ASHS 2024 Conference

As entrepreneurs look to find new ways to shorten the gap between farm and table in urban communities, many are considering vertical farming as an answer to the problem of limited growing space. The aim of this experiment is to determine the optimal harvest time in weeks for vertically grown, hydroponic kale (Brassica oleracea var. acephala cv. ‘Toscano’) based on morphological data, phytonutrient concentrations, energy, and yield. After a four-week germination period, kale was grown for up to eight weeks and harvested at eight different stages of growth, based on the number of weeks spent in the vertical system. When harvested, morphological parameters were measured, and samples were collected to analyze mineral nutrient content. Electrical Energy usage data was collected and presented as: Lighting, HVAC, and Other. Data was analyzed as a Randomized Complete Block Design with three blocks. Mean plant height, fresh leaf mass, and leaf dry mass all increased with growth stage, with the largest plants being observed at stage eight. Additionally, the greatest mean quantity of dead, diseased, or unconsumable leaves of 3.27 leaves per plant was observed at stage eight. Mineral nutrient concentrations of calcium, sulfur, and manganese increased through seven weeks (stage seven), after which a decrease was observed in stage eight. Decreases in concentration during stage eight was also observed for phosphorus, potassium, and magnesium, with negligible differences in the younger stages. No differences in energy data existed for the daily mean lighting, HVAC, and Other electrical consumption across all eight stages. Harvest data collected indicates that plants should be harvested prior to stage eight to maintain mineral nutrient content and minimize dead leaves and should be considered with total energy consumption to optimize farm productivity, energy efficiency, and nutritional content of plants. Further analysis of other primary and secondary metabolites alongside total energy consumption cost is necessary to identify the best stage of harvest maturity and nutritional quality for consumers relative to energy usage and production cost.

Controlled environment agriculture will play an important role in feeding the increasing world population as urbanization is expanding, and arable land is decreasing. Higher yields will help offset the initial high cost for building hydroponic production facilities. Beneficial bacterial endophytes have been receiving more attention in sustainable agriculture practices because they can promote plant growth, enhance nutrient uptake, and inhibit pathogen growth. The Institute for Advanced Learning and Research has established a bacterial endophyte library of more than 2000 strains and found that some bacterial endophytes significantly increased the growth of tall fescue KY31 in vitro, up to 8-fold compared with untreated control plants. In previous paper, we reported that Pseudomonas psychrotolerans IALR632 significantly promote lettuce growth in hydroponic systems. In this study, we investigated the molecular and microbiological mechanisms these bacteria exhibit for plant growth promotion in hydroponic systems through plant gene expression with RNAseq and root bacterial community changes through microbiome analysis after bacterial inoculation. Lettuce (Lactuca sativa) cultivar ‘Green Oakleaf’ was inoculated with Pseudomonas psychrotolerans IALR632 one week after seeds were sown and transplanted to nutrient film technique (NFT) hydroponic units one week after bacterial inoculation. Samples were taken at 4, 10, and 15 days after lettuce seedlings were transplanted for gene expression analysis. Root samples were taken 15 days after transplantation for microbiome analysis. Anosim, NMDS, and PCoA analyses indicated bacterial community changes in inoculated plants. The top genus relative abundance was unclassified bacteria with 87% in IALR632 treatment and 85% in control (p=0.0136). In the next top 24 genus’s relative abundance, IALR632 inoculation dramatically increased Sediminibacterium, Hyphomicrobium, Sphingobium, Devosia, Mycobacterium, Rhodoplanes, and Runella by 68%, 114%, 72%, 158%, 513%, 103% and 1920%, respectively, and reduced Methylotenera, Rhizobium, and Sphingomonas by 68%, 62% and 45%, respectively. RNAseq data showed that there were 135, 2059, and 9319 DEG between the control and bacterial treatment at 4, 10, and 15 days, respectively. These DEG are being analyzed for pathways involved in plant growth promotion.

