Entity
Description
  • Value proposition

    Image Analytics Solutions for Agriculture

    Our Mission is to bring image analysis tools to the agricultural research community and your field trial programs.
    Hiphen has been serving the crop breeding and research communities around the globe since 2014 bringing tools that make processing images easier and more impactful. We’ve built a platform that helps organizations:
    • Effectively acquire research grade images
    • Innovatively analyze those images
    • Efficiently incorporate the images and data into product development pipelines
    We analyze images every day from satellites, to drones to phenomobiles and even smartphones. We would love to help you achieve your phenotyping ambitions.


    High Thoughput Phenotyping, Plant Functionning, Plant Measurements, Remote Sensing, Data Analytics, Agronomy, Decision Tools, Multispectral Sensors, IoT, Satellite, Artificial Intelligence, Deep Learning, Agriculture, and Plant Models

  • Original language

    Image Analytics Solutions for Agriculture

    Hiphen imagine, crée et développe des systèmes de phénotypage de plantes haut-débit en champ.

    Nous proposons une combinaison unique de compétences sur les capteurs, en traitement de données et en physiologie des plantes pour extraire des traits physiologiques pertinents.

    Hiphen offre des outils et des services flexibles, facilement adaptables à vos besoins spécifiques.

    Contactez-nous pour plus d’information !

  • Hiphen - Plant Phenotyping and Crop Image Analytics Solutions

    Hiphen expertise is in High Troughput Plant Phenotyping, data acquisition and deep learning image analysis solutions applied to agriculture.

  • https://www.hiphen-plant.com/
Corporate interactions BETA
Corporate TypeTweets Articles
The Yield Lab
The Yield Lab
Venture Capital and Private Equity Principals
The Yield Lab
Venture Capital and Private Equity Principals
Other

18 Dec 2022


La Tribune
La Tribune
Media, Newspapers
La Tribune
Media, Newspapers
Other

1 Feb 2019


DigitalFoodLab
DigitalFoodLab
Startup accelerator & VC, Business Consulting and Services
DigitalFoodLab
Startup accelerator & VC, Business Consulting and Services
Other

2 Mar 2018


Région Auvergne-Rhône-Alpes
Région Auvergne-Rhône-Alpes
National and local authorities, Government Administration
Région Auvergne-Rhône-Alpes
National and local authorities, Government Administration
Other

25 May 2018


Agri Sud-Ouest Innovation
Agri Sud-Ouest Innovation
Public business cluster, French Cluster, Food and Beverage Manufacturing
Agri Sud-Ouest Innovation
Public business cluster, French Cluster, Food and Beverage Manufacturing
Other

17 Nov 2020


NASA - National Aeronautics and Space Administration
NASA - National Aeronautics and Space Administration
Research, Aviation and Aerospace Component Manufacturing
NASA - National Aeronautics and Space Administration
Research, Aviation and Aerospace Component Manufacturing
Other

6 Jan 2023


Bosch
Bosch
Manifacturing tools, Software Development
Bosch
Manifacturing tools, Software Development
Other

16 Jan 2019


Amazon
Amazon
IT services, Consumer Electronics, Software Development
Amazon
IT services, Consumer Electronics, Software Development
Other

15 Oct 2022


Airbus
Airbus
Defence and Aerospace, Aviation and Aerospace Component Manufacturing
Airbus
Defence and Aerospace, Aviation and Aerospace Component Manufacturing
Other

6 Jan 2023


Irstea
Irstea
Environment, Government Administration
Irstea
Environment, Government Administration
Other

