Breeding new varieties for controlled environments

Thai Oakleaf Lettuce Phenocopies a Phytochrome B Mutant

Photomorphogenic development in seedlings may be diagnostic of future plant performance. In this report, we characterize the Thai Oakleaf lettuce genotype, as it exhibited abnormalities in photomorphogenic development that were the most conspicuous under red light, including defects in hypocotyl growth inhibition, decreased cotyledon expansion, and constitutive shade avoidance tendencies. These observations are consistent with defects in red light sensing through the phytochrome B (phyB) photoreceptor system. This genotype is sold commercially as a heat-tolerant variety, which aligns with the evidence that phyB acts as a thermosensor.

Effect of Light Quality on Seed Potato (Solanum tuberose L.) Tuberization When Aeroponically Grown in a Controlled Greenhouse

A plant factory equipped with artificial lights is a comparatively new concept when growing seed potatoes (Solanum tuberosum L.) for minituber production. The shortage of disease-free potato seed tubers is a key challenge to producing quality potatoes. Quality seed tuber production all year round in a controlled environment under an artificial light condition was the main purpose of this study. The present study was conducted in a plant factory to investigate the effects of distinct spectrum compositions of LEDs on potato tuberization when grown in an aeroponic system. The study was equipped with eight LED light combinations: L1 = red: blue: green (70 + 25 + 5), L2 = red: blue: green (70 + 20 + 10), L3 = red: blue: green (70 + 15 + 15), L4 = red: blue: green (70 + 10 + 20), L5 = red: blue: far-red (70 + 25 + 5), L6 = red: blue: far-red (70 + 20 + 10), L7 = red: blue: far-red (70 + 15 + 15), L8 = red: blue: far-red (70 + 10 + 20), and L9 = natural light with 300 µmol m-2 s-1 of irradiance, 16/8 h day/night, 65% relative humidity, while natural light was used as the control treatment. According to the findings, treatment L4 recorded a higher tuber number (31/plant), tuber size (>3 g); (9.26 ± 3.01), and GA3 content, along with better plant growth characteristics. Moreover, treatment L4 recorded a significantly increased trend in the stem diameter (11.08 ± 0.25), leaf number (25.32 ± 1.2), leaf width (19 ± 0.81), root length (49 ± 2.1), and stolon length (49.62 ± 2.05) compared to the control (L9). However, the L9 treatment showed the best performance in plant fresh weight (67.16 ± 4.06 g) and plant dry weight (4.46 ± 0.08 g). In addition, photosynthetic pigments (Chl a) (0.096 ± 0.00 mg g-1, 0.093 ± 0.00 mg g-1) were found to be the highest in the L1 and L2 treatments, respectively. However, Chl b and TCL recorded the best results in treatment L4. Finally, with consideration of the plant growth and tuber yield performance, treatment L4 was found to have the best spectral composition to grow quality seed potato tubers.

Deciphering transcriptomic signatures explaining the phenotypic plasticity of nonheading lettuce genotypes under artificial light conditions

Elucidating the mechanisms and pathways involved in genotype-environment (G×E) interactions and phenotypic plasticity is critical for improving plant growth. Controlled environment agricultural systems allow growers to modulate the environment for particular genotypes. In this study, we evaluated the effects of interactions among 14 genotypes and four artificial light environments on leaf lettuce phenotypes and dissected the underlying molecular mechanism via transcriptome-based modeling. Variations in morphological traits and phytochemical concentrations in response to artificial light treatments revealed significant G×E interactions. The appropriate genotype and artificial light combinations for maximizing phenotypic expression were determined on the basis of a joint regression analysis and the additive main effect and multiplicative interaction model for these G×E interactions. Transcriptome-based regression modeling explained approximately 50%-90% of the G×E variations. Further analyzes indicated Red Lettuce Leaves 4 (RLL4) regulates UV-B and blue light signaling through the effects of the HY5-MBW pathway on flavonoid biosynthesis and contributes to natural variations in the light-responsive plasticity of lettuce traits. Our study represents an important step toward elucidating the phenotypic variations due to G×E interactions in nonheading lettuce under artificial light conditions.

