Flavor-cyber-agriculture: Optimization of plant metabolites in an open-source control environment through surrogate modeling

Surrogate optimisation strategies for intraocular lens formula constant optimisation

PURPOSE

To investigate surrogate optimisation (SO) as a modern, purely data-driven, nonlinear adaptive iterative strategy for lens formula constant optimisation in intraocular lens power calculation.

METHODS

A SO algorithm was implemented for optimising the root mean squared formula prediction error (rmsPE, defined as predicted refraction minus achieved refraction) for the SRKT, Hoffer Q, Holladay, Haigis and Castrop formulae in a dataset of N = 888 cataractous eyes with implantation of the Hoya Vivinex hydrophobic acrylic aspheric lens. A Gaussian Process estimator was used as the model, and the SO was initialised with equidistant datapoints within box constraints, and the number of iterations restricted to either 200 (SRKT, Hoffer Q, Holladay) or 700 (Haigis, Castrop). The performance of the algorithm was compared to the classical gradient-based Levenberg-Marquardt algorithm.

RESULTS

The SO algorithm showed stable convergence after fewer than 50/150 iterations (SRKT, HofferQ, Holladay, Haigis, Castrop). The rmsPE was reduced systematically to 0.4407/0.4288/0.4265/0.3711/0.3449 dioptres. The final constants were A = 119.2709, pACD = 5.7359, SF = 1.9688, -a0 = 0.5914/a1 = 0.3570/a2 = 0.1970, C = 0.3171/H = 0.2053/R = 0.0947 for the SRKT, Hoffer Q, Holladay, Haigis and Castrop formula and matched the respective constants optimised in previous studies.

CONCLUSION

The SO proves to be a powerful adaptive nonlinear iteration algorithm for formula constant optimisation, even in formulae with one or more constants. It acts independently of a gradient and is in general able to search within a (box) constrained parameter space for the best solution, even where there are multiple local minima of the target function.

Preharvest and postharvest techniques that optimize the shelf life of fresh basil (Ocimum basilicum L.): a review

Basil (Ocimum basilicum L.) is a popular specialty crop known for its use as a culinary herb and medicinal plant around the world. However, its profitability and availability are limited by a short postharvest shelf life due to poor handling, cold sensitivity and microbial contamination. Here, we comprehensively review the research on pre- and postharvest techniques that extend the shelf life of basil to serve as a practical tool for growers, distributors, retailers and scientists. Modifications to postharvest storage conditions, pre- and postharvest treatments, harvest time and preharvest production methods have been found to directly impact the quality of basil and its shelf life. The most effective strategies for extending the shelf life and improving the quality of basil are discussed and promising strategies that research and industry employ are identified.

Infosphere, Datafication, and Decision-Making Processes in the AI Era

A recent interpretation of artificial intelligence (AI) (Floridi 2013, 2022) suggests that the implementation of AI demands the investigation of the binding conditions that make it possible to build and integrate artifacts into our lived world. Such artifacts can successfully interact with the world because our environment has been designed to be compatible with intelligent machines (such as robots). As the use of AI becomes ubiquitous in society, possibly leading to the formation of increasingly intelligent bio-technological unions, there will likely be a coexistence of a plethora of micro-environments wrapped and tailored around humans and basic robots. The key element of this pervasive process will be the capacity to integrate biological realms in an infosphere suitable for the implementation of AI technologies. This process will require extensive datafication. This is because data is the basis of the logical-mathematical codes and models that drive and guide AI. This process will have huge consequences on workplaces, on workers, as well as on the decision-making processes required for the functioning of future societies. In this paper we will offer a comprehensive reflection on the moral and social implications of datafication as well as a set of considerations about its desirability, which will be informed by the following insights: (1) full protection of privacy may become structurally impossible, thus leading to undesirable forms of political and social control; (2) worker's freedom may be reduced; (3) human creativity, imagination, and even divergence from AI logic might be channeled and possibly discouraged; (4) there will likely be a push towards efficiency and instrumental reason, which will become preeminent in production lines as well as in society.

Effects of White and Blue-Red Light on Growth and Metabolism of Basil Grown under Microcosm Conditions

Indoor farming of basil (Ocimum basilicum L.) under artificial lighting to support year-round produce demand is an area of increasing interest. Literature data indicate that diverse light regimes differently affect downstream metabolic pathways which influence basil growth, development and metabolism. In this study, basil was grown from seedlings to fully developed plants in a microcosm, an innovative device aimed at growing plants indoor as in natural conditions. Specifically, the effects of white (W) and blue-red (BR) light under a photosynthetic photon flux density of 255 μmol m^-2 s^-1 on plant growth, photochemistry, soluble nutrient concentration and secondary metabolism were investigated. Plants grew taller (41.8 ± 5.0 vs. 28.4 ± 2.5 cm) and produced greater biomass (150.3 ± 24.2/14.7 ± 2.0 g vs. 116.2 ± 28.3/12.3 ± 2.5 g fresh/dry biomass) under W light compared to BR light. The two lighting conditions differently influenced the soluble nutrient concentration and the translocation rate. No photosynthetic stress was observed under the two lighting regimes, but leaves grown under W light displayed higher levels of maximum quantum yield of PSII and electron transport rate. Sharp differences in metabolic patterns under the two lighting regimes were detected with higher concentrations of phenolic compounds under the BR light.

