventional P&O algorithm falls short in extracting the maximum power from PV systems under partial shading conditions due to the existence of multiple maximum points. In such scenarios, optimization techniques can be employed to search for the global maximum point. The proposed MIWO-based P&O algorithm updates the reference voltage to ensure that the PV system operates at the Maximum Power Point (MPP) based on the prevailing weather conditions. This MIWO based PV system is further fed to water pumping system. A PV-based water pumping system is utilized for both irrigation and domestic purposes. Additionally, a sensorless vector control-based induction motor is employed in this study to drive the pump. The objective of this research is to demonstrate the achievement of an efficient PV-based water pumping system without the need for battery storage. Various results based on MIWO are compared with PSO and GWO. The results are presented based on various water pumping applications and the availability of solar irradiance during rapid climate changes. MATLAB/Simulink simulations, along with hardware-based experiments, are provided to validate the effectiveness of the proposed method under both transient and steady-state conditions.

Comparison of drying methods for biochemical composition, energy aspects, and color properties of alfalfa hay

AbstractAlfalfa is a crucial feed source for livestock, necessitating proper drying to achieve optimal moisture levels before consumption. This study aims to reveal alfalfa's drying characteristics and quality properties, defined as the queen of feed, by drying it under different drying conditions. Alfalfa samples were dried using different drying techniques: Open-sun, shade, greenhouse, hybrid (microwave-air-convective), air-convective, microwave, and freeze-drying. The influence of drying techniques on the drying kinetics, energy aspects, biochemical properties, mineral composition, fatty acids, carotene, and color attributes of alfalfa were investigated. Present findings revealed that shade and high-temperature drying conditions increased the crude fiber content (23.18%) of alfalfa samples. The highest protein values were found in open-sun drying (22.01%) and 60 °C air-convective drying (22.10%). The highest values for mineral composition were determined in freeze drying, and the greatest Zn (33.68 ppm) and Fe (135.45 ppm) contents were determined in 100 °C air-convective drying. The highest saturated fatty acids open-sun (21.27%) and freeze dryer (21.07%), unsaturated fatty acids at 60 °C (84.51%) and 80 °C (84.26%), poly unsaturated fatty acids at 60 °C (78.36%), 80 °C (78.14%) and 100 °C (77.74%) were obtained. The drying kinetics of alfalfa were best modeled with the Jena&Das, and in terms of a* (greenness) values, the hybrid drying yielded the best results. The lowest total energy consumption (54.00 kWh) was seen in 200W + 80 °C hybrid drying and the highest (324.72 kWh) in 100 °C air-convective drying. The color attributes and energy consumption findings showed that hybrid drying could efficiently be used for alfalfa drying. In addition, freeze drying was determined to be the best drying method in terms of nutrient preservation.

A novel algorithm MPPT controller based on the herd horse optimization for photovoltaic systems under partial shadow conditions

In recent years, a significant scientific issue has been the creation of maximum power point tracking (MPPT) methods to increase the energy production of PV plants. Moreover, to try to cope with the unparalleled operating conditions of PV plants, many bio-inspired meta-heuristic algorithms have already been suggested in the literature, but their implementation is often complex and difficult. In this sense, we propose a novel algorithm for monitoring the (MPPT), using the newly meta-heuristic approach of herd horse optimization (HHO). A DC/DC boost converter is utilised in the suggested controllers to extract the most power possible from the PV resource. The system is programmed and modelled using the MATLAB/SIMULINK software, which also studies four shadow models and a 3S1P topography of single-junction solar arrays. Considering partial shading conditions (PSC), the success of the power values in the global maximum power point (GMPP) of the proposed method is between 99.64% and 99.07%. Besides the time to capture the GMPP by the proposed algorithm is between 0.396 s and 1.666 s, shorter than that of the CSA and FPA algorithms. Comparison with the CSA and FPA optimizers confirmed the quality of the MPPT-based HHO algorithm for GMPP extraction in different (PSC).

Improved Sliding Mode Control for Tracking Global Maximum Power of Triple Series Parallel Ladder Photovoltaic Array under Uneven Shadowing

Abstract This paper presents an innovative way for enhancing the performance of photovoltaic arrays under uneven shadowing conditions. The study focuses on a triple series parallel ladder configuration to exploit the benefits of increased power generation while addressing the challenges associated with uneven shadowing. The proposed methodology focuses on the implementation of improved sliding mode Control technique for the global maximum power point tracking efficiently. Sliding mode control is known for its robustness in the presence of uncertainties and disturbances, making it suitable for dynamic and complex systems such as photovoltaic arrays. This work employs a comprehensive simulation framework to comment the performance of the suggested improved sliding mode control strategy at uneven shadowing scenarios. Comparative analysis has been done to show the effectiveness of the suggested method than the traditional control strategies. The results demonstrate a remarkable enhancement in the tracking accuracy of the global maximum power point, leading to enhanced energy harvesting capabilities under challenging environmental conditions. Furthermore, the proposed approach exhibits robustness and adaptability in mitigating the effect of shading on the photovoltaic array, thereby increasing overall system efficiency. This research contributes valuable insights into the development of advanced control strategies for photovoltaic arrays, particularly in the context of triple series parallel ladder configurations operating under uneven shadowing conditions. Under short narrow shading condition, the improved sliding mode control method tracking the maximum power more compared to perturb & observe is 20.68%, incremental conductance is 68.78%, fuzzy incremental conductance is 19.8%, and constant velocity sliding mode control is 1.25%. The improved sliding mode control method has 60% less chattering than constant velocity sliding mode control under shading conditions.