11 Apr 2019


Hiphen
3 days, 20 hours ago 2

𝐀𝐂𝐂𝐄𝐋𝐄𝐑𝐀𝐓𝐈𝐍𝐆 𝐍𝐄𝐖 𝐓𝐑𝐀𝐈𝐓𝐒 𝐓𝐎 𝐌𝐀𝐑𝐊𝐄𝐓 𝐂𝐘𝐂𝐋𝐄𝐒
At Hiphen we help breeding teams rapidly and efficiently phenotype breeding lines. We always keep up on the latest developments in the breeding world like developments in gene editing technology applied to crops.
From nature biotechnology
"Genome editing using CRISPR–Cas9 works efficiently in plant cells1, but delivery of genome-editing machinery into the vast majority of crop varieties is not possible using established methods2. (Timothy Kelliher) et al. co-opted the aberrant reproductive process of haploid induction (HI)3,4,5,6 to induce edits in nascent seeds of diverse monocot and dicot species. The method, named HI-Edit, enables direct genomic modification of commercial crop varieties. HI-Edit was tested in field and sweet corn using a native haploid-inducer line4 and extended to dicots using an engineered CENH3 HI system7. They also recovered edited wheat embryos using Cas9 delivered by maize pollen. The data indicate that a transient hybrid state precedes uniparental chromosome elimination in maize HI. Edited haploid plants lack both the haploid-inducer parental DNA and the editing machinery. 𝐓𝐡𝐞𝐫𝐞𝐟𝐨𝐫𝐞, 𝐞𝐝𝐢𝐭𝐞𝐝 𝐩𝐥𝐚𝐧𝐭𝐬 𝐜𝐨𝐮𝐥𝐝 𝐛𝐞 𝐮𝐬𝐞𝐝 𝐢𝐧 𝐭𝐫𝐚𝐢𝐭 𝐭𝐞𝐬𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐢𝐫𝐞𝐜𝐭𝐥𝐲 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐢𝐧𝐭𝐨 𝐜𝐨𝐦𝐦𝐞𝐫𝐜𝐢𝐚𝐥 𝐯𝐚𝐫𝐢𝐞𝐭𝐲 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭."

#plantphenotyping
#Highthroughputphenotyping
#ImageAnalysis4Ag
#crispr-cas9


Dakota Starr
Jared Carter
Peter Wittich
Shujie Dong
Quideng Que
Nic Bate
Pairwise
https://lnkd.in/dzMKGGa

Hiphen
1 week ago 23 2

𝐍𝐎𝐖 𝐓𝐇𝐀𝐓 𝐇𝐈𝐆𝐇 𝐓𝐇𝐑𝐎𝐔𝐆𝐇𝐏𝐔𝐓 𝐏𝐇𝐄𝐍𝐎𝐓𝐘𝐏𝐈𝐍𝐆 𝐈𝐒 𝐁𝐄𝐂𝐎𝐌𝐈𝐍𝐆 𝐌𝐎𝐑𝐄 𝐀𝐂𝐂𝐄𝐒𝐒𝐈𝐁𝐋𝐄 - 𝐇𝐎𝐖 𝐃𝐎 𝐖𝐄 𝐁𝐄𝐒𝐓 𝐔𝐒𝐄 𝐓𝐇𝐄 𝐃𝐀𝐓𝐀?

Very interesting paper by Fred van Eeuwijk and Scott Chapman et al. As high throughput phenotyping data becomes more accessible to #plantbreeding practitioners, correcting spatially and temporally will become critical in maximizing the quality and confidence in the decisions that will be based on the models for genomic prediction based on phenotypic responses to the environment.

"A primary objective and problem in plant breeding remains the improvement of yield. Therefore, the utility of new genotyping and phenotyping techniques should be evaluated in the light of the additional genetic gain for yield that can be obtained by the implementation of new techniques, where cost-benefit considerations should be made in relation to the speed and cost of the additional genetic gain. Yield is an example of a complex trait characterized by the contributions of many genes with relatively small effects that show strong context dependencies in the form of epistatic and genotype by environment interactions (G × E). These context dependencies complicate the breeding process [1–3]. Improvement of yield is made in relation to a target population of environments (TPE), i.e. the set of conditions for which the genotypes (cultivars, varieties) are bred [3,4]. Across the TPE, typically the environmental conditions change to an extent that the phenotypic response curves of individual genotypes, the reaction norms [5,6], will show divergence, convergence, and intersection, which is an expression of G × E. Traditional phenotyping strategies consist of the evaluation of genotypes in a number of trials across a number of locations for a number of years, called multi-environment trials (METs). The hope is that the trials in the MET form a representative sample from the conditions in the TPE and that the MET provides enough information for identifying and estimating G × E patterns with enough precision to decide upon a strategy on how to handle G × E [7,8]."

Daniela Bustos-Korts
Emilie Millet
Martin Boer
Willem Kruijer
Addie Thompson
Marcos Malosetti
Hiroyoshi IWATA
Roberto Quiroz
Christian Kuppe
Onno Muller
Konstantinos Blazakis
Kang Yu
Francois Tardieu
https://lnkd.in/dWU7A2ji #plantphenotyping
#Highthroughputphenotyping
#ImageAnalysis4Ag
#Innoag
#plantbreeding
#agtech
#agstats

Hiphen
1 week, 1 day ago 49

🌱 [#Event] 🌱
COME MEET US AT THE BIGGEST FIELD EXPERIMENTATION TECHNOLOGY SHOW IN FRANCE

Alexis Comar is pleased to welcome you today at the #AFMEX2023 show in Le Mans, France to talk image analytics for phenotyping adapted to #seedbreeding & #AgInputs applications - If you're in town feel free to stop by!

