Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping

Wintersterfte van bijenvolken 2021-2022 : Resultaten van een enquête naar wintersterfte onder bijenvolken in Nederland in de winter van 2021 – 2022

Ieder jaar wordt in Nederland een monitor gehouden onder bijenhouders naar de gezondheidstoestand van hun bijenvolken en de manier waarop ze bijenhouden. De voornaamste uitkomst van deze enquêteis de wintersterfte, die een indicatie geeft van de gezondheidstoestand van de gehouden populatie bijenvolken in Nederland. Dit rapport geeft een overzicht van de resultaten van deze monitor. De monitor is gehouden in april en mei van dit jaar en bestond uit een vragenlijst met als doel basisgegevens over de bijenhouders en de bijenhouderij te verzamelen. Een tweede deel bestond uit een vragenlijst die ieder jaar wordt opgesteld in samenwerking met instituten die participeren in de COLOSS werkgroep monitoring. Hier doen meer dan 35 landen, voornamelijk in Europa aan mee.De enquête bestaat ieder jaar uit dezelfde drie onderdelen: het eerste gedeelte gaat over de gegevens van de bijenhouder, het tweede gedeelte over de bepaling van de wintersterfte en het laatste gedeelteis de COLOSS-enquête met een aantal toegevoegde vragen die relevant zijn voor de Nederlandse bijenhouderij. Deze toegevoegde vragen kunnen aangepast worden naar gelang de wens van de opdrachtgever en de kennisbehoefte.In de winter van 2021-2022 ging 18,4% van de gehouden populatie bijenvolken dood. 81,6% van de bijenvolken overleefde de winter. De sterfte is hoger dan de twee voorgaande jaren toen respectievelijk15.8% (2020-2021) en 13.1% van de bijenvolken de winter niet overleefden. 46.5% van de bijenhouders rapporteerde geen sterfte van volken in de winter. Dit is een kleiner deel van de bijenhouders dan in het voorgaande jaar (52%). Op basis van de respons wordt het aantal bijenvolken per bijenhouder in Nederland geschat op 9.34. Doorgerekend naar het aantal bijenvolken in Nederland,komen we uit op een schatting van 90078 bijenvolken.Een aantal andere highlights van de resultaten: De respondenten oogstten gemiddeld zo’n 8.2 kg honing per bijenvolk. Dit is bijna een halvering ten opzichte van vorig jaar (14.8 kg) maar ongeveer evenveel als het jaar daarvoor (8 kg). De prijs voor een kilogram honing die respondenten rekenen is €12,27 en de totale productiekosten komen uit op een gemiddelde van €528,63,- per respondent. 74.3% van de respondenten geeft aan niet te reizen met hun bijen. 18,1% van de bijenhouders geeft aan niet aan varroa-bestrijding te doen.De resultaten van de COLOSS-enquête worden in internationaal verband geanalyseerd en vergeleken met de resultaten daarvan uit andere landen. In totaal doen zo’n 35 landen mee aan de COLOSS-enquête. De resultaten worden in de loop van 2022 ter publicatie aan een wetenschappelijk tijdschrift aangeboden

Transfer of tomato immune receptor Ve1 confers Ave1-dependent Verticillium resistance in tobacco and cotton

Summary: Verticillium wilts caused by soilborne fungal species of the Verticillium genus are economically important plant diseases that affect a wide range of host plants and are notoriously difficult to combat. Perception of pathogen(-induced) ligands by plant immune receptors is a key component of plant innate immunity. In tomato, race-specific resistance to Verticillium wilt is governed by the cell surface-localized immune receptor Ve1 through recognition of the effector protein Ave1 that is secreted by race 1 strains of Verticillium spp. It was previously demonstrated that transgenic expression of tomato Ve1 in the model plant Arabidopsis thaliana leads to Verticillium wilt resistance. Here, we investigated whether tomato Ve1 can confer Verticillium resistance when expressed in the crop species tobacco (Nicotiana tabcum) and cotton (Gossypium hirsutum). We show that transgenic tobacco and cotton plants constitutively expressing tomato Ve1 exhibit enhanced resistance against Verticillium wilt in an Ave1-dependent manner. Thus, we demonstrate that the functionality of tomato Ve1 in Verticillium wilt resistance through recognition of the Verticillium effector Ave1 is retained after transfer to tobacco and cotton, implying that the Ve1-mediated immune signalling pathway is evolutionary conserved across these plant species. Moreover, our results suggest that transfer of tomato Ve1 across sexually incompatible plant species can be exploited in breeding programmes to engineer Verticillium wilt resistance

The activation-tagged Arabidopsis mutant A2 is more resistant to <i>V. dahliae</i> and <i>V. albo-atrum</i>.

<p>(A) Typical symptoms of <i>Verticillium</i> on the wild-type (WS) and the activation-tagged mutant A2. Picture was taken at 21 days post inoculation (dpi) and a representative of three independent experimental replicates is shown. (B) Relative quantification (RQ) by real-time PCR of Verticillium colonization by comparing levels of the <i>V. dahliae</i> (white bars) and <i>V. albo-atrum</i> (grey bars) internal transcribed spacer (ITS) region of the ribosomal DNA (as measure for fungal biomass) relative to levels of the large subunit of the Arabidopsis <i>RubisCo</i> gene (for equilibration) at 14 and 21 dpi. Bars represent averages with standard deviation of four technical replicates. A representative of three independent experiments is shown. (C) Relative quantification (RQ) of <i>EWR1</i> transcription level in the wild-type WS and the activation-tagged mutant A2. The bar represents the average of three independent experiments and standard deviation of the means and asterisks indicate significant differences (Dunnett t-test at <i>P = 0.01</i>) compared to the wild-type WS.</p

<i>EWR1</i> is highly conserved in <i>Brassicaceae</i>.