Prediction of Phenolic Contents Based on Ultraviolet-B Radiation in Three-Dimensional Structure of Kale Leaves

Ultraviolet-B (UV-B, 280-315 nm) radiation has been known as an elicitor to enhance bioactive compound contents in plants. However, unpredictable yield is an obstacle to the application of UV-B radiation to controlled environments such as plant factories. A typical three-dimensional (3D) plant structure causes uneven UV-B exposure with leaf position and age-dependent sensitivity to UV-B radiation. The purpose of this study was to develop a model for predicting phenolic accumulation in kale (Brassica oleracea L. var. acephala) according to UV-B radiation interception and growth stage. The plants grown under a plant factory module were exposed to UV-B radiation from UV-B light-emitting diodes with a peak at 310 nm for 6 or 12 h at 23, 30, and 38 days after transplanting. The spatial distribution of UV-B radiation interception in the plants was quantified using ray-tracing simulation with a 3D-scanned plant model. Total phenolic content (TPC), total flavonoid content (TFC), total anthocyanin content (TAC), UV-B absorbing pigment content (UAPC), and the antioxidant capacity were significantly higher in UV-B-exposed leaves. Daily UV-B energy absorbed by leaves and developmental age was used to develop stepwise multiple linear regression models for the TPC, TFC, TAC, and UAPC at each growth stage. The newly developed models accurately predicted the TPC, TFC, TAC, and UAPC in individual leaves with R ² > 0.78 and normalized root mean squared errors of approximately 30% in test data, across the three growth stages. The UV-B energy yields for TPC, TFC, and TAC were the highest in the intermediate leaves, while those for UAPC were the highest in young leaves at the last stage. To the best of our knowledge, this study proposed the first statistical models for estimating UV-B-induced phenolic contents in plant structure. These results provided the fundamental data and models required for the optimization process. This approach can save the experimental time and cost required to optimize the control of UV-B radiation.

Adaptalight: An Inexpensive PAR Sensor System for Daylight Harvesting in a Micro Indoor Smart Hydroponic System

Environmental changes and the reduction in arable land have led to food security concerns around the world, particularly in urban settings. Hydroponic soilless growing methods deliver plant nutrients using water, conserving resources and can be constructed nearly anywhere. Hydroponic systems have several complex attributes that need to be managed, and this can be daunting for the layperson. Micro Indoor Smart Hydroponics (MISH) leverage Internet of Things (IoT) technology to manage the complexities of hydroponic techniques, for growing food at home for everyday citizens. Two prohibitive costs in the advancement of MISH systems are power consumption and equipment expense. Reducing cost through harvesting ambient light can potentially reduce power consumption but must be done accurately to sustain sufficient plant yields. Photosynthetic Active Radiation (PAR) meters are commercially used to measure only the light spectrum that plants use, but are expensive. This study presents Adaptalight, a MISH system that harvests ambient light using an inexpensive AS7265x IoT sensor to measure PAR. The system is built on commonly found IoT technology and a well-established architecture for MISH systems. Adpatalight was deployed in a real-world application in the living space of an apartment and experiments were carried out accordingly. A two-phase experiment was conducted over three months, each phase lasting 21 days. Phase one measured the IoT sensor’s capability to accurately measure PAR. Phase two measured the ability of the system to harvest ambient PAR light and produce sufficient yields, using the calibrated IoT sensor from phase one. The results showed that the Adaptalight system was successful in saving a significant amount of power, harvesting ambient PAR light and producing yields with no significant differences from the control. The amount of power savings would be potentially greater in a location with more ambient light. Additionally, the findings show that, when calibrated, the AS7265x sensor is well suited to accurately measure PAR light in MISH systems.

SpaceHort: redesigning plants to support space exploration and on-earth sustainability

Crewed missions to Mars are planned within the next twenty years. Production of food and materials in situ will eventually be necessary for mission success. This will require the development of crops which can thrive in environments we can sustain in Space. Here, we discuss the challenges we must solve to provide adequate nutrition to support long term Space habitation. Further, we propose that plants are an ideal biomanufacturing platform for producing pharmaceuticals and biomaterials on demand. Designing Space plants requires advances in our ability to engineer plant biology in a predictive manner. Parallel development of suitable tightly controlled growth environments, including extensive monitoring and sensing, will also be a key enabler. Collectively, such research promises to deliver solutions for progressing sustainable closed environment agriculture on Earth.