🇫🇷 Aujourd'hui nous exposons au salon #AFMEX2023, pour y présenter nous solutions de #phénotypage haut-débit adaptées à l'expérimentation agricole en plein champs, qui répondent notamment aux problématiques des #semenciers et des producteurs d'#intrants.

🌱 N'hésitez pas à vous arrêter à notre stand afin de discuter d'analyse d'image pour le phénotypage des plantes. Alexis Comar notre PDG vous recevra avec grand plaisir.

#phenotyping #plantbreeding #agtech

Hiphen
1 week, 2 days ago 65 2

🌱 [#InsideHiphen] 🌱
INSTALLING A PHENOTYPING MEASUREMENT HEAD ON A LYSIMETRIC PLATFORM

Our team is currently out in #Morocco to install a new system on a lysimetric platform of ICARDA; International Center for Agricultural Research in the Dry Areas.

🚀 This system will help their team to boost #drought #tolerance research enabling them to combine lysimetric measurements with phenotypic data to make the best decisions.

💎 Equipped with a state-of-the-art 3D sensor (LiDAR) + RGB cameras with flashes, the system will be able to deliver #traits such as plant biovolume, organs count, greeness, disease detection, potential transpiration rate, and more. In addition, the system is fitted with an on-site smart processing unit for almost real-time decisions.

👉 Discover more about our PhenoMobile® product range at www.hiphen-phenomobile.com
#phenotyping #agtech #plantbreeding #AI

Hiphen
1 week, 3 days ago 32

𝐂𝐨𝐦𝐛𝐢𝐧𝐢𝐧𝐠 𝐂𝐫𝐨𝐩 𝐆𝐫𝐨𝐰𝐭𝐡 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠 𝐚𝐧𝐝 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐆𝐞𝐧𝐞𝐭𝐢𝐜 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠 𝐭𝐨 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐞 𝐏𝐡𝐞𝐧𝐨𝐭𝐲𝐩𝐢𝐧𝐠 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬
Daniela Bustos-Korts Marin Boer, Marcos Malosetti Scott Chapman Karine Chenu, Bangyou Sheng, Fred van Eeuwijk
At Hiphen we are always looking for ways to make the data we generate as impactful as possible. To that end we try to stay up on the literature and the researchers working on the challenges facing 21st century agriculture.

"Genomic prediction of complex traits, say yield, benefits from including information on correlated component traits. Statistical criteria to decide which yield components to consider in the prediction model include the heritability of the component traits and their genetic correlation with yield. Not all component traits are easy to measure. Therefore, it may be attractive to include proxies to yield components, where these proxies are measured in (high-throughput) phenotyping platforms during the growing season. Using the Agricultural Production Systems Simulator (APSIM)-wheat cropping systems model,... . The distribution of the additive quantitative trait locus effects regulating the APSIM physiological parameters approximated the same distribution of quantitative trait locus effects on real phenotypic data for yield and heading date. We use the crop growth model APSIM-wheat to simulate phenotypes in three Australian environments with contrasting water deficit patterns. The APSIM output contained the dynamics of biomass and canopy cover, plus yield at the end of the growing season. Each water deficit pattern triggered different adaptive mechanisms and the impact of component traits differed between drought scenarios. We evaluated multiple phenotyping schedules by adding plot and measurement error to the dynamics of biomass and canopy cover. We used these trait dynamics to fit parametric models and P-splines to extract parameters with a larger heritability than the phenotypes at individual time points. We used those parameters in multi-trait prediction models for final yield. The combined use of crop growth models and multi-trait genomic prediction models provides a procedure to assess the efficiency of phenotyping strategies and compare methods to model trait dynamics. It also allows us to quantify the impact of yield components on yield prediction accuracy even in different environment types. In scenarios with mild or no water stress, yield prediction accuracy benefitted from including biomass and green canopy cover parameters. The advantage of the multi-trait model was smaller for the early-drought scenario, due to the reduced correlation between the secondary and the target trait. Therefore, multi-trait genomic prediction models for yield require scenario-specific correlated traits."

#plantbreeding
https://lnkd.in/dtJC3-UN

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