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Although Jung et al. (2014) measured the change in CO 2 concentration according to growth stage and ratio of romaine lettuces to king oyster mushrooms  , they did not precisely analyze the CO 2 ... Behavior Models for the Cultivation Systems The photosynthetic rates in the lettuce chambers (Equation (1)) were calculated using models of lettuce photosynthesis over time experimentally developed by Jung ...doi:10.3390/su13105434 fatcat:iy66tccngre5jm2tmoqgptxo64
Fresh weight is a direct index of crop growth. It is difficult to continuously measure the fresh weight of bell peppers grown in soilless cultures, however, due to the difficulty in identifying the moisture condition of crops and growing media. The objective of this study was to develop a continuous and nondestructive measuring system for the fresh weight of bell peppers grown in soilless cultures considering the moisture content of growing media. The system simultaneously measures the trellisdoi:10.3390/agronomy9100652 fatcat:u3g2le56e5drdmxxtbemdjnlmq
more »... tring's supported weight and gravitational weight using tensile load cells. The moisture weight of growing media was calibrated during the growth period using changes in moisture content before and after the first irrigation of the day. The most stable time period for the measurement, from 03:00 to 06:00, was determined by analyzing the diurnal change in relative water content. To verify the accuracy of the system, the fruits, stems, leaves, and roots' fresh weights were measured manually. The fresh weights measured by the developed system were in good agreement with those manually measured. The results confirm that our system can reliably and accurately measure fresh weights of bell peppers grown in soilless cultures. This method can be applied to continuous growth data collection for other crops grown in soilless cultures.
As smart farms are applied to agricultural fields, the use of big data is becoming important. In order to efficiently manage smart farms, relationships between crop growth and environmental conditions are required to be analyzed. From this perspective, various artificial intelligence algorithms can be used as useful tools to quantify this relationship. The objective of this study was to develop and validate an algorithm that can interpret the crop growth rate response to environmental factorsdoi:10.3390/horticulturae7090284 doaj:f336463f0dcd4061bfbb9217191a7cba fatcat:jwwhdf3nnvatzlh3h6qayriwei
more »... sed on a recurrent neural network (RNN), and to evaluate the algorithm accuracy compared to the process-based model (PBM). The algorithms were trained with data from three growth periods. The developed methods were used to measure the crop growth rate. The algorithm consisted of eight environmental variables days after transplanting and two crop growth characteristics as input variables producing weekly crop growth rates as output. The RNN-based crop growth rate estimation algorithm was validated using data collected from a commercial greenhouse. The CropGro-bell pepper model was applied to compare and evaluate the accuracy of the developed algorithm. The training accuracies varied from 0.75 to 0.81 in all growth periods. From the validation result, it was confirmed that the accuracy was reliable in the commercial greenhouse. The accuracy of the developed algorithm was higher than that of the PBM. The developed algorithm can contribute to crop growth estimation with a limited number of data.
Three treatments were unmodified spectra under which cucumber plants were grown with conventional light sources: HPS0 (HPS SON-T 400W, Philips, Eindhoven, The Netherlands), RB0 (660 nm R (R660) and 450 ... Three treatments were unmodified spectra under which cucumber plants were grown with conventional light sources: HPS 0 (HPS SON-T 400W, Philips, Eindhoven, The Netherlands), RB 0 (660 nm R (R660) and 450 ...doi:10.3390/plants9050556 pmid:32349252 pmcid:PMC7285096 fatcat:cpxpr2ueeveaxkjcs3d4gl6owi
Greenhouses require accurate and reliable data to interpret the microclimate and maximize resource use efficiency. However, greenhouse conditions are harsh for electrical sensors collecting environmental data. Convolutional neural networks (ConvNets) enable complex interpretation by multiplying the input data. The objective of this study was to impute missing tabular data collected from several greenhouses using a ConvNet architecture called U-Net. Various data-loss conditions with errors indoi:10.3390/s21062187 pmid:33804781 pmcid:PMC8003888 fatcat:zdxb6w3uafcphp6m2vuprfaov4
more »... ividual sensors and in all sensors were assumed. The U-Net with a screen size of 50 exhibited the highest coefficient of determination values and the lowest root-mean-square errors for all environmental factors used in this study. U-Net50 correctly learned the changing patterns of the greenhouse environment from the training dataset. Therefore, the U-Net architecture can be used for the imputation of tabular data in greenhouses if the model is correctly trained. Growers can secure data integrity with imputed data, which could increase crop productivity and quality in greenhouses.