Single Wavelengths of LED Light Supplement Promote the Biosynthesis of Major Cyclic Monoterpenes in Japanese Mint

Environmental light conditions influence the biosynthesis of monoterpenes in the mint plant. Cyclic terpenes, such as menthol, menthone, pulegone, and menthofuran, are major odor components synthesized in mint leaves. However, it is unclear how light for cultivation affects the contents of these compounds. Artificial lighting using light-emitting diodes (LEDs) for plant cultivation has the advantage of preferential wavelength control. Here, we monitored monoterpene contents in hydroponically cultivated Japanese mint leaves under blue, red, or far-red wavelengths of LED light supplements. Volatile cyclic monoterpenes, pulegone, menthone, menthol, and menthofuran were quantified using the head-space solid phase microextraction method. As a result, all light wavelengths promoted the biosynthesis of the compounds. Remarkably, two weeks of blue-light supplement increased all compounds: pulegone (362% increase compared to the control), menthofuran (285%), menthone (223%), and menthol (389%). Red light slightly promoted pulegone (256%), menthofuran (178%), and menthol (197%). Interestingly, the accumulation of menthone (229%) or menthofuran (339%) was observed with far-red light treatment. The quantification of glandular trichomes density revealed that no increase under light supplement was confirmed. Blue light treatment even suppressed the glandular trichome formation. No promotion of photosynthesis was observed by pulse-amplitude-modulation (PAM) fluorometry. The present result indicates that light supplements directly promoted the biosynthetic pathways of cyclic monoterpenes.

Ulva intestinalis Extract Acts as Biostimulant and Modulates Metabolites and Hormone Balance in Basil (Ocimum basilicum L.) and Parsley (Petroselinum crispum L.)

Natural elicitors from macroalgae may affect plant secondary metabolites. Ulvan is a sulfated heteropolysaccharide extracted from green seaweed, acting as both a plant biotic protecting agent, and a plant elicitor, leading to the synthesis of signal molecules. In this work, the aqueous extract of Ulva intestinalis L., mainly composed of ulvan, was used as foliar-spraying treatment and its eliciting effect was investigated in basil (Ocimum basilicum L.) and parsley (Petroselinum crispum L.). Antioxidant metabolites (polyphenols and carotenoids), volatile compounds (both in headspace emissions and hydrodistilled essential oils), and hormones (jasmonic acid, salicylic acid, salicylic acid 2-O-β-D-glucoside, abscisic acid, and azelaic acid) were quantified. The foliar-spraying treatment with U. intestinalis extract increased salicylic acid and its β-glucoside in parsley; in basil, it induced the accumulation of jasmonic and abscisic acids, indicating the presence of a priming effect. In basil, the elicitation caused a change of the essential oil (EO) chemotype from methyl eugenol/eugenol to epi-α-cadinol and increased sesquiterpenes. In parsley EO it caused a significant accumulation of 1,3,8-p-menthatriene, responsible of the typical “parsley-like” smell. In both species, the phenylpropanoids decreased in headspace and EO compositions, while the salicylic acid concentration increased; this could indicate a primarily defensive response to U. intestinalis extract. Due to the evidenced significant biological activity, U. intestinalis extract used as an elicitor may represent a suitable tool to obtain higher amounts of metabolites for optimizing plant flavor metabolites.

From Prediction to Prescription: Evolutionary Optimization of Nonpharmaceutical Interventions in the COVID-19 Pandemic

Several models have been developed to predict how the COVID-19 pandemic spreads, and how it could be contained with nonpharmaceutical interventions, such as social distancing restrictions and school and business closures. This article demonstrates how evolutionary AI can be used to facilitate the next step, i.e., determining most effective intervention strategies automatically. Through evolutionary surrogate-assisted prescription, it is possible to generate a large number of candidate strategies and evaluate them with predictive models. In principle, strategies can be customized for different countries and locales, and balance the need to contain the pandemic and the need to minimize their economic impact. Early experiments suggest that workplace and school restrictions are the most important and need to be designed carefully. They also demonstrate that results of lifting restrictions can be unreliable, and suggest creative ways in which restrictions can be implemented softly, e.g., by alternating them over time. As more data becomes available, the approach can be increasingly useful in dealing with COVID-19 as well as possible future pandemics.

