Search

Thermomorphogenesis is, among other traits, characterized by enhanced hypocotyl elongation due to the induction of auxin biosynthesis genes like YUCCA8 by transcription factors, most notably PHYTOCHROME INTERACTING FACTOR 4 (PIF4). Efficient binding of PIF4 to the YUCCA8 locus under warmth depends on HISTONE DEACETYLASE 9 (HDA9) activity, which mediates histone H2A.Z depletion at the YUCCA8 locus. However, HDA9 lacks intrinsic DNA-binding capacity, and how HDA9 is recruited to YUCCA8, and possibly other PIF4-target sites, is currently not well understood. The Mediator complex functions as a bridge between transcription factors bound to specific promoter sequences and the basal transcription machinery containing RNA polymerase II. Mutants of Mediator component Mediator25 (MED25) exhibit reduced hypocotyl elongation and reduced expression of YUCCA8 at 27°C. In line with a proposed role for MED25 in thermomorphogenesis in Arabidopsis (Arabidopsis thaliana), we demonstrated an enhanced association of MED25 to the YUCCA8 locus under warmth and interaction of MED25 with both PIF4 and HDA9. Genetic analysis confirmed that MED25 and HDA9 operate in the same pathway. Intriguingly, we also showed that MED25 destabilizes HDA9 protein. Based on our findings, we propose that MED25 recruits HDA9 to the YUCCA8 locus by binding to both PIF4 and HDA9.

Agriculture is facing many challenges that are related to increased prices of farming inputs, labor shortage, and climate change. Advanced machines and autonomous vehicles as well as sensor systems with increased capabilities are now present on the farm and can offer solutions to these challenges but the issue that remains is how to connect the components involved in forming an integrated digital farming system. At the same time, ISO 11783 (commonly designated as ISOBUS) is playing a substantial role in farming and an increasing number of ISOBUS-compliant machines can be seen among the farm machinery. Under this perspective, the newly funded H2020 project Robs4Crops is trying to combine agricultural robotics with the already existing implements by leveraging ISOBUS. The aim is to integrate autonomous vehicles into the available farm infrastructure and not include them as proprietary solutions. In addition, the project aims at increasing the intelligence of the implements by using sensors and analytics that in real-time can assess the efficiency of the operation performed and subsequently, by using ISOBUS, inform the robots in order for the latter to take relevant action. This work describes the development of perception units for spraying and mechanical weeding machines and how these “intelligent” implements are using ISOBUS to communicate with two different agricultural robots. From the existing results, it is becoming clear that ISOBUS can play an important role in introducing agricultural robots in farming but also facilitate the cyber-physical connection between the implements and the cloud-based solutions (e.g. digital twins).

The ‘Winterlichtkas’ was designed for high light transmission in the winter months: 10% more than a conventional Venlo greenhouse (Kempkes et al., 2015). The Winterlichtkas which was built in 2016 at test location IDC-Energy at Wageningen University & Research BU Greenhouse Horticulture in Bleiswijk. During the years 2017-2019, 4 cucumber crop cycles took place in the Winterlichtkas with the aim to find an optimal crop and climate strategy in which this extra amount of light can be converted into assimilates and thus fresh produce (Kempkes et al., 2022). Principles from ‘Het Nieuwe Telen’ and a low energy input were key. The aim of this study in 2021 was to minimize CO₂ dosing: a maximum 10 kg was allowed instead of the common practice of 30 kg. In the summer trial of 2021, WUR managed to produce 60 kg/m2 to 67 kg/m2 for the different varieties with reduced CO₂ supply of 8.3 kg CO2. The cultivation cycle started in April and ended the first week of September. This study was commissioned by Kas as Energiebron. De winterlichtkas is een kas met een 10% hogere lichtdoorlatendheid, met de focus op de wintermaanden, dan een standaard Venlo kas (Kempkes et al., 2015). Gedurende de jaren 2017-2019 heeft WUR 4 komkommerteelten in de winterlichtkas beproefd, waarbij werd gezocht naar een gewas- en klimaatstrategie waar deze extra hoeveelheid licht ook optimaal omgezet kon worden in assimilaten en daarmee versproductie, (Kempkes et al., 2022). In de zomer van 2021 heeft WUR in het kader van Kas als Energiebron onderzocht of er met een derde van de standaard gedoseerde hoeveelheid CO2 (in plaats van 30 maximaal 10 kg/m2 in 5 maanden), een vergelijkbare productie en kwaliteit behaald kan worden als in de praktijk. De teelt liep van april tot en met de eerste week van september 2021. In die periode zijn met een verbruik van 8,3 kg CO2 producties van 60 kg/m2 tot 67 kg/m2 voor de verschillende rassen behaald.