Emergent molecular traits of lettuce and tomato grown under wavelength-selective solar cells

The integration of semi-transparent organic solar cells (ST-OSCs) in greenhouses offers new agrivoltaic opportunities to meet the growing demands for sustainable food production. The tailored absorption/transmission spectra of ST-OSCs impacts the power generated as well as crop growth, development and responses to the biotic and abiotic environments. To characterize crop responses to ST-OSCs, we grew lettuce and tomato, traditional greenhouse crops, under three ST-OSC filters that create different light spectra. Lettuce yield and early tomato development are not negatively affected by the modified light environment. Our genomic analysis reveals that lettuce production exhibits beneficial traits involving nutrient content and nitrogen utilization while select ST-OSCs impact regulation of flowering initiation in tomato. These results suggest that ST-OSCs integrated into greenhouses are not only a promising technology for energy-neutral, sustainable and climate-change protected crop production, but can deliver benefits beyond energy considerations.

Physicochemical properties and transcriptional changes underlying the quality of 'Gala' apples (Malus × domestica Borkh.) under atmosphere manipulation in long-term storage

BACKGROUND

The year-round availability of apples (Malus × domestica Borkh.) depends on post-harvest technologies, which are essential for the retention of fruit sensory and chemical properties by delaying senescence. The effectiveness of strategies for preserving the quality of apples depends on complex interactions between the storage environment and endogenous biological factors. In the current work, we integrated instrumental, sensory, and transcriptional data to determine the role of conservation technologies cold storage, controlled atmosphere, and 1-methylcyclopropene-mediated ethylene blockage on the long-term conservation of apples.

RESULTS

The results demonstrated that inhibition of the consumer's perception of the apples' ethylene content is essential for long-term cold storage, and such quality conservation can be achieved by reducing oxygen pressure. Overall appreciation of apples after storage was determined mainly by their texture, with crispness and juiciness contributing favorably, and mealiness contributing negatively. Reduced oxygen pressure and inhibition of ethylene perception exerted distinct effects on the transcription of candidate genes associated with ripening in apple. Hexose and cell-wall carbohydrate metabolism genes exhibit distinct expression patterns under storage.

CONCLUSION

Inhibition of ethylene perception and reduction of relative oxygen pressure under cold storage both promote similar conservation of apple sensory traits under long-term cold storage. Texture was the main contributor to global appreciation of apples subjected to long-term storage. The conditions that were investigated were able to delay, but not fully prevent, senescence, as evidenced by physicochemical and gene expression analyses. The expression of gene-encoding enzymes involved in hexose metabolism was mainly developmentally regulated, whereas storage conditions exerted a stronger effect on the expression of genes associated with cell-wall metabolism. © 2022 Society of Chemical Industry.

Novel Materials for Urban Farming

Scarcity of natural resources, shifting demographics, climate change, and increasing waste are four major challenges in the quest to feed the exploding world population. These challenges serve as the impetus to harness novel technologies to improve agriculture, productivity, and sustainability. Urban farming has several advantages over conventional farming: higher productivity, improved sustainability, and the ability to provide fresh food all year round. Novel materials are key to accelerating the evolution of urban farming - with their ability to facilitate controlled release of nutrients and pesticides, improved seed health, substrates with better water retention capability, more efficient recycling of agricultural waste, and precise plant health monitoring. Materials science enables environmental sustainability and higher harvest yields in urban farms. Here, Singapore is used as an example of a land-scarce city where urban farming may be the solution for future food production. Potential research directions and challenges in urban farming are highlighted, and how material optimization and innovation drive the development of urban farming to meet national and global food demands is briefly discussed. This review serves as a guide for researchers and a reference for stakeholders of urban farms, policy makers, and other interested parties.