Speed breeding is a cutting-edge technology, that utilizes controlled environments to significantly reduce plant generation time, thereby accelerating breeding and research programs. The manipulation of temperature, irrigation, phytohormones, and light are the main ways to reduce plant cycles in speed breeding programs. However, changing these factors can result in decreased yield efficiency, which can also affect the quality of a speed-breeding program. This study aimed to increase seed production without increasing harvest time in soybean plants, a short-day plant, by using different photoperiod regimes. Two soybean (Glycine max) varieties, S16-14801C and CZ7570LL, were grown from seeds in 11-L pots containing peat moss-based substrate in growth chambers with controlled temperature (27 ± 0.5 ˚C), CO2 (475 ± 15 µmol mol-1), humidity (70 ± 5.0%), and light (300 ± 5 µmol m-2 s-1 at table; 20% blue, 10% green, 70% red). One week after germination, seedlings were exposed to four different photoperiod regimes: i) 10 h (0 w at 18 h); ii) two weeks at 18 h and then 10 h (2 w at 18 h); iii) four weeks at 18 h and then 10 h (4 w at 18 h) and iv) six weeks at 18 h and then 10 h (6 w at 18 h). The light fixtures were not adjusted over plant height following industry practices. The plants were harvested ten days after 95% of the pods had attained maturity (R8 stage). For both varieties, the number of pods and seeds and seed weight per plant increased linearly, with the increase in the number of weeks at 18 h. Thus, the number of pods, seeds, and seed weight of plants at 6 w at 18 h were at least 5-fold higher than in plants at 0 w at 18 h. Similarly, plants grown at 6 w at 18 h presented 4-fold higher biomass than plants grown at 0 w at 18 h. However, the increased seed yield and biomass accumulation did not result in a longer plant cycle; plants of both varieties at 6 w at 18 h were harvested 32 days before plants at 0 w at 18 h. Here, we demonstrated that seed yield can be increased and harvest time decreased by manipulating the photoperiod. These findings can help plant breeders in identifying the most suitable method for growing soybean plants in a shorter period, while also ensuring high seed production.

Controlled environment agriculture (CEA) is considered one of the most efficient ways of crop production. CEAs have the ability to control environmental conditions to maximize crop production. Indoor farms are considered one of the CEA systems that precisely control the environment, leading to high energy consumption in lighting, heating, cooling, and humidity control requirements. Enhancing the energy use efficiency (EUE) of indoor farms requires a better understanding of the energy characteristics of the system and crop production is needed. In this study, a steady state energy model and a machine learning based crop growth model were developed to evaluate energy-saving strategies for indoor lettuce production. The strategies included shifting photoperiod, utilizing heat tolerant crops, and adjusting air temperature settings at four different locations (Phoenix, AZ, Los Angeles, CA, Jacksonville, FL, and Boston, MA). The results showed that cultivar selection plays an important role in EUE improvement. Using high temperature settings with heat tolerant cultivars can increase the EUE of the system. However, increasing temperature setting alone does not significantly reduce energy consumption because of the increasing amount of energy needed for dehumidification. The geographical location of the indoor farm also affects energy consumption because of the different outdoor climate conditions. Boston, MA, which has the coldest outdoor air temperature, had the lowest energy consumption overall compared to the other three locations. Lastly, changing the photoperiod schedule from daytime to nighttime can reduce the electricity costs dramatically by avoiding the peak rate of electricity despite not having a significant reduction in energy consumption.

As global population and stress on our natural resources increases, we need to rethink how/where we produce food with emphasis on recycling resources such as carbon, water, and nutrients. Controlled environment agriculture (CEA) is gaining increasing attention due to its potential for improving resource use efficiency compared to traditional field-based agriculture. This project investigated a novel approach for treating hydroponics irrigation water and recovering nutrients from vegetable waste for reuse in CEA systems. An integrated anaerobic/aerobic biological treatment process was investigated. Anaerobic digester effluent was nitrified via an aerobic membrane bioreactor process to produce a liquid organic fertilizer supplement (nADE). The nADE was evaluated as a nutrient source for indoor hydroponic and greenhouse soilless drip-irrigation lettuce cultivation. Lettuce yield, tissue nutrient content, water quality, and nutrient uptake efficiency were compared between the nADE treatment and a commercial fertilizer control for each CEA system. The lettuce grown on nADE demonstrated similar or higher yields, more leaves, and elevated tissue nutrient content than the control. The nADE media improved N and P uptake efficiency in the drip-irrigation system but decreased K, Ca, and Mg uptake efficiency, possibly from the over-application of these nutrients. Further research is needed to optimize the integrated treatment system as well as nADE dosing. The study demonstrates a circular bioeconomy approach to decrease dependency on inorganic fertilizers while benefiting crop yield and quality.