The increasing acreage of strawberry under protected conditions has to be cultivated fossil free and sustainably,certainly given the recent rise in energy prices. Commissioned by Kas als Energiebron, WUR and Delphy have described how such a cultivation system looks like. A general description of future strawberry cultivation has been given, current knowledge and knowledge gaps are given, and an with computation model options for further energy saving steps are quantified. Computations are performed for three situations, viz., cultivating a not-illuminated ever-bearing cultivar, an illuminated ever-bearing cultivar, and a low-chill fresh cultivar. Using thoughtful setpoints already leads to considerable energy saving. Furthermore, attention is given to lowering air temperature, increasing relative air humidity, and longer or higher lighting. The consequences for the use of gas, electricity and CO2 are estimated for all situations. The remains an energy demand for heating and lighting, however, these should be supplied from non-fossil sources. Het toenemende areaal aardbei onder glas moet fossielvrij en duurzaam worden geteeld, zeker gezien de recente stijging in energieprijzen. WUR en Delphy hebben in opdracht van Kas als Energiebron beschreven hoe zo’n aardbeiteelt er uit ziet. Er is een schets op hoofdlijnen van de toekomstige aardbeiteelt opgesteld, de bestaande kennis en kennishiaten zijn geïnventariseerd, en met een rekenmodel is een schatting gemaakt van de stappen die er nog kunnen worden gezet. Hiervoor is gerekend aan drie teelten, namelijk een onbelichte doorteelt, een belichte doorteelt, en een low-chill verse teelt. Door op het scherpst van de snede te telen is er al veel te bereiken. Er is verder gekeken naar het verlagen van de luchttemperatuur, het verhogen van de relatieve luchtvochtigheid, en langer of intensiever belichten. Voor alle situaties zijn de gevolgen voor het gebruik van gas, elektriciteit en CO2 berekend. Er blijft behoefte aan energie voor verwarming en belichting, alleen moet deze van niet-fossiele oorsprong zijn.

Cultivation and breeding of legumes as protein sources in the human or animal diet could benefit from accurate, rapid, and non-invasive measurements of protein content. A study was conducted into the feasibility of a fully non-invasive, in vivo protein measurement methodology applied to soybean (Glycine max. L.). The proposed methodology works by recording spectral images of the soybean pods in the visible and near-infrared (Vis-NIR), a rule-based segmentation approach, and partial least squares (PLS) regression to predict the crude protein content of the beans contained within the imaged pods. Using all 150 channels of the spectral camera, a model could be calibrated with a mean absolute precision error (MAPE) of 4.8 % (R2 = 0.92). Applying a tailored feature elimination approach to select only eight spectral bands and degrading the spectral resolution to 25 nm yields a model with a MAPE of 6.0 % (R2 = 0.88), indicating the potential for multispectral cameras in this application.

The detection and sizing of fruits with computer vision methods is of interest because it provides relevant information to improve the management of orchard farming. However, the presence of partially occluded fruits limits the performance of existing methods, making reliable fruit sizing a challenging task. While previous fruit segmentation works limit segmentation to the visible region of fruits (known as modal segmentation), in this work we propose an amodal segmentation algorithm to predict the complete shape, which includes its visible and occluded regions. To do so, an end-to-end convolutional neural network (CNN) for sim ultaneous modal and amodal instance segmentation was implemented. The predicted amodal masks were used to estimate the fruit diameters in pixels. Modal masks were used to identify the visible region and measure the distance between the apples and the camera using the depth image. Finally, the fruit diameters in millimetres (mm) were computed by applying the pinhole camera model. The method was developed with a Fuji apple dataset consisting of 3925 RGB-D images acquired at different growth stages with a total of 15,335 annotated apples, and was subsequently tested in a case study to measure the diameter of Elstar apples at different growth stages. Fruit detection results showed an F1-score of 0.86 and the fruit diameter results reported a mean absolute error (MAE) of 4.5 mm and R2 = 0.80 irrespective of fruit visibility. Besides the diameter estimation, modal and amodal masks were used to automatically determine the percentage of visibility of measured apples. This feature was used as a confidence value, improving the diameter estimation to MAE = 2.93 mm and R2 = 0.91 when limiting the size estimation to fruits detected with a visibility higher than 60%. The main advantages of the present methodology are its robustness for measuring partially occluded fruits and the capability to determine the visibility percentage. The main limitation is that depth images were generated by means of photogrammetry methods, which limits the efficiency of data acquisition. To overcome this limitation, future works should consider the use of commercial RGB-D sensors. The code and the dataset used to evaluate the method have been made publicly available at https://github.com/GRAP-UdL-AT/Amodal_Fruit_Sizing. This work was partly funded by the Departament de Recerca i Universitats de la Generalitat de Catalunya (grant 2021 LLAV 00088), the Spanish Ministry of Science, Innovation and Universities (grants RTI2018-094222-B-I00 [PAgFRUIT project], PID2021-126648OB-I00 [PAgPROTECT project] and PID2020-117142GB-I00 [DeeLight project] by MCIN/AEI/10.13039/501100011033 and by “ERDF, a way of making Europe”, by the European Union). The work of Jordi Gen´e Mola was supported by the Spanish Ministry of Universities through a Margarita Salas postdoctoral grant funded by the European Union - NextGenerationEU. We would also like to thank Nufri (especially Santiago Salamero and Oriol Morreres) for their support during data acquisition, and Pieter van Dalfsen and Dirk de Hoog from Wageningen University & Research for additional data collection used in the case study.

Background A well-known method for evaluating plant resistance to insects is by measuring insect reproduction or oviposition. Whiteflies are vectors of economically important viral diseases and are, therefore, widely studied. In a common experiment, whiteflies are placed on plants using clip-on-cages, where they can lay hundreds of eggs on susceptible plants in a few days. When quantifying whitefly eggs, most researchers perform manual eye measurements using a stereomicroscope. Compared to other insect eggs, whitefly eggs are many and very tiny, usually 0.2mm in length and 0.08mm in width; therefore, this process takes a lot of time and effort with and without prior expert knowledge. Plant insect resistance experiments require multiple replicates from different plant accessions; therefore, an automated and rapid method for quantifying insect eggs can save time and human resources. Results In this work, a novel automated tool for fast quantification of whitefly eggs is presented to accelerate the determination of plant insect resistance and susceptibility. Leaf images with whitefly eggs were collected from a commercial microscope and a custom-built imaging system. A deep learning-based object detection model was trained using the collected images. The model was incorporated into an automated whitefly egg quantification algorithm, deployed in a web-based application called Eggsplorer. Upon evaluation on a testing dataset, the algorithm was able to achieve a counting accuracy as high as 0.94,r2of 0.99, and a counting error of ± 3 eggs relative to the actual number of eggs counted by eye. The automatically collected counting results were used to determine the resistance and susceptibility of several plant accessions and were found to yield significantly comparable results as when using the manually collected counts for analysis. Conclusion This is the first work that presents a comprehensive step-by-step method for fast determination of plant insect resistance and susceptibility with the assistance of an automated quantification tool. Further information This article was published in the BMC Plant Methodsjournal. The datasets underlying this publication can be foundhere.&nbsp

