Photovoltaic Agriculture Research Articles

Physiological, Photosynthetic, and Transcriptomics Insights into the Influence of Shading on Leafy Sweet Potato.

Leafy sweet potato is a new type of sweet potato, whose leaves and stems are used as green vegetables. However, sweet potato tips can be affected by pre-harvest factors, especially the intensity of light. At present, intercropping, greenhouse planting, and photovoltaic agriculture have become common planting modes for sweet potato. Likewise, they can also cause insufficient light conditions or even low light stress. This research aimed to evaluate the influence of four different shading levels (no shading, 30%, 50%, and 70% shading degree) on the growth profile of sweet potato leaves. The net photosynthetic rate, chlorophyll pigments, carbohydrates, and polyphenol components were determined. Our findings displayed that shading reduced the content of the soluble sugar, starch, and sucrose of leaves, as well as the yield and Pn. The concentrations of Chl a, Chl b, and total Chl were increased and the Chl a/b ratio was decreased for the more efficient interception and absorption of light under shading conditions. In addition, 30% and 50% shading increased the total phenolic, total flavonoids, and chlorogenic acid. Transcriptome analysis indicated that genes related to the antioxidant, secondary metabolism of phenols and flavonoids, photosynthesis, and MAPK signaling pathway were altered in response to shading stresses. We concluded that 30% shading induced a high expression of antioxidant genes, while genes related to the secondary metabolism of phenols and flavonoids were upregulated by 50% shading. And the MAPK signaling pathway was modulated under 70% shading, and most stress-related genes were downregulated. Moreover, the genes involved in photosynthesis, such as chloroplast development, introns splicing, and Chlorophyll synthesis, were upregulated as shading levels increased. This research provides a new theoretical basis for understanding the tolerance and adaptation mechanism of leafy sweet potato in low light environments.

Sustainable and Intelligent Phytoprotection in Photovoltaic Agriculture: New Challenges and Opportunities

Photovoltaic Agriculture (PA) is a new management system combining industry with modern agriculture that can effectively reduce the competition for limited land resource usage between electric power production and agricultural production. However, PA has been facing the challenge of managing plant protection measures because it is difficult to monitor plants grown under the photovoltaic panels by remote sensing satellites and pesticide applications using drones. To overcome this challenge, Solar Insecticidal Lamps (SILs) can be used for phytoprotection in PA. However, to effectively use SILs in PA, it is important to identify a suitable field location to maintain strong wireless communication signals. In this paper, two testbeds were designed and a series of experiments in PA was performed. The results indicate that there is considerable interference exists around the confluence box. A higher interference seriously reduces the Packet Reception Rate (PRR) of the nearby node, which is an important constraint for deploying wireless sensors in PA. Finally, new challenges and future research opportunities are proposed.

Research on Niche Evaluation of Photovoltaic Agriculture in China.

To evaluate the ecological niche of China's photovoltaic agriculture, this paper firstly analyzed the composition of photovoltaic agriculture and constructed the ecosystem of photovoltaic agriculture. Then, we defined the concept of the ecological niche of photovoltaic agriculture, and based on this the preliminary niche evaluation index system was constructed. Further, redundant indicators in the preliminary index system were deleted based on the rough set theory, and the final niche evaluation index system was constructed. Finally, the ecological niche of photovoltaic agriculture was evaluated using the DANP method and cloud model. We found that the niche level of China's photovoltaic agriculture is between low and medium levels. Specifically, the level of resource niche is the highest, between medium and high levels; following is policy niche, near medium level; then is environmental niche, which is at a slightly lower medium level; the last three in turn are technology niche, social niche and economic niche. The technology should fully realize the synergistic effect of photovoltaic power generation and agricultural production, and the policy should play better environmental, social and economic functions on this basis to achieve a higher niche level of China's photovoltaic agriculture.

Research on Niche Improvement Path of Photovoltaic Agriculture in China.

To explore the niche improvement path of photovoltaic agriculture in China, a niche influencing factor system was constructed first. Then, this study innovatively combined the DEMATEL and analytic network process (DANP) method and the NK model, which can correct the defects of the traditional NK model. Based on the above method, the influence coefficients and index weight of each niche factor were calculated, and the niche fitness landscape of photovoltaic agriculture was constructed. Finally, according to the fitness landscape map of each combination state, the optimal configuration state of niche influencing factors of photovoltaic agriculture and the optimal niche improvement path of photovoltaic agriculture were explored. We found that the interaction between the six niche influencing factors determines the niche fitness of photovoltaic agriculture, and the changes in the niche fitness and the niche improvement of photovoltaic agriculture are coordinated. It was proposed that the optimal niche improvement path of photovoltaic agriculture in China is “technological innovation → policy formulation → resource allocation → economic improvement → social recognition → environmental protection”, and the research conclusions were further explained and discussed.