<p>(A) Schematic representation of the full-length genomic DNA sequence of <i>EWR1</i> gene. (B) Nucleotide sequence alignment of <i>AtEWR1</i> and its homologs from <i>Arabidopsis lyrata</i> (<i>AlEWR1</i>), <i>Brassica oleracea</i> var. <i>gemmifera</i> (<i>BoEWR1</i>), <i>Brassica rapa (BrEWR1)</i>, and <i>Sisymbrium irio</i> (<i>SiEWR1</i>).</p

<i>BoEWR1</i> over-expression enhances Arabidopsis resistance to Verticillium wilt.

<p>(A). Typical disease symptoms caused by <i>V. dahliae</i> on the wild-type (WS) and three independent <i>BoEWR1</i> over-expressing plants (BoEWR1-1, BoEWR1-2 and BoEWR1-3) at 21 days post inoculation (dpi). The experiment was repeated at least three times and representative of the three independent biological replications is shown. (B) <i>Verticillium</i>-induced stunting of wild-type (WS), three independent <i>BoEWR1</i> over-expressing plants (BoEWR1-1, BoEWR1-2 and BoEWR1-3) at 21 dpi. Rosette diameters of inoculated plants were compared with those of mock-inoculated plants. The bars represent averages of three independent experiments with standard deviation and asterisks indicate significant differences (Dunnett t-test at <i>P = 0.05</i>). (C) Relative quantification (RQ) by real-time PCR of <i>Verticillium</i> colonization by comparing levels of the <i>V. dahliae</i> internal transcribed spacer (ITS) region of the ribosomal DNA (as measure for fungal biomass) relative to levels of the large subunit of the Arabidopsis <i>RubisCo</i> gene (for equilibration) at 21 dpi. Bars represent averages with standard deviation of four technical replicates. A representative of three independent experiments is shown. (D) Relative quantification (RQ) of <i>EWR1</i> transcription in wild-type (WS) and three independent <i>BoEWR1</i> over-expressing plants (BoEWR1-1 and BoEWR1-2, and BoEWR1-3). Bars represent averages with standard deviation of three biological replicates</p

<i>EWR1</i> over-expressing Arabidopsis plants are resistant to <i>V. dahliae</i>.

<p>(A) Typical symptoms of <i>V. dahliae</i> on the wild-type (Col-0), three <i>EWR1</i> expressing lines (EWR1-1, EWR1-2, and EWR1-3) and <i>EWR1</i> knock out line (<i>ewr1</i>). Picture was taken at 21 days post inoculation and a representative of three experimental replicates is shown. (B) Disease severity score for the wild-type (Col-0), the three <i>EWR1</i> expressing lines (EWR1-1, EWR1-2, and EWR1-3) and <i>EWR1</i> knock out line (<i>ewr1</i>) at 14 (white bar) and 21 (grey bar) days post inoculation (dpi). The total number of rosette leaves and the number of rosette leaves that showed Verticillium symptoms were counted at least from eight plants and percentage of the diseased leaves were calculated as an indication of disease severity. The bars represent the average of three independent experiments with standard deviation and asterisks indicate significance differences (Dunnett t-test at <i>P = 0.05</i>). (C) Relative quantification (RQ) by real-time PCR of Verticillium colonization by comparing levels of the <i>V. dahliae</i> internal transcribed spacer (ITS) region of the ribosomal DNA (as measure for fungal biomass) relative to levels of the large subunit of the Arabidopsis <i>RubisCo</i> gene (for equilibration) at 21 dpi. Bars represent averages with standard deviation of four technical replicates. A representative of three independent experiments is shown.</p

<i>AtEWR1</i> over-expressing plants are tolerant to drought stress.

<p>Three weeks-old wild-type Col-0, <i>AtEWR1</i> expressing line (EWR1-2) and <i>AtEWR1</i> knock out line (<i>ewr1</i>) plants were exposed to drought stress and picture was taken at 14 days post drought treatment. The assay was repeated three times and a representative of the replicates is shown.</p

Deletion of <i>EWR1</i> enhances Arabidopsis susceptibility to Verticillium wilt.

<p>(A) Typical symptoms of <i>V. dahliae</i> on the wild-type (Col-0) and <i>EWR1</i> knock out (<i>ewr1</i>) plants. Picture was taken at 21 days post inoculation (dpi) and a representative of three independent experimental replicates is shown. (B) Disease severity score for the wild-type (Col-0) and <i>ewr1</i> at 14 (white bar) and 21 (grey bar) days post inoculation (dpi). The total number of rosette leaves and the number of rosette leaves that showed Verticillium symptoms were counted at least from eight plants and percentage of the diseased leaves were calculated as an indication of disease severity. The bars represent averages of three independent experiments with standard deviation and asterisks indicate significance differences (Dunnett t-test at <i>P = 0.05</i>). (C) Relative quantification (RQ) by real-time PCR of Verticillium colonization by comparing levels of the <i>V. dahliae</i> internal transcribed spacer (ITS) region of the ribosomal DNA (as measure for fungal biomass) relative to levels of the large subunit of the Arabidopsis <i>RubisCo</i> gene (for equilibration) at 21 dpi. Bars represent averages with standard deviation of four technical replicates. A representative of three independent experiments is shown.</p