The dataset was generated for the needs of the 3rd International Autonomous Greenhouse Challenge in the experimental facilities of the Greenhouse Horticulture Business Unit in Bleiswijk, The Netherlands in 2022. Information regarding the competition can be found here http://www.autonomousgreenhouses.com/

Plant-to-plant variation (interplant variation) may play an important role in determining individual plant and whole canopy performance, where interplant variation in architecture and photosynthesis traits has direct effects on light absorption and photosynthesis. We aimed to quantify the importance of observed interplant variation on both whole-plant and canopy light absorption and photosynthesis. Plant architecture was measured in two experiments with fruiting tomato crops (Solanum lycopersicum) grown in glasshouses in the Netherlands, in week 16 (Exp. 1) or week 19 (Exp. 2) after transplanting. Experiment 1 included four cultivars grown under three supplementary lighting treatments, and Experiment 2 included two different row orientations. Measured interplant variations of the architectural traits, namely, internode length, leaf area, petiole angle, and leaflet angle, as well as literature data on the interplant variation of the photosynthesis traits alpha, Jmax28, and Vcmax28, were incorporated in a static functional–structural plant model (FSPM). The FSPM was used to analyze light absorption and net photosynthesis of whole plants in response to interplant variation in architectural and photosynthesis traits. Depending on the trait, introducing interplant variation in architecture and photosynthesis traits in a functional–structural plant model did not affect or negatively affected canopy light absorption and net photosynthesis compared with the reference model without interplant variation. Introducing interplant variation of architectural and photosynthesis traits in FSPM results in a more realistic simulation of variation of plants within a canopy. Furthermore, it can improve the accuracy of simulation of canopy light interception and photosynthesis although these effects at the canopy level are relatively small (<4% for light absorption and

The ‘Winterlichtkas’ was designed for high light transmission in the winter months: 10% more than a conventional Venlo greenhouse (Kempkes et al., 2015). The Winterlichtkas which was built in 2016 at test location IDC-Energy at Wageningen University & Research BU Greenhouse Horticulture in Bleiswijk. During the years 2017-2019, 4 cucumber crop cycles took place in the Winterlichtkas with the aim to find an optimal crop and climate strategy in which this extra amount of light can be converted into assimilates and thus fresh produce (Kempkes et al., 2022). Principles from ‘Het Nieuwe Telen’ and a low energy input were key. The aim of this study in 2021 was to minimize CO₂ dosing: a maximum 10 kg was allowed instead of the common practice of 30 kg. In the summer trial of 2021, WUR managed to produce 60 kg/m2 to 67 kg/m2 for the different varieties with reduced CO₂ supply of 8.3 kg CO2. The cultivation cycle started in April and ended the first week of September. This study was commissioned by Kas as Energiebron.

The increasing acreage of strawberry under protected conditions has to be cultivated fossil free and sustainably,certainly given the recent rise in energy prices. Commissioned by Kas als Energiebron, WUR and Delphy have described how such a cultivation system looks like. A general description of future strawberry cultivation has been given, current knowledge and knowledge gaps are given, and an with computation model options for further energy saving steps are quantified. Computations are performed for three situations, viz., cultivating a not-illuminated ever-bearing cultivar, an illuminated ever-bearing cultivar, and a low-chill fresh cultivar. Using thoughtful setpoints already leads to considerable energy saving. Furthermore, attention is given to lowering air temperature, increasing relative air humidity, and longer or higher lighting. The consequences for the use of gas, electricity and CO2 are estimated for all situations. The remains an energy demand for heating and lighting, however, these should be supplied from non-fossil sources.

Recent studies indicate that food demand will increase by 35–56% over the period 2010–2050 due to population increase, economic development, and urbanization. Greenhouse systems allow for the sustainable intensification of food production with demonstrated high crop production per cultivation area. Breakthroughs in resource-efficient fresh food production merging horticultural and AI expertise take place with the international competition “Autonomous Greenhouse Challenge”. This paper describes and analyzes the results of the third edition of this competition. The competition’s goal is the realization of the highest net profit in fully autonomous lettuce production. Two cultivation cycles were conducted in six high-tech greenhouse compartments with operational greenhouse decision-making realized at a distance and individually by algorithms of international participating teams. Algorithms were developed based on time series sensor data of the greenhouse climate and crop images. High crop yield and quality, short growing cycles, and low use of resources such as energy for heating, electricity for artificial light, and CO2 were decisive in realizing the competition’s goal. The results highlight the importance of plant spacing and the moment of harvest decisions in promoting high crop growth rates while optimizing greenhouse occupation and resource use. In this paper, images taken with depth cameras (RealSense) for each greenhouse were used by computer vision algorithms (Deepabv3+ implemented in detectron2 v0.6) in deciding optimum plant spacing and the moment of harvest. The resulting plant height and coverage could be accurately estimated with an R2 of 0.976, and a mIoU of 98.2, respectively. These two traits were used to develop a light loss and harvest indicator to support remote decision-making. The light loss indicator could be used as a decision tool for timely spacing. Several traits were combined for the harvest indicator, ultimately resulting in a fresh weight estimation with a mean absolute error of 22 g. The proposed non-invasively estimated indicators presented in this article are promising traits to be used towards full autonomation of a dynamic commercial lettuce growing environment. Computer vision algorithms act as a catalyst in remote and non-invasive sensing of crop parameters, decisive for automated, objective, standardized, and data-driven decision making. However, spectral indexes describing lettuces growth and larger datasets than the currently accessible are crucial to address existing shortcomings between academic and industrial production systems that have been encountered in this work.