Solar energy harvesting under partial shading conditions through a reconfiguration strategy using a multi-port DC–DC converter

Solar energy harvesting under partial shading conditions through a reconfiguration strategy using a multi-port DC–DC converter

Evaluating electrical power yield of photovoltaic solar cells with k-Nearest neighbors: A machine learning statistical analysis approach

The increasing demand for sustainable and renewable energy solutions reflects the critical importance of advancing photovoltaic (PV) technology and its operational efficiency. In response, this study introduces a novel application of the k-Nearest Neighbor (k-NN) algorithm to assess the reliability and applicability of solar panel simulation data which aimed to classify current states of partial shading, open, and short circuit conditions, alongside regression-based analysis for predicting specific operating parameters. In this research, a published dataset that involved various PV module configurations under different environmental conditions was tested and evaluated. The k-NN technique was applied to both classify the operational status and predict performance metrics of the modules. The diagnosis model demonstrated an accuracy of 99.2 % and an F1 score of 99.2 %, indicating a high degree of reliability in identifying the operational states of PV modules. Concurrently, the regression model exhibited a Root Mean Square Error (RMSE) of 0.036 and an R2 value of unity that showcased its effectiveness in predicting the operational parameters based on the simulation data. The concluded results are further enriching the effectiveness of simulation-based data generation to be endorsed and implemented before jumping into real experimental applications, in addition to highlighting the potential applicability of k-NN and machine learning for PV cells productivity statistical analysis.

Quantum maximum power point tracking (QMPPT) for optimal solar energy extraction

Solar energy is key to achieving a more environmentally responsible future. One way to exploit it is to use semiconductor technology through solar panels to generate clean, sustainable, and controllable energy. However, the use of such solutions must be optimised by methods such as maximum power point tracking (MPPT) to extract the maximum available solar energy. Although MPPT algorithms have been widely used and improved, the use of newer approaches, such as quantum computing, appears to hold the promise of achieving new performance levels, particularly for real-time MPPT implementation. The goal of this work is to develop and test a quantum algorithm for the photovoltaic (PV) energy MPPT problem using quantum particle swarm optimisation. The performance of the classic and quantum MPPT algorithms was evaluated under three main operating conditions: normal, high-temperature, and partial shading conditions. This represents a variety of environmental scenarios that can affect the efficiency of solar power generation. According to the study's results, the classical algorithm recorded 0.15% more power than the quantum algorithm in normal operating conditions, and the quantum algorithm generated 3.33% more power in higher temperature tests and 0.89% more power in the partial shading test. Moreover, the quantum algorithm recorded lower duty cycles for the three tests. While the classical algorithm may have a slight edge in power output under normal operation conditions, the quantum algorithm indicates superior performance in challenging conditions and consistently reveals more promising overall efficiency.

Performance Analysis of Interconnection and Differential Power Processing Techniques under Partial Shading Conditions

Partial shading conditions can cause low output power, hotspots, and a reduced lifespan in photovoltaic arrays. Interconnection (IC) and differential power processing (DPP) can be used to mitigate these effects. When individually applied to an array, these techniques can significantly increase the generated power. A few authors studied the combined use of these schemes under specific conditions such as large-scale arrays or a complex combination of several techniques, making it difficult to identify the individual contribution of each technique. Here, we aimed to determine whether the combined use of a switching-inductor DPP circuit and a total-cross-tied interconnection scheme presents better performance than each standalone technique, using a small-scale photovoltaic array. An array was tested using IC, DPP, and a combination of both techniques, and the array was subjected to 13 shading patterns and two irradiance levels. The performance in each case was assessed using maximum output power, performance ratio, mismatch power loss, and power enhancement indicators. The results showed that a standalone differential power processing circuit presents better performance than when it is combined with an interconnection. The DPP showed performance ratio values of up to 97%, mismatch power losses lower than 36.9%, and a power enhancement of up to 95.9%. The standalone interconnection shows the worst performance among the three techniques.

Transient shading in agrivoltaic greenhouses: its impact on growth, architecture, and dry matter accumulation and partition in tomato plants

ABSTRACT Installing mobile photovoltaic panels could be used to protect crops, providing both shade and renewable energy. For two years (June to October 2021 and April to August 2022), we studied the effects of alternating periods of full sun and shade on tomatoes by shading the plants at different times of the day (30% less incident radiation than the control). Under shading conditions, the air temperature was slightly reduced without significantly affecting plant phenology. Temporary shading increased stem length, leaf area, and specific leaf area, indicating shade-avoidance syndrome, similar to responses under constant shading. Fruits of shaded plants accumulated less dry mass in 2022, which could be linked to a carbon limitation during the spring of 2022. We discuss the possibility of modulating shading using mobile agrivoltaic systems to optimise the climatic conditions throughout the season for optimal plant and fruit growth.

RECONFIGURATION OF SOLAR PANELS TO PRODUCE MAXIMUM POWER USING NOVEL METHOD (TOUR PUZZLE)

This paper introduces a new reconfiguration technique called tour puzzle for better shadow dispersion and obtaining maximum output power under partial shade conditions. In the presented method, partial shadows are spread in all rows and maximum power can be achieved. The puzzle tour can be applied to all kinds of PV arrays of different dimensions and sizes. Accordingly, the puzzle tour procedure is applied in several cases in the form of squares and rectangles with different dimensions and various shading conditions in each case. To directly compare and present the efficiency of the proposed method, the total cross-connection model and conventional methods such as magic Square puzzle, competence Square puzzle, Skyscraper and improved Sudoku are also implemented in the introduced cases. Finally, the evaluations emphasize the capability and efficiency of the Tour puzzle solution compared to other methods by achieving GMPP values such as 63.9 VmIm, 69.3 VmIm, 69.3 VmIm and 68.4 VmIm for cases 1 to 4, respectively. The results show that the proposed method can provide acceptable performance for solving the problem of achieving maximum power under PSC in PV.