Light is a major environmental factor affecting the regulation of secondary metabolites, such as pigments and flavor. The Solanaceae plant family has diverse patterns of fruit metabolisms that serve as suitable models to understand the molecular basis of its regulation across species. To investigate light-dependent regulation for fruit pigmentation and volatile flavors, major fruit pigments, their biosynthetic gene expression, and volatiles were analyzed in covered fruits of tomato and belldoi:10.3390/antiox9010014 pmid:31877964 pmcid:PMC7023227 fatcat:jhuf4npk7vhwngtyhaifitp7qi
more »... er. Immature covered fruits were found to be ivory in color and no chlorophyll was detected in both plants. The total carotenoid content was found to be reduced in ripe tomato and bell pepper under cover. Naringenin chalcone decreased more than 7-fold in ripe tomato and total flavonoids decreased about 10-fold in immature and ripe pepper fruit under light deficiency. Light positively impacts fruit pigmentation in tomato and bell pepper by regulating gene expression in carotenoid and flavonoid biosynthesis, especially phytoene synthase and chalcone synthase, respectively. Nineteen volatile flavors were detected, and seven of these exhibited light-dependent regulations for both ripe tomato and pepper. This study will help in improving fruit quality and aid future research works to understand the molecular mechanisms regulating the influence of light-dependency on pigments and flavor volatiles.
In plant factories, light is fully controllable for crop production but involves a cost. For efficient lighting, light use efficiency (LUE) should be considered as part of light environment design. The objectives of this study were to evaluate and interpret the light interception, photosynthetic rate, and LUE of lettuces under electrical lights using ray-tracing simulation. The crop architecture model was constructed by 3D scanning, and ray-tracing simulation was used to interpret lightdoi:10.3390/agronomy10101545 fatcat:2stguwbxqfhhzdhn22ipanparm
more »... tion and photosynthesis. For evaluation of simulation reliability, measured light intensities and photosynthetic rates in a growth chamber were compared with those obtained by simulation at different planting densities. Under several scenarios modeling various factors affecting light environments, changes in light interception and LUE were interpreted. The light intensities and photosynthetic rates obtained by simulation showed good agreement with the measured values, with R2 > 0.86. With decreasing planting density, the light interception of the central plant increased by approximately 18.7%, but that of neighboring plants decreased by approximately 5.5%. Under the various scenarios, shorter lighting distances induced more heterogenetic light distribution on plants and caused lower light interception. Under a homogenous light distribution, the light intensity was optimal at approximately 360 μmol m−2 s−1 with an LUE of 6.5 g MJ−1. The results of this study can provide conceptual insights into the design of light environments in plant factories.