In the past decade, the potential of positioning LED lamps in between the canopy (intra-canopy) to enhance crop growth and yield has been explored in greenhouse cultivation. Changes in spatial heterogeneity of light absorption that come with the introduction of intra-canopy lighting have not been thoroughly explored. We calibrated and validated an existing functional structural plant model (FSPM), which combines plant morphology with a ray tracing model to estimate light absorption at leaflet level. This FSPM was used to visualize the light environment in a tomato crop illuminated with intra-canopy lighting, top lighting or a combination of both. Model validation of light absorption of individual leaves showed a good fit (R2 = 0.93) between measured and modelled light absorption of the canopy. Canopy light distribution was then quantified and visualized in three voxel directions by means of average absorbed photosynthetic photon flux density (PPFD) and coefficient of variation (CV) within that voxel. Simulations showed that the variation coefficient within horizontal direction was higher for intra-canopy lighting than top lighting (CV=48% versus CV= 43%), while the combination of intra-canopy lighting and top lighting yielded the lowest CV (37%). Combined intra-canopy and top lighting (50/50%) had in all directions a more uniform light absorption than intra-canopy or top lighting alone. The variation was minimal when the ratio of PPFD from intra-canopy to top lighting was about 1, and increased when this ratio increased or decreased. Intra-canopy lighting resulted in 8% higher total light absorption than top lighting, while combining 50% intra-canopy lighting with 50% top lighting, increased light absorption by 4%. Variation in light distribution was further reduced when the intra-canopy LEDs were distributed over strings at four instead of two heights. When positioning LED lamps to illuminate a canopy both total light absorption and light distribution have to be considered.

Most applications of remote sensing in agricultural crop monitoring use multispectral imaging techniques, but with upcoming hyperspectral missions, the opportunity arises to better estimate pigment absorption and crop structure by exploiting the full solar reflective spectrum. In this study, we demonstrate how hyperspectral time series can be used with the Soil Canopy Observation of Photochemistry and Energy fluxes (SCOPE) model to estimate crop yield variability among fields, crop varieties and nitrogen treatments generically, i.e. without a calibration with in situ, data. Field experiments were conducted in two potato fields in the Netherlands between May and September 2019. The fields were planted with five varieties of potato, under three nitrogen fertilization treatments. By fitting the model to the full VNIR-SWIR spectrum of measured hyperspectral reflectance, we retrieved the model input parameters of Leaf Area Index (LAI), leaf chlorophyll content (Cab) and leaf water content (Cw) and simulated the photosynthesis throughout the season using data of local Automatic Weather Stations (AWS). Statistical analysis of measured and retrieved traits of LAI, Cab and canopy water content showed that two fields responded differently to the treatments, exhibiting fewer classes than were expected based on the experimental design. Potato yield, which was estimated as the sum of photosynthesis flux multiplied by the harvest index of 0.64, correlated with the measured tuber dry weight with R2 0.36 and RMSE 2.5 t ha−1. This study demonstrates that even in the absence of crop or variety specific information, hyperspectral reflectance and local weather data ingested into SCOPE can explain a substantial part of the observed variability in yield among fields.

Purpose of Review The world-wide demand for agricultural products is rapidly growing. However, despite the growing population, labor shortage becomes a limiting factor for agricultural production. Further automation of agriculture is an important solution to tackle these challenges. Recent Findings Selective harvesting of high-value crops, such as apples, tomatoes, and broccoli, is currently mainly performed by humans, rendering it one of the most labor-intensive and expensive agricultural tasks. This explains the large interest in the development of selective harvesting robots. Selective harvesting, however, is a challenging task for a robot, due to the high levels of variation and incomplete information, as well as safety. Summary This review paper provides an overview of the state of the art in selective harvesting robotics in three different production systems; greenhouse, orchard, and open field. The limitations of current systems are discussed, and future research directions are proposed.

Over the last decade, LED lighting has gained considerable interest as an energy efficient light source in greenhouse horticulture. Much work on LED lighting is done under controlled conditions in the absence of sun light, whereas the primary application lies in supplementation of low light conditions in winter. A frequently forgotten aspect herein is that spectral composition may also affect the biology of pests and their natural enemies, both directly and indirectly through an impact on induced plant resistance. In this paper, we present results of trials with chrysanthemum and alstroemeria cut flowers which were exposed to lighting regimes with varying contributions of blue, green, red and far-red light. These trials were done under low levels of natural light, mimicking winter conditions. In chrysanthemum, spectra where blue or green were added did not affect stem length, plant dry weight and number of flowers when the percentage of red light remained over 75%. Replacing part of the photosynthetically active radiation (PAR) light by far-red light considerably increased stem length and (in some species) plant dry weight, at the expense of flowering. In alstroemeria, the number of flowers harvested, their length and fresh weight was largest in the treatment with equal shares of blue, green, red and far-red light. In chrysanthemum, the beneficial insect Orius laevigatus was introduced and its egg-laying activity and population development under different lighting strategies was monitored. The number of eggs laid by the first Orius generation was affected by the percentage red light in the spectrum, with the lowest egg number found in plants grown under 95% red. The results for egg-laying by the second Orius generation differed among chrysanthemum cultivars. The implications of this work on lighting strategies for greenhouse horticulture are discussed, both in spectral composition and in timing during the day and the season.

