Solar harvest: Enhancing carbon sequestration and energy efficiency in solar greenhouses with PVT and GSHP systems

The Yellow River Basin, which accommodates the second longest river in China – Yellow River, covers a total area of 795,000 km2 and plays an important role in the national agricultural production, economy, and culture. However, the Basin also faces enormous challenges related to sustainable water management in agriculture as driven by both drought and flood. In this special issue, we collected 64 articles across the Basin to improve our understanding of agricultural water management needs and demonstrate efficacies of management practices to improve the water management. The articles present exciting research on regional soil water storage and dynamics, soil moisture conservation in rain-fed agriculture, crop water demand, irrigation effects, water-nutrient coupling, water management and soil salinity, soil and nutrient losses, groundwater science and management. Findings of studies revealed: (1) the importance of mulching, drip and negative pressure irrigation, water and nutrient coupling (i.e., fertigation) in achieving both crop production and environmental protection objectives; (2) emerging research for better understanding of regional water resources and allocation of the water resources among different agricultural land uses and cropping systems, new approaches for conserving water and soil and mitigating soil salinity, system-level integrated rainfall and irrigation management, and improved knowledge on groundwater quantity and quality management; and (3) need of future research to understand processes and efficiencies of management practices in variable landscapes and cropping systems and variable and changing climates, and system-level linkages and analyses of water balance – soil water availability and conservation – water and soil losses – agricultural and environmental sustainability. 

Sustainable agricultural water management in the Yellow River Basin, China

The front roof of the solar greenhouse captures more solar radiation energy, the height of the rear wall exposed to direct sunlight is high and the last row of crop canopy receives direct sunlight throughout the day is the basis for the efficient use of solar thermal resources in solar greenhouses, however, previous studies generally focused on the optimization of individual structural parameters of greenhouses, never considering the greenhouse structure-crop cultivation correlation. Therefore, a model for optimal the design of the structural dimensions of the solar greenhouse based on the canopy height was established, comparing the calculated values with the actual structural dimensions of greenhouse and analyzing their structural stability in Abaqus software. The results showed that: The calculated values of the model and the actual construction parameters are in good agreement and meet the structural stability requirements; Taking the 12 m span of the solar greenhouse in Xi'an area as an example, the difference in solar radiation capture on the winter solstice for greenhouse front roofs of different structures under three canopy height conditions were small, 195.95, 194.76 and 192.44 MJ/m, respectively. Taking the 8 m span solar greenhouse in Harbin area as an example, when the canopy height is reduced from 2.0 m to 0.8 m, the corresponding total cost of solar greenhouse construction can be reduced by 5.24%, of which the wall and skeleton costs are reduced by 12.54% and 5.08%, respectively. This study can provide a reference for the optimization of structural dimensions of the solar greenhouse. • An optimal design model of solar greenhouse based on canopy height was established. • The rationality of the model was analyzed at the structural, economic and optical levels. • Apply the model to complete the design of structural parameters of solar greenhouse in northern China. 

Optimal design for solar greenhouses based on canopy height

The current study was undertaken to investigate the dynamic characteristics of the tomato crop, such as its plant height and leaf area index (LAI), based on the effective cumulative temperature. This was assessed under aerated drip irrigation (ADI) conditions and the application of a specific nitrogen (N) dose, and their relationship with the yield of the crop was formulated. The study was conducted in a greenhouse located in Zhengzhou, Henan province, China. The assessment conditions were the two irrigation methods, ADI and conventional drip irrigation (CK), and the three N application rates, i.e., 0, 140, and 210 kg ha–1. The logistic and Richards models were used to fit dynamic equations for plant height and LAI under the different treatments to quantify the characteristic parameters and understand their relationship with yield. The results revealed that the growth of the tomato plant fitted well with the logistic and Richards model at R2 > 0.98 (p < 0.01), regardless of the treatments. ADI and N application were found to significantly increase the maximum growth rate and average growth rate over the rapid growth period based on the tomato plant height and LAI. They were also noted to reduce the effective cumulative temperature at which plant height entered the rapid growth period (p < 0.05), thereby increasing the time spent in the nutritional growth phase. This is an essential precursor for the better development of subsequent reproductive organs. Tomato yields also confirm it: the highest yield of 85.87 t ha–1 was obtained with 210 kg N ha–1 for the ADI treatment, with an increase of 13.8%, 12.2%, and 39.6% compared to the CK−210 kg N ha–1, ADI−140 kg N ha–1, and ADI−0 kg N ha–1 treatments, respectively (p < 0.05). Grey correlation analysis showed that the characteristic parameters closely related to yield were all from the ADI and N application treatments. Furthermore, it was observed that the effective cumulative temperature and the maximum growth rate of the LAI at which the LAI entered the slow growth phase were the key growth characteristic parameters affecting tomato yield. This study provides a scientific basis for regulating the growth dynamics and yield of vegetables in greenhouse facilities under ADI and N application.

/pdf/relationship-between-the-dynamic-characteristics-of-tomato-194bhb7a.pdf

Relationship between the Dynamic Characteristics of Tomato Plant Height and Leaf Area Index with Yield, under Aerated Drip Irrigation and Nitrogen Application in Greenhouses

In a low-cost greenhouse, where there are few actuators to regulate the climate, increasing yield and preventing crop diseases are contradictory processes because pathogens and hosts stay in a similar ecological niche. Under given weather conditions, the environmental range for crop growth and disease control must be carefully balanced. The aim of this paper is to develop an accurate optimal control algorithm for disease ecological control and explore its contribution in the application of intelligent downy mildew prevention in a low-cost solar greenhouse. The proposed hierarchical optimization control strategy is compared with four common management methods in order to evaluate its impact on crop growth and disease prevention. The results show that the hierarchical optimization control strategy reaches the best balance between disease prevention, accumulated temperature promotion, and low temperature stress risk reduction without using an additional heating system. Moreover, an event-based PID controller is applied to the system considering the energy conservation aspect, which decreases the vents movements areas by 16%, while the control error is only increased by 1.9%. On the whole, this paper provides a solution for low-cost greenhouses about the joint use of greenhouse modelling, disease early warning and environment control, looking for promoting the green production in greenhouse environments by considerably reducing the disease occurrence and use of pesticides. 

A hierarchical optimization strategy in the intelligent ecological control of the greenhouse downy mildew

Simulating cucumber plant heights using optimized growth functions driven by water and accumulated temperature in a solar greenhouse

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Simulating cucumber plant heights using optimized growth functions driven by water and accumulated temperature in a solar greenhouse