Supplemental interlighting is commonly used in modern greenhouses to improve light deficiency, but the light spectrum affects fruit quality and color change. This study aimed to analyze the effect of ...interlighting with red, blue, and additional far-red light on the fruit qualities and carotenoid contents of red and yellow sweet peppers (
Capsicum annuum
L.). Three light treatments were applied: natural light (NL), NL with red + blue LED interlighting (71 μmol m
–2
s
–1
) (RB), and RB with far-red light (55 μmol m
–2
s
–1
) (RBFR). Ascorbic acid, free sugars, and individual carotenoid content were quantified with HPLC analysis. Fruits were sampled on 2020.11.14 (Group 1) and 2021.01.03 (Group 2) from the plants grown under average light intensities of 335.9 and 105.6 μmol m
–2
s
–1
, respectively. In the overall period, total yields in RB and RBFR were 22 and 33% higher than those in NL in red fruits and 2 and 21% higher in yellow fruits, respectively. In both colored fruits, ascorbic acid, total soluble sugar, and carotenoid content were higher in RB and RBFR than NL. In Group 1, ascorbic acid and total soluble sugar were significantly different between RB and RBFR only in red fruits. In Group 2, ascorbic acids in red and yellow fruits were 9 and 3% higher in RBFR than RB but total soluble sugars were 4 and 2% lower, respectively. Carotenoid contents in red and yellow fruits were 3.0- and 2.1-fold higher in RB and 2.0- and 1.4-fold higher in RBFR than those in NL, respectively. In this study, interlighting had a significant impact on fruit quality in Group 2, mainly due to the increase in the ratio of interlighting to total light by seasonal changes. In particular, red and yellow fruit yields were 9% and 19% higher in RBFR than RB, but carotenoid contents were 26 to 9% lower, respectively. This result exhibited that additional far-red lighting has a trade-off relationship between fruit yield and carotenoid content. Thus, it is necessary to provide an adequate light spectrum according to a specific cultivation purpose, such as improving yield or accumulating plastids in fruits.
•3D-scanned plant models with different structural accuracies were analyzed.•Light interception of the models with a low accuracy were overestimated.•3D-scanned reconstruction can contribute to ...accurate analysis of photosynthesis.
Plant structure is a significant factor for influencing the light interception and photosynthesis of plants. The light interception on the plant surface can be analyzed by three-dimensional (3D) plant model and optical simulation, but its accuracy is directly affected by the structural accuracy of the 3D model. This study aims to analyze and compare the effect of the accuracy of 3D structural models on light interception and photosynthesis. 3D-scanned plant models with different structural accuracies were constructed, and the light interception and photosynthetic rate were analyzed at single leaf and whole-plant scales. When using a low accuracy model that lacked the fine structural details of the plant, it was overestimated in light interception and photosynthetic rate compared to the 3D-scanned model that has high structural accuracy. At the single leaf scale, the light interception was higher in the low-accuracy model than that in the 3D-scanned model due to self-shadings from higher curvature in the leaf surface. At the whole-plant scale, the light interception and the subsequent photosynthetic rate in the low-accuracy model were 18% and 45 to 58% higher than those in the 3D-scanned model at light intensities of 700–2000 μmol m−2 s−1 at the upper canopy. The 3D-scanned plant model could accurately estimate the light interception and photosynthetic rate of the plants through optical simulation. The presented methodology can contribute to accurate analyses of plant light environment, plant physiological response, and plant growth modelling.
Crop fresh weight and leaf area are considered non-destructive growth factors due to their direct relation to vegetative growth and carbon assimilation. Several methods to measure these parameters ...have been introduced; however, measuring these parameters using the existing methods can be difficult. Therefore, a non-destructive measurement method with high versatility is essential. The objective of this study was to establish a non-destructive monitoring system for estimating the fresh weight and leaf area of trellised crops. The data were collected from a greenhouse with sweet peppers (Capsicum annuum var. annuum); the target growth factors were the crop fresh weight and leaf area. The crop fresh weight was estimated based on the total system weight and volumetric water content using a simple formula. The leaf area was estimated using top-view images of the crops and a convolutional neural network (ConvNet). The estimated crop fresh weight and leaf area exhibited average R2 values of 0.70 and 0.95, respectively. The simple calculation was able to avoid overfitting with fewer limitations compared with the previous study. ConvNet was able to analyze raw images and evaluate the leaf area without additional sensors and features. As the simple calculation and ConvNet could adequately estimate the target growth factors, the monitoring system can be used for data collection in practice owing to its versatility. Therefore, the proposed monitoring system can be widely applied for diverse data analyses.
In greenhouses, the higher plant density causes poor light environments inside the canopy due to the mutual shading of adjacent plants. Interlighting has been introduced as a countermeasure to ...compensate for the lack of light in the middle and bottom canopies. However, most studies have focused on growth and yield, not light use efficiency (LUE) or water use efficiency (WUE). The objective of this study was to evaluate the LUE and WUE of sweet pepper plants subjected to light-emitting diode (LED) interlighting in greenhouses. Two lighting treatments, natural light (control) and supplemental lighting with red and blue LEDs, were applied. Interlighting began 34 days after transplanting. The ratio of red and blue light to photosynthetic photon flux density (PPFD) was 8:2, and the total PPFD was adjusted to 71 μmol m
−2
s
−1
at a distance of 20 cm. The daily transpiration was measured by subtracting the drainage from the supplied nutrient solution and the weight change of the hydroponic systems. The photosynthetic rate was obtained by measuring light response curves at light intensities of 0, 50, 100, 200, 400, 600, 900, 1200, 1500, and 2000 μmol m
−2
s
−l
. The LUE was calculated based on the simulated light interception obtained by 3D-scanned plant models and ray-tracing simulation. WUE was calculated by dividing the measured dry weight by the accumulated water consumption. Under the interlighting, the LUE increased at the canopy level due to the improved vertical light distributions. The WUE for biomass and fruit yield were higher in the interlighting treatment than in the control. These results were due to the higher increase rates of plant dry weight and fruit yield than that of water consumption by interlighting. In this study, the improvement of LUE and WUE by interlighting could be quantified by optical simulation and a measurement of water consumption throughout the entire growth period.