As earlier leaf removal experiments in tomato had shown that this improved dry matter partitioning to the fruits and production, a pilot experiment with high-wire cucumber was conducted in the spring and summer of 2016 at the experimental research facilities of Wageningen UR Greenhouse Horticulture. The five treatments were combinations of 3 or 3.5 stems m-2, and 0, 16 or 33% leaf removal in head of the crop. The combination 3.5/0% was lacking. The experimental data were analysed with the INTKAM crop growth model. The total number of fruits m-2 was the most important factor for production, which is determined by the optimal combination of stem density and assimilate supply. It is therefore important to grow the crop such that the maximum number of fruits with sufficient weight can be realized. Leaf removal in itself led to a slightly higher abortion, a lower development rate and therefore less axils, and a lower LAI with less light interception, and therefore produced less fruits and kilos. This, however, can be compensated with a higher stem density. It results in a crop with a normal LAI and architecture, combined with more axils m-2 that can bear fruits. Production and light use efficiency increase. On the other hand, labour and the risk to harvest small fruits will increase.

The world population is increasing rapidly together with the demand for healthy fresh food. Greenhouse industry can play an important role, but encounters difficulties finding skilled staff to manage crop production. Artificial intelligence (AI) reaches breakthroughs in several areas, however, not yet in horticulture. An international competition on “autonomous greenhouses” aims in combining horticultural expertise with AI to make breakthroughs in fresh food production with fewer resources. Five international teams with different background in horticulture and AI participated in a growing experiment. Each team had a 96-m2 modern greenhouse compartment at WUR to grow remotely a cucumber crop ('Hi-Power') during a 4-months period. Each compartment was equipped with standard actuators and sensors, heating, ventilation, screening, artificial lighting, fogging, CO2 supply and irrigation. Climate control set points were remotely determined by teams using own AI algorithms, actuators were operated by a climate and irrigation process computer. Additionally, teams sent instructions for the crop pruning strategy. Measurements and set points were exchanged via a digital interface. Achievements in AI-controlled compartments were compared with a reference compartment, operated manually by three commercial growers. Teams used additional individually chosen sensors such as RGB or thermal cameras, temperature-humidity-light-sensor-networks, root-zone sensors, sap-flow meters or crop-weighing sensors. Teams' strategies for remote control ranged from supervised, unsupervised and reinforcement machine learning. Teams were judged and received points on several aspects: 50% for net profit, 20% for sustainability indicators, energy- and water-use-efficiency and CO2 consumption, 30% for their artificial intelligence algorithms, novelty, level of autonomous control, robustness and scalability. The results obtained by different teams in terms of climate and growing strategies, different resource use efficiency and net profit are presented in this paper. One of the AI-controlled compartments achieved overall better results than the manual grown reference compartment.

The world population is increasing rapidly together with the demand for healthy fresh food. Greenhouse industry can play an important role, but encounters difficulties finding skilled staff to manage crop production. Artificial intelligence (AI) reaches breakthroughs in several areas, however, not yet in horticulture. An international competition on “autonomous greenhouses” aims in combining horticultural expertise with AI to make breakthroughs in fresh food production with fewer resources. Five international teams with different background in horticulture and AI participated in a growing experiment. Each team had a 96-m2 modern greenhouse compartment at WUR to grow remotely a cucumber crop ('Hi-Power') during a 4-months period. Each compartment was equipped with standard actuators and sensors, heating, ventilation, screening, artificial lighting, fogging, CO2 supply and irrigation. Climate control set points were remotely determined by teams using own AI algorithms, actuators were operated by a climate and irrigation process computer. Additionally, teams sent instructions for the crop pruning strategy. Measurements and set points were exchanged via a digital interface. Achievements in AI-controlled compartments were compared with a reference compartment, operated manually by three commercial growers. Teams used additional individually chosen sensors such as RGB or thermal cameras, temperature-humidity-light-sensor-networks, root-zone sensors, sap-flow meters or crop-weighing sensors. Teams' strategies for remote control ranged from supervised, unsupervised and reinforcement machine learning. Teams were judged and received points on several aspects: 50% for net profit, 20% for sustainability indicators, energy- and water-use-efficiency and CO2 consumption, 30% for their artificial intelligence algorithms, novelty, level of autonomous control, robustness and scalability. The results obtained by different teams in terms of climate and growing strategies, different resource use efficiency and net profit are presented in this paper. One of the AI-controlled compartments achieved overall better results than the manual grown reference compartment.