Evaluation of Compact Tomato Cultivars for Container Gardening Indoors and under Sunlight

Numerous compact tomato cultivars are available for home gardening. However, evaluations under different environmental conditions are limited. The aim of this study was to characterize the growth and productivity of 20 compact tomato cultivars grown indoors under environmental conditions that resembled a residential space (11 mol·m−2·d−1 of white light, constant 22 °C, and moderate relative humidity) or in a greenhouse with sunlight only. Plants in the greenhouse were generally larger and yielded more fruit than those grown indoors, likely due to the various differences in environmental conditions and corresponding effects of water and nutrient availability. Considering growth and yield variables, all cultivars evaluated in this study are recommended for outdoor gardening. However, ‘Little Bing’, ‘Sweet SturdyTM F1—Grace’, ‘Sweet SturdyTM F1—Jimmy’, ‘Sweet SturdyTM F1—Jo’, and ‘Tarzan F1′ are likely too large to be grown in most space-limited indoor environments. Furthermore, ‘Little Bing’, ‘Rosy Finch’, ‘Sweet ‘n’ Neat Yellow’, and ‘Yellow Canary’ were affected by intumescence when grown indoors, which could negatively affect gardening experiences until recommendations to mitigate this disorder become available. Results from this study provide baseline information for the use of compact tomato cultivars for container gardening indoors and under sunlight.

LED color gradient as a new screening tool for rapid phenotyping of plant responses to light quality

BACKGROUND

The increasing demand for local food production is fueling high interest in the development of controlled environment agriculture. In particular, LED technology brings energy-saving advantages together with the possibility of manipulating plant phenotypes through light quality control. However, optimizing light quality is required for each cultivated plant and specific purpose.

FINDINGS

This article shows that the combination of LED gradient set-ups with imaging-based non-destructive plant phenotyping constitutes an interesting new screening tool with the potential to improve speed, logistics, and information output. To validate this concept, an experiment was performed to evaluate the effects of a complete range of red:blue ratios on 7 plant species: Arabidopsis thaliana, Brachypodium distachyon, Euphorbia peplus, Ocimum basilicum, Oryza sativa, Solanum lycopersicum, and Setaria viridis. Plants were exposed during 30 days to the light gradient and showed significant, but species-dependent, responses in terms of dimension, shape, and color. A time-series analysis of phenotypic descriptors highlighted growth changes but also transient responses of plant shapes to the red:blue ratio.

CONCLUSION

This approach, which generated a large reusable dataset, can be adapted for addressing specific needs in crop production or fundamental questions in photobiology.

Morphological and Physiological Screening to Predict Lettuce Biomass Production in Controlled Environment Agriculture

Fast growth and rapid turnover is an important crop trait in controlled environment agriculture (CEA) due to its high cost. An ideal screening approach for fast-growing cultivars should detect desirable phenotypes non-invasively at an early growth stage, based on morphological and/or physiological traits. Hence, we established a rapid screening protocol based on a simple chlorophyll fluorescence imaging (CFI) technique to quantify the projected canopy size (PCS) of plants, combined with electron transport rate (ETR) measurements using a chlorophyll fluorometer. Eleven lettuce cultivars (Lactuca sativa), selected based on morphological differences, were grown in a greenhouse and imaged twice a week. Shoot dry weight (DW) of green cultivars at harvest 51 days after germination (DAG) was correlated with PCS at 13 DAG (R2 = 0.74), when the first true leaves had just appeared and the PCS was <8.5 cm2. However, early PCS of high anthocyanin (red) cultivars was not predictive of DW. Because light absorption by anthocyanins reduces the amount of photons available for photosynthesis, anthocyanins lower light use efficiency (LUE; DW/total incident light on canopy over the cropping cycle) and reduce growth. Additionally, the total incident light on the canopy throughout the cropping cycle explained 90% and 55% of variability in DW within green and red cultivars, respectively. Estimated leaf level ETR at a photosynthetic photon flux density (PPFD) of 200 or 1000 µmol m−2 s−1 were not correlated with DW in either green or red cultivars. In conclusion, early PCS quantification is a useful tool for the selection of fast-growing green lettuce phenotypes. However, this approach may not work in cultivars with high anthocyanin content because anthocyanins direct excitation energy away from photosynthesis and growth, weakening the correlation between incident light and growth.