High‐Efficiency Semi‐Transparent Organic Solar Cells Using Pentacyclic Aromatic Lactam‐Containing Terpolymer Strategy for Eco‐Friendly Greenhouse Application

Semitransparent organic solar cells (ST‐OSCs) offer unique features such as spectral tunability and see‐through function, giving them great potential in photovoltaic (PV) agriculture. However, the combination of sufficient average visible transmittance (AVT) and high power conversion efficiency (PCE) with eco‐friendly device fabrication has always been a key issue. Herein, a simple but effective strategy by incorporating pentacyclic aromatic lactam acceptor unit (TPTI) in copolymer donors for toluene processed high‐efficiency ST‐OSCs is performed. The comparisons between D18‐ and DEH‐X‐based ST‐OSCs demonstrate the effect of TPTI inserting on the polymer main skeleton can not only lower the energy level, improve the processability in nonhalogen solvent, tune the ideal morphology for efficient charge dissociation, but also control a photon transport window suitable for plant absorption. Therefore, the resulting OSCs processed with toluene exhibit a PCE of 14.6% with an AVT of 22%, which represents one of the highest values for ST‐OSCs made from nonhalogenated solvents. What's more, it is found that plant growth under ST‐OSCs filtered light is comparable with that under natural light. Herein, a guide for developing high‐performance ST‐OSCs is provided and the prospect of ST‐OSCs for green manufacturing PV greenhouse application is demonstrated.

Research on Income evaluation of photovoltaic agricultural investment model based on fuzzy real option

With the proposal of emission peak and carbon neutrality, in view of the actual development of China's energy economy , photovoltaic agriculture becomes an important means to promote the economic development of poor and remote areas. Aiming at the investment modes of photovoltaic agriculture projects such as agricultural land leasing and farmers' participation in investment, this paper constructs a fuzzy real option investment model, and uses Monte Carlo simulation method to evaluate and analyze the income of both photovoltaic power generation project modes. The research shows that compared with the traditional real option income evaluation, the fuzzy real option model is more suitable for the investment evaluation of photovoltaic power generation project modes, and the project with farmers’ participation has higher returns. The income evaluation results show that the best time to benefit from the photovoltaic power generation project is in the next seven years or so, which provides reference for policy guidance and investment decision-making, and helps to promote the development of photovoltaic agriculture projects.

Nitric Oxide Crosstalk With Phytohormone Is Involved in Enhancing Photosynthesis of Tetrastigma hemsleyanum for Photovoltaic Adaptation.

Photovoltaic agriculture is a newly emerging ecological planting pattern. In view of the adverse effect on production, a better understanding of photovoltaic adaptation responses is essential for the development of the innovative agriculture mode in sustainable crop production. Here, we investigated the impact of photovoltaic condition on endogenous hormone composition and transcriptome profile of Tetrastigma hemsleyanum. A total of 16 differentially accumulated phytohormones and 12,615 differentially expressed genes (DEGs) were identified. Photovoltaic adaptation significantly decreased the contents of phytohormones especially salicylic acid (SA) and jasmonic acid (JA). DEGs were the most relevant to photosynthesis and mitogen-activated protein kinase (MAPK) signaling pathway especially the key genes encoding proteins involved in photosystem I (PS I) and photosystem II (PS II) reaction center. Nitric oxide (NO), JA, and SA treatment alone significantly enhanced the photosynthetic efficiency which was decreased by exposure to photovoltaic condition, but the combined treatment of “NO + SA” could weaken the enhancement effect by regulating the expression level of psaL, CHIL, petF1, psbQ, and psaE genes. Exogenous phytohormones and NO treatment mitigated the accumulation of reactive oxygen species (ROS) and potentiated antioxidant capacity, which would be weakened by the combined treatment of “NO + SA.” SA and JA significantly decreased endogenous NO burst triggered by photovoltaic adaptation. SA might be a potent scavenger of NO and counter the restoration effect of NO on growth and photosynthetic potential in T. hemsleyanum. The results could provide reference for the application of phytohormones/other signaling molecules in photovoltaic agriculture.