Horticultural production faces a growing demand for mechanization, automation and robotics as labour costs are increasing and the availability of skilled labour is decreasing. The modern consumer demands guaranteed and constant quality. Moreover, there are intensified hygiene, food safety and traceability demands. Automated production and quality assessment systems can contribute to fulfil these demands. Many highly automated systems are already applied in commercial high-tech greenhouses. This includes logistics and autonomous transport of plants and harvested product from the greenhouse to the sorting and packing facilities, spraying robots, machine vision based sorting systems for pot-plants and cut-flowers and robotic cutting, planting and grafting machines. Current research focus on automated crop scouting (e.g., insect and disease detection), phenotyping (e.g., monitoring and predicting fruit setting) and postharvest quality assessment. Many research activities are currently carried out on robotic systems that are capable to autonomously harvest crops and to conduct other repetitive and labour intensive operations. In most of these applications the success rate and cycle time are currently still too low to allow implementation in commercial practice. Human-robot collaboration and “human in the loop” applications are important stepping-stones towards full automation. These applications must also include the key issues of user safety and user acceptance. From the plant side, breeding crops with novel phenotypes and plant architectures, such as fruits which are easy to see and reach by robots, will simplify and accelerate the application of robotics in the horticultural field. Challenges involve the complex integration of multiple disciplines and technologies (e.g., navigation, safe operation, grasping, manipulation, perception, learning and adaptation). Current developments are supported by the worldwide rapid improvements in computing and sensor hardware, software and artificial intelligence.

The function of the arrangement of leaves (phyllotaxy) in a plant increases its ability to perform photosynthesis by positioning the leaves to maximize the surface area available to intercept sunlight. In mangroves species, phyllotaxis is an unexplored phenomenon with the exception of early work from Tomlinson and Wheat. Available red mangrove models do not provide the needed flexibility in representation of tree architecture, which is needed to analyse and reconstruct the detailed architecture of saplings. The objective of the current study was to generate the phyllotactic pattern for red mangrove saplings (Rhizophora mangle) based on our 3D digitized model, in situ measurements, photographic analysis and using an algorithm. Onsite mangrove saplings (between 1 and 2.5 m) from Turneffe Atoll, Belize, were photographed. The above-ground part was digitized using the electromagnetic digitizing equipment (FASTRAK® Polhemus Inc.), high-resolution photos of the leaf arrangements were taken along with field notes and the model was constructed using the software GroIMP (Growth-grammar-related Interactive Modelling Platform). Our algorithm, enriched by probabilistic approaches for the purpose of handling perturbations in phyllotactic patterns, was able to closely refoliate our 3D model. We then used the resulting hybrid model, composed of the digitized branching structure and the algorithmically generated leaves, to simulate the interception of light by individual leaves, employing the stochastic raytracing-based radiation model. This preliminary result allows us to assess and visualize the photosynthetic contributions of single leaves throughout the canopy. Simulations of other processes (flows in xylem and phloem; mechanical behaviour) could be based on such a model.

Previous studies have shown that wool can adsorb contaminants present in the air. In this study it was determined how much ammonia or nitrous oxide could be absorbed by the untreated wool of each of three sheep races. In an airtight glass chamber supplied with a fixed amount of ammonia or nitrous oxide the concentration was monitored after a piece of wool was added. The wool of Schoonebeeker and Blauwe Texelaar sheep absorbed on average 0.11 g kg-1 ammonia, while Drentse heide sheep wool absorbed 0.09 g kg-1. Repeated additions of ammonia were absorbed at the same rate. For all wool types no absorption of nitrous oxide was observed. Research in cattle stables should be carried out to determine the real air purification of ammonia by installed wool material. Schapenwol bleek in eerder onderzoek luchtzuiverende eigenschappen te bezitten. In dit onderzoek is voor onbehandelde wol van drie Nederlandse schapenrassen bepaald hoeveel ammoniak of stikstofoxide wordt vastgelegd in de wol. Hiervoor is met luchtdichte meetstolpen en kunstmatig toegevoegde stikstofcomponent bepaald in hoeverre de concentratie in de lucht afneemt. Van de drie getoetste wolsoorten nemen de Schoonebeeker en Blauwe Texelaar wol volgens de stolpmetingen gemiddeld ca. 0.11 g ammonia kg-1 wol op, terwijl Drentse heide wol ca 0.09 g kg-1 opneemt. Herhaalde blootstelling aan ammoniak laat steeds weer vergelijkbare opname-hoeveelheden door de wol zien. Er vond geen opname van NO2 door de wol plaats. Onderzoek in de praktijk moet uitwijzen of het aanbrengen van schapenwol in stallen tot daadwerkelijke zuivering van ammoniak in de stallucht leidt.

Previous studies have shown that wool can adsorb contaminants present in the air. In this study it was determined how much ammonia or nitrous oxide could be absorbed by the untreated wool of each of three sheep races. In an airtight glass chamber supplied with a fixed amount of ammonia or nitrous oxide the concentration was monitored after a piece of wool was added. The wool of Schoonebeeker and Blauwe Texelaar sheep absorbed on average 0.11 g kg-1 ammonia, while Drentse heide sheep wool absorbed 0.09 g kg-1. Repeated additions of ammonia were absorbed at the same rate. For all wool types no absorption of nitrous oxide was observed. Research in cattle stables should be carried out to determine the real air purification of ammonia by installed wool material.

Achieving the desired stem length is important in the winter cultivation of chrysanthemums under LED lighting. Earlier research showed that stem length under full-LED can be controlled by “end of day” lighting with 20 μmol/m²/s far-red light for 30 minutes. The question is whether the same effect can be achieved with a lower intensity or a shorter period of “end of the day” far-red light. Measurements on four chrysanthemum varieties grown under 200 mol/m²/sfull LED showed that the effect of 20 or 10 minutes of “end of the day” far red light was comparable to 30 minutes of 20 μmol/m²/s far red light. Reducing the intensity of the “end of the day” far red to 10 or 5 μmol/m2/s also had asimilar effect. To obtain this effect, lighting with “end of the day” far red light only during the first weeks of cultivation is not sufficient. The “end of the day” far red light has a greater effect on elongation or time to harvest than the lightspectrum during the day, where the proportion of green light was varied between 0 and 15% at the expense of red light. These results show that it is quite possible to grow chrysanthemums under full LED, and that there are sufficientpossibilities with light colors to control the crop in such a way that a desired stem quality can be achieved.