Journal of Agricultural Meteorology
The alternative nutrient replenishment technique proposed by Ahn and Son  was used in the closed-loop soilless culture system (Equation (3)). ...doi:10.3390/horticulturae8040295 fatcat:3jqzf3b44vhfnfabydabcjgwku
., 2008; Shin and Son, 2016) . Consequently, changes in drainage characteristics influence the recycled nutrient solution (Savvas and Manos, 1999) . ... However, the recent literature theoretically deduced a modified nutrient replenishment method for steady-state management of EC and experimentally demonstrated its effect (Ahn and Son, 2019) . ...doi:10.3389/fpls.2021.656403 pmid:34108979 pmcid:PMC8181128 fatcat:jwbfz4qrr5gxxgcawjfv7qjv4q
Root-zone environment is considered difficult to analyze, particularly in interpreting interactions between environment and plant. Closed-loop soilless cultures have been introduced to prevent environmental pollution, but difficulties in managing nutrients can cause nutrient imbalances with an adverse effect on crop growth. Recently, deep learning has been used to draw meaningful results from nonlinear data and long short-term memory (LSTM) is showing state-of-the-art results in analyzingdoi:10.1186/s13007-019-0443-7 pmid:31160918 pmcid:PMC6540585 fatcat:5peomnhr6nd77d5kuzbxokfv2e
more »... eries data. Therefore the macronutrient ion concentrations affected by accumulated environment conditions can be analyzed using LSTM. The trained LSTM can estimate macronutrient ion concentrations in closed-loop soilless cultures using environmental and growth data. The average training accuracy of six macronutrients was R2 = 0.84 and the test accuracy was R2 = 0.67 with RMSE = 1.48 meq L-1. The used values of input interval and time step were 1 h and 168 (1 week), respectively. The accuracy was improved when the input interval became shorter, but not improved when the LSTM consisted of a multilayer structure. Regarding training methods, the LSTM improved the accuracy better than the non-LSTM. The trained LSTM showed relatively adequate accuracies and the interpolated ion concentrations showed variations similar to those seen during traditional cultivation. We could analyze the nutrient balance in the closed-loop soilless culture, the model showed potential in estimating the macronutrient ion concentrations using environmental and growth factors measured in greenhouses. Since the LSTM is a powerful and flexible tool used to interpret accumulative changes, it is easily applicable to various plant and cultivation conditions. In the future, this approach can be used to analyze interactions between plant physiology and root-zone environment.
<p>If a greenhouse in the temperate and subtropical regions is maintained in a closed condition, the indoor temperature commonly exceeds that required for optimal plant growth, even in the cold season. This study considered this excess energy as surplus thermal energy (STE), which can be recovered, stored and used when heating is necessary. To use the STE economically and effectively, the amount of STE must be estimated before designing a utilization system. Therefore, this study proposed andoi:10.5424/sjar/2016141-7517 fatcat:2y6hsnxdxba5ppz6sifstypi7i
more »... model using energy balance equations for the three steps of the STE generation process. The coefficients in the model were determined by the results of previous research and experiments using the test greenhouse. The proposed STE model produced monthly errors of 17.9%, 10.4% and 7.4% for December, January and February, respectively. Furthermore, the effects of the coefficients on the model accuracy were revealed by the estimation error assessment and linear regression analysis through fixing dynamic coefficients. A sensitivity analysis of the model coefficients indicated that the coefficients have to be determined carefully. This study also provides effective ways to increase the amount of STE.</p>
Chlorophyll fluorescence has been known as one of the indicators of photosynthetic status to various environmental stresses. The aims of this study were to assess the effects of environmental factors on lettuce chlorophyll fluorescent responses (Fv/Fm) and to develop an environment optimization model for lettuce growth using a simple genetic algorithm. High values of Fv/Fm were observed when environmental factors were 22-26ºC ambient temperature, 15-23ºC root zone temperature, 900-1,600 ppm COdoi:10.6090/jarq.40.149 fatcat:vr4qktng3bc7hkeorgyd5evzfi
more »... concentration, 0.4-1.3 m⋅s -1 air current speed, and 65-85% relative humidity. As photosynthesis photon flux (PPF) increased over 150 μmol⋅m -2 ⋅s -1 , Fv/Fm values were decreased. Principle component analysis was used to estimate the combined effects of six environmental factors on lettuce growth. The developed model fitted observed Fv/Fm values with an average standard error of 1.2%. An optimal environment for lettuce growth was estimated by the model to be 22ºC ambient temperature, 20ºC root zone temperature, 1,578 ppm CO 2 concentration, 1.3 m⋅s -1 air current speed, 216 μmol⋅m -2 ⋅s -1 PPF, and 75% relative humidity. The Fv/Fm value can be a good indicator of plant stress level and thus a useful parameter to optimize the environment for plant growth.
Copyright © 2021 Yoon, Kim, Kim and Son. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). ...doi:10.3389/fpls.2021.667456 fatcat:vqxn5cqajnfu7n7upvzlrx67ji
Copyright © 2016 Kim, Lee, Ahn, Shin, Park and Son. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). ...doi:10.3389/fpls.2016.01321 pmid:27667994 pmcid:PMC5016622 fatcat:crigj553incxxcitgn6s6koo74
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