Current status and future challenges in implementing and upscaling vertical farming systems

Vertical farming can produce food in a climate-resilient manner, potentially emitting zero pesticides and fertilizers, and with lower land and water use than conventional agriculture. Vertical farming systems (VFS) can meet daily consumer demands for nutritious fresh products, forming a part of resilient food systems-particularly in and around densely populated areas. VFS currently produce a limited range of crops including fruits, vegetables and herbs, but successful implementation of vertical farming as part of mainstream agriculture will require improvements in profitability, energy efficiency, public policy and consumer acceptance. Here we discuss VFS as multi-layer indoor crop cultivation systems, exploring state-of-the-art vertical farming and future challenges in the fields of plant growth, product quality, automation, robotics, system control and environmental sustainability and how research and development, socio-economic and policy-related institutions must work together to ensure successful upscaling of VFS to future food systems.

Selection of nitrogen responsive root architectural traits in spinach using machine learning and genetic correlations

The efficient acquisition and transport of nutrients by plants largely depend on the root architecture. Due to the absence of complex microbial network interactions and soil heterogeneity in a restricted soilless medium, the architecture of roots is a function of genetics defined by the soilless matrix and exogenously supplied nutrients such as nitrogen (N). The knowledge of root trait combinations that offer the optimal nitrogen use efficiency (NUE) is far from being conclusive. The objective of this study was to define the root trait(s) that best predicts and correlates with vegetative biomass under differed N treatments. We used eight image-derived root architectural traits of 202 diverse spinach lines grown in two N concentrations (high N, HN, and low N, LN) in randomized complete blocks design. Supervised random forest (RF) machine learning augmented by ranger hyperparameter grid search was used to predict the variable importance of the root traits. We also determined the broad-sense heritability (H) and genetic (r_g) and phenotypic (r_p) correlations between root traits and the vegetative biomass (shoot weight, SWt). Each root trait was assigned a predicted importance rank based on the trait’s contribution to the cumulative reduction in the mean square error (MSE) in the RF tree regression models for SWt. The root traits were further prioritized for potential selection based on the r_g and SWt correlated response (CR). The predicted importance of the eight root traits showed that the number of root tips (Tips) and root length (RLength) under HN and crossings (Xsings) and root average diameter (RAvdiam) under LN were the most relevant. SWt had a highly antagonistic r_g (− 0.83) to RAvdiam, but a high predicted indirect selection efficiency (− 112.8%) with RAvdiam under LN; RAvdiam showed no significant rg or rp to SWt under HN. In limited N availability, we suggest that selecting against larger RAvdiam as a secondary trait might improve biomass and, hence, NUE with no apparent yield penalty under HN.

Longer Photoperiods with the Same Daily Light Integral Increase Daily Electron Transport through Photosystem II in Lettuce

Controlled environment crop production recommendations often use the daily light integral (DLI) to quantify the light requirements of specific crops. Sole-source electric lighting, used in plant factories, and supplemental electric lighting, used in greenhouses, may be required to attain a specific DLI. Electric lighting is wasteful if not provided in a way that promotes efficient photochemistry. The quantum yield of photosystem II (ΦPSII), the fraction of absorbed light used for photochemistry, decreases with increasing photosynthetic photon flux density (PPFD). Thus, we hypothesized that the daily photochemical integral (DPI), the total electron transport through photosystem II (PSII) integrated over 24 h, would increase if the same DLI was provided at a lower PPFD over a longer photoperiod. To test this, ΦPSII and the electron transport rate (ETR) of lettuce (Lactuca sativa 'Green Towers') were measured in a growth chamber at DLIs of 15 and 20 mol m-2 d-1 over photoperiods ranging from 7 to 22 h. This resulted in PPFDs of 189 to 794 μmol m-2 s-1. The ΦPSII decreased from 0.67 to 0.28 and ETR increased from 55 to 99 μmol m-2 s-1 as PPFD increased from 189 to 794 μmol m-2 s-1. The DPI increased linearly as the photoperiod increased, but the magnitude of this response depended on DLI. With a 7-h photoperiod, the DPI was ≈2.7 mol m-2 d-1, regardless of DLI. However, with a 22-h photoperiod, the DPI was 4.54 mol m-2 d-1 with a DLI of 15 mol m-2 d-1 and 5.78 mol m-2 d-1 with a DLI of 20 mol m-2 d-1. Our hypothesis that DPI can be increased by providing the same DLI over longer photoperiods was confirmed.