In this project a conceptual framework is made about different types of plant stress in a greenhouse cultivation. The aim is to get a better understanding of plant stress and to prevent the need for energy consuming actions when a plant is “out of balance”. What is plant stress? A plant strives for homeostasis: all chemical and physical processes are in balance with the environment. In a stress situation, a plant senses the change that disturbs the balance between plant and environment. The plant adapts to the new situation which leads to a new balance (acclimation). That means that stress can have a negative impact on the crop, but stress can also be beneficial. Crop and climate management both disturb the balance and steer the crop in the desired direction, which is considered as positive stress. The cultivation method “Next Generation Growing” aims for balances in crop and greenhouse. It is not always clear which actions lead to positive stress and which actions are negative for the crop. Monitoring plant balance or plant stress would be a helpful tool. But a lot is still unknown, like which plant processes should be monitored, what are critical values and what time period is needed for “a balanced crop”. In dit project is een denkkader opgesteld om na te gaan welke vormen van nuttige en negatieve plantstress er in de kas voorkomen. Het doel daarvan is om meer begrip te krijgen, en daarmee energievragende bijsturing te voorkomen als het gewas “uit balans” is. Maar wat is plantstress? Een plant streeft naar homeostase: dat betekent dat alle chemische en fysische processen in evenwicht zijn met de omgeving. Bij stress worden door de plant veranderingen waargenomen in de omgeving die leiden tot verstoring van het evenwicht tussen plant en omgeving die vragen om aanpassingen in de plant en deze leiden tot een nieuwe balans (acclimatie). Dat betekent dat stress negatieve effecten kan hebben op het gewas, maar dat stress ook nuttig kan zijn. Teelthandelingen die een teler doet om zijn gewas te sturen halen de plant uit balans en sturen de plant in de gewenste richting en worden beschouwd als nuttige stress. Het Nieuwe Telen stuurt op balansen in de plant en kas om te voorkomen dat het gewas uit balans is. Het is de vraag welke acties leiden tot nuttige stress en wanneer er negatieve stress optreedt. Het monitoren van plantbalans of stress zou hierbij een hulpmiddel kunnen zijn maar roept veel vragen op met betrekking tot welke onderliggende plantprocessen gemeten moeten worden, welke grenswaarden er gelden en over welke tijdsperiode “balans” gaat.

Powdery mildew on strawberry (Podosphaera aphanis) leaf and fruit is one of the most important diseases in strawberry. Mildew in strawberry depends on the number of spores in the air leading to infection, on the microclimate around the plant and on the variety. Germination of spores and mycelium growth takes place in the boundary layer close to leaf and fruit. This project looked at the influence of the microclimate in the boundary layer of leaf and fruit on mildew infection and how this may contribute to a management strategy of mildew. First, the thickness of the boundary layer was determined. Subsequently, the microclimate in this boundary layer was measured and climate data were compared with the greenhouse. With these data, a model of the microclimate was drawn up based on measured climate values in the surrounding greenhouse air, leading to a good predictability (R2=0.98). This makes it possible to calculate the microclimate in the boundary layer of leaves and fruits based on measured climate values in the surrounding greenhouse air without the need for specific microclimate sensors. Data from mildew incidence were collected and linked to the microclimate in the boundary layer. Microclimate settings that appeared to inhibit or promote mildew development were then tested in climate chamber experiments measuring mildew germination and mycelium development. It appeared that germination of mildew spores on young leaves is higher than on old leaves, that germination increases with an increase in relative humidity and that temperatures above 30oC inhibit germination. Mycelium development immediately after inoculation was not linked to the microclimate, while outwardly visible mycelium increased two weeks after inoculation at higher relative humidity. This shows that for mildew development, relative humidity appears to be a more important factor for the microclimate than temperature. Based on these data, a first model for the prediction of mildew germination depending on the microclimate was set up leading to a reasonable predictability (R2=0.79).

The development towards a sustainable and climate-neutral greenhouse horticulture requires zero emission, zero use of natural gas and the use of biological control of pests and diseases. The challenge is how to keep the crop productive and healthy with minimal energy input. To achieve this, the use of efficient lighting systems such as LEDs is essential. The fact that LED lighting can be adjusted in color offers new opportunities, but also raises questions regarding the most suitable light spectrum. This research shows that young tomato and cucumber plants can be cultivated well under different light spectra. The balance of blue and far-red light primarily determine the elongation, and thus the plant architecture. This allows the propagation and cultivation of crops towards the required plant morphology. Light spectrum did not affect plant weight and early fruit production of snack cucumber. A light spectrum with a higher proportion of red light is perceived by insects as higher light intensities, which improves reproduction and activity. This knowledge can be used to adapt the strategy to release natural enemies to the lighting conditions in the greenhouse. In een duurzame en klimaatneutrale glastuinbouw wordt gewerkt zonder gebruik van chemische gewasbeschermingsmiddelen en gas, en deze is vrij van emissies. De uitdaging hierbij is hoe het gewas productief én gezond kan worden gehouden met minimale energiekosten. Om dit te realiseren is het gebruik van efficiënte belichtingssystemen zoals LEDs essentieel. Het feit dat de kleuren van LED belichting instelbaar zijn, biedt nieuwe kansen om gewaseigenschappen te sturen, maar roept ook vragen op ten aanzien van het meest geschikte lichtspectrum. De experimenten in dit onderzoek laten zien dat de teelt van jonge tomaten- en komkommerplanten goed kan onder verschillende lichtkleuren, waarbij met name de balans tussen blauw en verrood licht de mate van strekking bepaalt. Daarmee kan tijdens de opkweek en de start van de teelt gestuurd worden op het telen van een plant met de gewenste plantvorm. Het lichtspectrum had geen effect op plantgewicht en op de vroege productie van snackkomkommer. Een lichtspectrum met een hoger aandeel rood licht wordt door insecten ervaren als condities met meer licht, wat de zoekactiviteit ten goede komt. Deze kennis kan gebruikt worden om de uitzetstrategie van natuurlijke vijanden aan te passen aan de lichtomstandigheden in de kas.