In controlled environment agriculture (CEA), maintaining effective plant spacing throughout the crop growth cycle is crucial for efficient resource (light, water, space, and nutrients) utilization to achieve optimal crop yield and quality. Overcrowded or overlapping plant leaves could cause inefficient light exposure to plants/parts of plants, negatively affecting their growth. Additionally, reduced airflow makes overcrowded plants prone to diseases and foliage damage. Meanwhile, sparse plant spacing could result in inefficient space and light utilization. Traditional plant spacing adjustment relies on expert knowledge and manual labor, which is time-consuming, labor-intensive, and costly. Computer vision-based automatic plant space adjustment could help with data-driven decision-making and reduce labor dependency. This study aims to develop a deep learning-based computer vision approach to estimate the effective plant spacing by extracting the morphological characteristics of plants and NFT (nutrient film technique) channels during different plant growth stages. A total of 576 lettuce plants were grown in an NFT channel-based hydroponics system in a controlled environment. Then, RGB-D information of these plants and NFT channels was collected each day for three weeks from planting to harvesting. Then, CNN (convolutional neural network) was employed to extract the plant and NFT channel feature information. Then, the spatial pyramid pooling approach was used to encode and decode the contextual information and segment the plants and NFT channels. This approach helped to achieve an F1-score of 0.90 on the test dataset to estimate space between plants and NFT channels. These results show the potential of the proposed approach for automated plant space adjustment for efficient resource utilization.

Current mist irrigation practices in plant propagation do not represent the variable rate of water loss experienced in a greenhouse environment and often rely on grower experience for adjusting irrigation settings. Automated control logic for these systems can be improved by considering climate data to predict the real-time water loss in the propagation environment. The objectives of this study were to 1) identify the impacts of environmental parameters on the water loss of young plants in greenhouses and indoor environments and 2) develop an evapotranspiration model based on the key parameters identified to achieve weather-based mist irrigation control for resource-efficient plant propagation in controlled environment agriculture. Data sets that include climate data, water applied, and water loss were collected in greenhouse sunlight and indoor sole-source LED environments with unrooted chrysanthemum cuttings. Trials were completed in June and September in 2023 and February in 2024 to collect diverse minute-by-minute data in each environment. Measurements using load cells indicated highly variable water loss in the greenhouse environment. Conversely, in the indoor environment with lower and constant photosynthetic photon flux density (PPFD) and reduced vapor pressure deficit via a fog system, rate of water loss was lower and consistent over time. The key parameters for modeling water loss, found using stepwise regression, were PPFD, leaf temperature, and air vapor pressure (temperature and relative humidity). These climate parameters were correlated with water loss data over time to yield a simple evapotranspiration equation that could be programmed into commercial environmental control systems to improve current irrigation scheduling programs. By improving the control of mist irrigation to take climate data into account, growers have the potential to reduce crop losses (“shrinkage”), reduce rooting time, and improve water use efficiency.

In South Korea, where many fruit vegetable crops are grown in greenhouses, the practice of continuous cropping in the same soil environments often leads to significant issues To mitigate these problems, there has been a shift from soil-based to hydroponic cultivation. While hydroponics is recommended as a sustainable agricultural practice, non-recirculating systems can lead to environmental contamination as the nutrient-rich drainage is discharged outside, affecting soil and water quality. However, recirculating hydroponics, which reuses the drained nutrient solution, conserves water and fertilizer, thereby promoting sustainable and eco-friendly agriculture. As plants grow, their nutrient requirements change with each growth stage. Reusing the drainage without adjusting its nutrient content can lead to imbalances. Periodic nutrient correction is crucial in recirculating hydroponic systems. This study was conducted to find the optimal nutrient correction intervals for growing melons hydroponically in a recirculating system, analyzing the effects of different correction intervals (every 2 weeks, every 4 weeks, and no correction) on nutrient imbalances and their impact on melon growth and fruit development. In the case of melons, post-fruit set, as plants shift from vegetative to reproductive growth, changes in nutrient uptake lead to imbalances. In this experiment, the nutrient composition between treatments corrected periodically did not differ significantly, but was markedly different from the uncorrected treatments. In uncorrected systems, the continual reuse of the drainage altered the balance of anions and cations, with anions increasing by approximately 4% and cations decreasing by the same margin, disrupting the nutrient balance and causing pH fluctuations. Specifically, there was a 10-12% difference in the ratios of cations such as K+ and Ca2+, and a 7% difference in anions like NO3-. Despite these nutritional variances, statistical analysis revealed no significant differences in the growth and fruit characteristics among the treatments.