Far-red light has been included in horticultural light sources due to its physiological activity related to phytochrome-mediated responses. Recent studies have shown that adding far-red light to red ...and blue inter-lighting LEDs improves the growth and production of greenhouse tomatoes. However, in long-term cultivation, the effects of inter-lighting with additional far-red light may vary according to the seasonal light environment. This study aims to investigate the effect of adding far-red light to red and blue inter-lighting on growth and yield of sweet pepper in winter and summer. Sweet pepper (
Capsicum annuum L
. cv. Kori) plants were grown in greenhouses for five months under average daily light integrals of 16.6 and 32.2 mol m
− 2
day
− 1
in winter and summer, respectively. The inter-lighting with adding 55 µmol m
− 2
s
− 1
of far-red light to 71 µmol m
− 2
s
− 1
of red and blue light (red:blue = 8:2). The shoot dry weight and fruit yields were 20% and 17% higher, respectively, with additional far-red in the winter, but no significant differences in growth, yield, or morphology were observed in the summer. In summer, stem length and leaf area of plants increased rapidly due to sufficient sun irradiance, resulting in a higher far-red fraction at the bottom canopy. Thus, the far-red fraction at the middle and bottom canopies would have been sufficient with sunlight alone. Moreover, additional far-red inter-lighting promotes a decrease in leaf photosynthetic capacity in the bottom canopies. Therefore, plant growth and morphology were not influenced by adding far-red to inter-lighting in the summer at our latitude. We concluded that the additional far-red could contribute to growth and yield of sweet peppers in insufficient light conditions, but this effect disappears in conditions with ample sunlight.
Crop models have been developed for wide research purposes and scales, but they have low compatibility due to the diversity of current modeling studies. Improving model adaptability can lead to model ...integration. Since deep neural networks have no conventional modeling parameters, diverse input and output combinations are possible depending on model training. Despite these advantages, no process-based crop model has been tested in full deep neural network complexes. The objective of this study was to develop a process-based deep learning model for hydroponic sweet peppers. Attention mechanism and multitask learning were selected to process distinct growth factors from the environment sequence. The algorithms were modified to be suitable for the regression task of growth simulation. Cultivations were conducted twice a year for 2 years in greenhouses. The developed crop model, DeepCrop, recorded the highest modeling efficiency (= 0.76) and the lowest normalized mean squared error (= 0.18) compared to accessible crop models in the evaluation with unseen data. The t-distributed stochastic neighbor embedding distribution and the attention weights supported that DeepCrop could be analyzed in terms of cognitive ability. With the high adaptability of DeepCrop, the developed model can replace the existing crop models as a versatile tool that would reveal entangled agricultural systems with analysis of complicated information.
The leaf area index (LAI), which represents crop growth characteristics, is used to calculate canopy photosynthetic rates, set irrigation standards, and predict crop growth. The LAI can be ...non-destructively and continuously estimated using the light-intensity ratio of the upper and lower crop canopy, but it is affected by solar altitude and external weather conditions. The objective of this study was to develop a method to estimate the LAI of bell peppers (
Capsicum annuum
L.) using the light-intensity ratio of the upper and lower crop canopy via solar altitude and weather conditions. Growth stages and weather conditions with solar altitude were set using 3D-scanned plant models and ray-tracing simulation, respectively. The light intensities at each location of the canopy for given conditions were calculated using ray-tracing simulation. The relationship between the light-intensity ratio and the LAI was analyzed using a long short-term memory (LSTM) algorithm, which is a type of artificial neural network. According to our results, the ratio varied depending on solar altitude and external weather conditions and exponentially decreased with increasing LAI. This LSTM algorithmic approach was able to quantitatively analyze this complex relationship; compared with a greenhouse experiment for validation, the algorithm was highly accurate (R
2
= 0.808). Accuracy further increased when solar altitude and weather conditions were added to the model. Therefore, we conclude that, using this method, the LAI can be accurately measured in a non-destructive and continuous manner.
Depolymerization of polycarbonate waste by glycolysis using ethylene glycol without catalyst was explored in order to get the monomer bisphenol A (BPA). The depolymerized products were identified by ...GC/MS and FTIR spectroscopy. The effects of operation variables such as reaction time, reaction temperature, ethylene glycol/polycarbonate (EG/PC) weight ratio, and the kinetics of glycolysis were studied. A maximum yield of BPA of 95.6% was achieved at a reaction temperature of 220 °C for 85 min with an EG/PC weight ratio 4. It was found that the depolymerization reaction has two different activation energies, indicating that the reaction occurs in series. A new model was proposed to explain the depolymerization reaction which consists of a series of reactions: random scission from high molecular weight PC to its solid oligomer, dissolution from the solid oligomer to liquid oligomer, and homogeneous degradation from the liquid oligomer to its monomer, BPA. The activation energies were found to be 98.9 kJ/mol for the random scission reaction, 32.7 kJ/mol for the dissolution, and 355.8 kJ/mol for the homogeneous reaction, respectively. The predicted values by the proposed model were shown in good agreement with the experimental ones.
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