To combine the development towards sustainable and climate-neutral cultivation systems for all-electric greenhouses with lighting, efficient lighting systems such as LEDs are essential. LEDs have a high energy-efficiency and make it possible to apply dynamic light recipes, in which light intensity and spectral composition can be varied throughout the day and during the cultivation depending on the developmental stage of the crop. Knowledge on the effects of light spectrum is still limited for most crops, as well as the effect of spectral composition on the control of pests and diseases in the crop. In this project, we took an integrated approach that combines research on the effects of dynamic light spectra on the growth and production of eggplant, tomatoes and cucumbers with the effects on plant resistance to pests and diseases, incorporating the underlying physiological and genetic processes. The behavior of pests and natural enemies has been further investigated in chrysanthemum and sweet pepper. The results indicate that growth and production of greenhouse grown crops can be controlled with the light spectrum, whereby resistance to diseases and pests is a precondition. Om de ontwikkeling naar duurzame en klimaatneutrale teeltsystemen voor all-electric glastuinbouw te kunnen combineren met belichting zijn efficiënte belichtingssystemen zoals LEDs essentieel. LED biedt energetische voordelen en maakt het mogelijk om dynamische lichtrecepten toe te passen, waarbij lichtintensiteit en lichtkleur gedurende de dag en gedurende de teelt naar behoefte van het gewas gevarieerd kunnen worden. Voor de meeste gewassen is er nog maar een zeer beperkte kennis over de effecten van het lichtspectrum op het gewas, maar zeker ook over welke rol het lichtspectrum speelt in het beheersen van ziekten en plagen in het gewas. In dit project wordt een geïntegreerde benadering gekozen waarbij effecten van dynamische lichtspectra op de groei en productie van aubergine, tomaat en komkommer onderzocht zijn, met daarbij ook de effecten op plantweerbaarheid tegen ziekten en plagen, waarbij ook gekeken wordt naar de onderliggende fysiologische en genetische processen. In chrysant en paprika is het gedrag van plagen en natuurlijke vijanden verder onderzocht. De resultaten geven aan dat groei en productie van deze gewassen gestuurd kan worden met het lichtspectrum, waarbij de weerbaarheid tegen ziekten en plagen een randvoorwaarde is.

In a desk study financed by Kas als Energiebron, WUR and Delphy investigated the possibilities of fossil-free cultivation of woody soft fruit under glass. To this end, discussions were held with growers. In addition to a description of the current situation in woody berries, a literature study was conducted in which the results of national and international research on blackberries and raspberries, which mainly related to climate factors, were listed. Partly on the basis of this, an attempt has been made to provide a vision of a fossil-free future for woody soft fruit and what measures growers of blackberries and raspberries could take to achieve this. A number of knowledge gaps with regard to woody berries have also been identified.

When glass is laminated for safety reasons, it usually blocks UV radiation partially or even completely when UV blocking materials are used. In the last decade, there has been an increasing interest in interlayers with high UV transmission, especially in relation to greenhouse applications. In this paper, we present an overview of the effects of UV transmittance on plant growth and development, in order to advice on the use of the high transmission interlayers versus the standard interlayers. Using UV transmitting films instead of UV blocking films has opportunities to alter plant growth and morphology. In general, plants grow more compact with increased UV transmittance, growth and biomass are reduced, flowering is stimulated (although the effects are species dependent), concentrations of secondary metabolites which are positive from nutritional perspective are stimulated and flower appearance (color) can be positively influenced. Pollination by bees is improved when UV is present and plant resilience to pests and diseases is improved. These results show that UV transmitting materials can have potential to be used in for example botanical gardens, office centers and garden markets, where producing biomass might even be unfavorable. On the contrary, the increased ornamental value by improved shape and flower color will be appreciated. Therefore, these aspects of transmitting UV to plants can have potential for markets where plant production is not the main goal.

In this project a conceptual framework is made about different types of plant stress in a greenhouse cultivation. The aim is to get a better understanding of plant stress and to prevent the need for energy consuming actions when a plant is “out of balance”. What is plant stress? A plant strives for homeostasis: all chemical and physical processes are in balance with the environment. In a stress situation, a plant senses the change that disturbs the balance between plant and environment. The plant adapts to the new situation which leads to a new balance (acclimation). That means that stress can have a negative impact on the crop, but stress can also be beneficial. Crop and climate management both disturb the balance and steer the crop in the desired direction, which is considered as positive stress. The cultivation method “Next Generation Growing” aims for balances in crop and greenhouse. It is not always clear which actions lead to positive stress and which actions are negative for the crop. Monitoring plant balance or plant stress would be a helpful tool. But a lot is still unknown, like which plant processes should be monitored, what are critical values and what time period is needed for “a balanced crop”.