Vertical Farming: Moving from Genetic to Environmental Modification

Vertical farming (VF) is a novel plant production system that allows local production of high-quality fruits and vegetables for rapidly growing cities. VF offers a myriad of opportunities to move from genetic to environmental modification and to produce crops of guaranteed quality and quantity independent of weather, soil conditions, or climate change.

Recognition and Localization Methods for Vision-Based Fruit Picking Robots: A Review

The utilization of machine vision and its associated algorithms improves the efficiency, functionality, intelligence, and remote interactivity of harvesting robots in complex agricultural environments. Machine vision and its associated emerging technology promise huge potential in advanced agricultural applications. However, machine vision and its precise positioning still have many technical difficulties, making it difficult for most harvesting robots to achieve true commercial applications. This article reports the application and research progress of harvesting robots and vision technology in fruit picking. The potential applications of vision and quantitative methods of localization, target recognition, 3D reconstruction, and fault tolerance of complex agricultural environment are focused, and fault-tolerant technology designed for utilization with machine vision and robotic systems are also explored. The two main methods used in fruit recognition and localization are reviewed, including digital image processing technology and deep learning-based algorithms. The future challenges brought about by recognition and localization success rates are identified: target recognition in the presence of illumination changes and occlusion environments; target tracking in dynamic interference-laden environments, 3D target reconstruction, and fault tolerance of the vision system for agricultural robots. In the end, several open research problems specific to recognition and localization applications for fruit harvesting robots are mentioned, and the latest development and future development trends of machine vision are described.

Using morphological attributes for the fast assessment of nutritional responses of Buddhist pine (Podocarpus macrophyllus [Thunb.] D. Don) seedlings to exponential fertilization

Culturing slowly growing tree seedlings is a potential approach for managing the conflict between the increasing demand for ornamental stock and the decreasing area of farmlands due to urbanization. In this study, Buddhist pine (Podocarpus macrophyllus [Thunb.] D. Don) seedlings were raised in multishelves with light-emitting diode lighting in the spectrum of 17:75:8 (red:green:blue) at 190–320 μmol m^-2 s^-1 with controlled temperature and relative humidity at 19.5°C and 60%, respectively. Seedlings were fed by exponential fertilization (EF) (nitrogen [N]-phosphorus [P]₂O₅-K₂O, 10-7-9) at eight rates of 0 (control), 20 (E20), 40 (E40), 60 (E60), 80 (E80), 100 (E100), 120 (E120), and 140 (E140) mg N seedling^-1 for four months through 16 fertilizer applications. The nutritional responses of Buddhist pine seedlings can be identified and classified into various stages in response to increasing doses, up to and over 120 N seedling^-1. Morphological traits, i.e., the green color index and leaf area (LA) obtained by digital analysis and the fine root growth, all remained constant in response to doses that induced steady nutrient loading. LA had a positive relationship with most of the nutritional parameters. A dose range between 60 and 120 mg N seedling^-1 was recommended for the culture of Buddhist pine seedlings. At this range of fertilizer doses, measuring the leaf area through digital scanning can easily and rapidly indicate the inherent nutrient status of the seedlings.