Sustainability Evaluation of Modern Photovoltaic Agriculture Based on Interval Type-2 Fuzzy AHP-TOPSIS and Least Squares Support Vector Machine Optimized by Fireworks Algorithm

Photovoltaics (PV) has been combined with many other industries, such as agriculture. But there are many problems for the sustainability of PV agriculture. Timely and accurate sustainability evaluation of modern photovoltaic agriculture is of great significance for accelerating the sustainable development of modern photovoltaic agriculture. In order to improve the timeliness and accuracy of evaluation, this paper proposes an evaluation model based on interval type-2 Fuzzy AHP-TOPSIS and least squares support vector machine optimized by fireworks algorithm. Firstly, the criteria system of modern photovoltaic agriculture sustainability is constructed from three dimensions including technology sustainability, economic sustainability and social sustainability. Then, analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) methods are improved by using interval type-2 fuzzy theory, and the traditional evaluation model based on interval type-2 Fuzzy AHP-TOPSIS is obtained, and the improved model is used for comprehensive evaluation. After that, the optimal parameters of least squares support vector machine (LSSVM) model are obtained by Fireworks algorithm (FWA) training, and the intelligent evaluation model for the sustainability of modern photovoltaic agriculture is constructed to realize fast and intelligent calculation. Finally, an empirical analysis is conducted to demonstrate the scientificity and accuracy of the proposed model. This study is conducive to the comprehensive evaluation of the sustainability of modern photovoltaic agriculture, and can provide decision-making support for more reasonable development model in the future of modern photovoltaic agriculture.

Design of multi-passband polymer multilayer film and its application in photovoltaic agriculture

To solve the issue of the contradiction between photovoltaic power generation and plant photosynthesis for sunlight demand, we propose a design method of multi-passband polymer multilayer optical structure. Using polycarbonate (PC) and polymethyl methacrylate (PMMA), two polymer materials with different refractive indices, the passband position and passband bandwidth are calculated and adjusted by the transmission matrix method and TFCalc software. A 450 nm, 660 nm, and 730 nm three-passband filter was realized by superimposing stacks of different band positions. The feasibility of the photovoltaic agriculture was confirmed by the power generation efficiency and the actual plant growth.

Key factors affecting the adoption willingness, behavior, and willingness-behavior consistency of farmers regarding photovoltaic agriculture in China

Agricultural fossil energy consumption increases carbon dioxide emissions and is a critical concern in China. Photovoltaic agriculture refers to combining agricultural activities and photovoltaic power generation without changing the agricultural land and affecting agricultural production. It is a new agricultural production approach and has been identified as an important measure to deal with environmental pollution and fossil energy consumption. The goal of this study was to analyze the key factors that influence the willingness, behavior, and willingness-behavior consistency of farmers to adopt photovoltaic agriculture. A survey with 643 participants was conducted in China. The bivariate probit model and the binary logistic regression were used to test nineteen influencing factors. The results showed that the proportion of farmers whose adoption willingness was consistent with the adoption behavior was 37.1%, whereas 62.9% of farmers exhibited inconsistency between adoption willingness and adoption behavior. Differences were observed in the key factors influencing the willingness, behavior, and willingness-behavior consistency of adopting photovoltaic agriculture. The usefulness perception and technical training had significant positive impacts on the adoption willingness, adoption behavior, and willingness-behavior consistency of the farmers, whereas the photovoltaic investment cost had a negative impact. The results of this study provide an understanding of the factors influencing the promotion and dissemination of photovoltaic agriculture, a basis for optimizing related policies, and references to facilitate the implementation of photovoltaic agriculture in rural areas in other countries.

Assessment of the Ecological Niche of Photovoltaic Agriculture in China

To evaluate the ecological niche of photovoltaic agriculture in China, an evaluation index system was constructed. Based on the presentation form of interval numbers, we used the interval entropy weight method and interval cloud model to measure the niche state value and niche role value of photovoltaic agriculture. In this way, we determined the development trend of the ecological niche of photovoltaic agriculture. The results show that Chinese photovoltaic agriculture is in a good state and plays a good, but weak, role. The ecological niche of China’s photovoltaic agriculture will undergo a four-stage evolution process: positioning, integration, leap, and symbiosis. China has completed the positioning stage and entered the integration stage. Hence, it is important to constantly improve the level of industrial integration technology and to form a new photovoltaic agriculture recycling economic ecosystem.

Research on Coupling Coordination Development for Photovoltaic Agriculture System in China

To explore the law of coupling coordination development of China’s photovoltaic (PV) agriculture system, this study measured the comprehensive development level of the agriculture and PV industries from 2007 to 2016 using China’s agricultural and photovoltaic industry statistics. Once this was achieved, the coupling coordination degree of the PV agricultural system was measured and a development mode of this system was determined. Finally, we explored the development trend of the coupled and coordinated evolution of the system. The main research results show that: (1) Although the development level of the agriculture and PV industries are both in an upward trend, the rising rate of development by the PV industry far exceeds the agriculture industry. (2) As agricultural and PV industries expand, they both show stock resource-led characteristics, but the incremental resources of the PV industry are gradually taking the lead. (3) The coupling coordination degree of the agriculture and PV industries fluctuates as it rises, but the coupling is low. It has not yet evolved to a higher level of coupling, and the speed of upgrading and evolution is slow. (4) In the next 10 years, the evolution speed of the two industries will be significantly improved, and the coupling between them will enter the coordination stage. PV agriculture will further develop in a sustainable direction.