Ethnobotany and the Role of Plant Natural Products in Antibiotic Drug Discovery

The crisis of antibiotic resistance necessitates creative and innovative approaches, from chemical identification and analysis to the assessment of bioactivity. Plant natural products (NPs) represent a promising source of antibacterial lead compounds that could help fill the drug discovery pipeline in response to the growing antibiotic resistance crisis. The major strength of plant NPs lies in their rich and unique chemodiversity, their worldwide distribution and ease of access, their various antibacterial modes of action, and the proven clinical effectiveness of plant extracts from which they are isolated. While many studies have tried to summarize NPs with antibacterial activities, a comprehensive review with rigorous selection criteria has never been performed. In this work, the literature from 2012 to 2019 was systematically reviewed to highlight plant-derived compounds with antibacterial activity by focusing on their growth inhibitory activity. A total of 459 compounds are included in this Review, of which 50.8% are phenolic derivatives, 26.6% are terpenoids, 5.7% are alkaloids, and 17% are classified as other metabolites. A selection of 183 compounds is further discussed regarding their antibacterial activity, biosynthesis, structure-activity relationship, mechanism of action, and potential as antibiotics. Emerging trends in the field of antibacterial drug discovery from plants are also discussed. This Review brings to the forefront key findings on the antibacterial potential of plant NPs for consideration in future antibiotic discovery and development efforts.

Creative AI Through Evolutionary Computation: Principles and Examples

The main power of artificial intelligence is not in modeling what we already know, but in creating solutions that are new. Such solutions exist in extremely large, high-dimensional, and complex search spaces. Population-based search techniques, i.e. variants of evolutionary computation, are well suited to finding them. These techniques make it possible to find creative solutions to practical problems in the real world, making creative AI through evolutionary computation the likely "next deep learning."

Changes in Tea Plant Secondary Metabolite Profiles as a Function of Leafhopper Density and Damage

Insect herbivores have dramatic effects on the chemical composition of plants. Many of these induced metabolites contribute to the quality (e.g., flavor, human health benefits) of specialty crops such as the tea plant (Camellia sinensis). Induced chemical changes are often studied by comparing plants damaged and undamaged by herbivores. However, when herbivory is quantitative, the relationship between herbivore pressure and induction can be linearly or non-linearly density dependent or density independent, and induction may only occur after some threshold of herbivory. The shape of this relationship can vary among metabolites within plants. The tea green leafhopper (Empoasca onukii) can be a widespread pest on tea, but some tea farmers take advantage of leafhopper-induced metabolites in order to produce high-quality "bug-bitten" teas such as Eastern Beauty oolong. To understand the effects of increasing leafhopper density on tea metabolites important for quality, we conducted a manipulative experiment exposing tea plants to feeding by a range of E. onukii densities. After E. onukii feeding, we measured volatile and non-volatile metabolites, and quantified percent damaged leaf area from scanned leaf images. E. onukii density had a highly significant effect on volatile production, while the effect of leaf damage was only marginally significant. The volatiles most responsive to leafhopper density were mainly terpenes that increased in concentration monotonically with density, while the volatiles most responsive to leaf damage were primarily fatty acid derivatives and volatile phenylpropanoids/benzenoids. In contrast, damage (percent leaf area damaged), but not leafhopper density, significantly reduced total polyphenols, epigallocatechin gallate (EGCG), and theobromine concentrations in a dose-dependent manner. The shape of induced responses varied among metabolites with some changing linearly with herbivore pressure and some responding only after a threshold in herbivore pressure with a threshold around 0.6 insects/leaf being common. This study illustrates the importance of measuring a diversity of metabolites over a range of herbivory to fully understand the effects of herbivores on induced metabolites. Our study also shows that any increases in leafhopper density associated with climate warming, could have dramatic effects on secondary metabolites and tea quality.

Optimization of Photoperiod and Quality Assessment of Basil Plants Grown in a Small-Scale Indoor Cultivation System for Reduction of Energy Demand

Vertical farming is a novel type of food production in indoor environments with artificial lighting and controlled cultivation conditions. In this context, sustainability in small-scale indoor cultivation systems is crucial. Sustainability can be achieved by optimizing all the cultivation factors involved in the production process. The effects of different photoperiod conditions under different timing during plant development—from sowing to germination and maturity—have been studied in a small-scale indoor cultivation area. The main objective of this research was to investigate the possibilities of an optimized photoperiod for basil plants to reduce the energy demand cost of the cultivation unit. Three different photoperiod treatments (P8D16L, P10D14L, and P11D13L) were applied to basil plants with stable light intensity. Furthermore, the photoperiod was shortened to test the reaction of the biomass from the plants in a reduced energy demand system. The dry biomass produced was measured along with the energy consumed in each treatment. The basil quality was assessed by measuring different physiological indices, such as chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (Chl tot), the fraction of photosynthetically active irradiance absorbed by the leaf, and leaf temperature. The results of the study showed that a shorter photoperiod did not negatively affect the quantity and quality of the basil plants. Continuously, the evaluation of the energy demand variation under the different photoperiod treatments can provide a significant positive impact on the energetic, ecological, and economic aspects of small-scale food production.