April 3, 2023 at 4:09 pm | Updated April 3, 2023 at 4:09 pm | 9 min read
Agriculture 4.0, with a focus on precision agriculture, is data-driven. Decisions in agriculture are made based on data collection through advanced technology and precise analysis incorporating the latest scientific models. The data is collected from multiple sources, farms, remotely sensed imagery, and third-party sources.
Researchers and agtech providers need software to analyze the vast data collected in different formats. Software, which also forms part of Big Data, can help stakeholders with updated and various analytical tools. This article lists websites that guide people to open-access and commercial software useful for agtech and plant research.
It is a website started by scientists Lobet G., Draye X., and Périlleux C., which provides software and models for plant image analysis free of cost under the Open Data Commons. The website was designed to help researchers who have to analyze plants.
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The website groups the tools into image software, image datasets, and plant crop models. The developers of the software are from different universities around the world.
The 181 software tools are designed for different computer operating systems and could have three automation levels- fully automated, semi-automated, and manual. Plant parts analyzed are comprehensive and include the plant, canopy, cell, flower, leaf, root, fruit, seed, shoot, single, root, hypocotyl, and fungi. The 19 measurements include height, color, growth, diseases, angle, gravitropism, fluorescence, and anatomy. Other measurements include data analysis, visualization, count, curvature, and damage.
Figure 1: Example of datasets provided by Quantitative Plant.org. (Image credits: https://www.quantitative-plant.org/)
The 31 data sets include images organized under plant part- plant, root system, single root, flower, leaf, fruit, pollen, and rosette; see Figure 1. Information on fourteen species is included.
The 101 crop and plant models are classified depending on the model category, plant part, program, license, species, and model simulations.
2. Penn State – Open Access Software for Scientists
A Penn State Department of Plant Science website reviews free software supported on many open science platforms. These include software to help fresh and experienced ecological researchers in data entry, statistical analysis, literature review, writing, graphics, and communication. Though free, the software is top quality and comparable to commercial alternatives. The free software, the application, the platforms, and the commercial software they replace are listed in Table 1.
Table 1: Free software that can help researchers. (Credits: https://plantscience.psu.edu/research/labs/roots/methods/computer/opensoftware)
|Ubuntu||Operating system||Windows and OS X|
|LibreOffice||Word processor, spreadsheets, presentations||Microsoft Office||Linux, OS X, Windows|
|R and RStudio||Statistics and graphics||SAS, SPSS, etc.||Linux, OS X, Windows|
|Mendeley Desktop||Reference manager||Endnote||Linux, OS X, Windows|
|GIMP||Bitmap image manipulation||Photoshop||Linux, OS X, Windows|
|Inkscape||Vector graphics creation and manipulation||Illustrator||Linux, OS X, Windows|
|ImageJ||Image measurements||Linux, OS X, Windows|
|QGIS||Geographic information systems||ArcGIS||Linux, OS X, Windows|
3. Tools from Mccormick Lab
Alistair McCormick’s Lab at the Institute of Molecular Plant Sciences, School of Biological Sciences, University of Edinburgh, studies photosynthesis in micro-algae and higher plants using biochemical and physiological approaches. The group uses Plant Engineering Biology principles that design, construct, and incorporate biological parts into microbes.
Figure 2: “Image data of pyrenoids in Chlamydomonas and proto-pyrenoid condensates in higher plant chloroplasts,” Mccormick Lab. (Image credits:https://mccormick.bio.ed.ac.uk/tools)
The Lab shares its research software and tools for everyone to use through their website. The tools include,
- Plant Imaging data from various publications.
- Plant phenotyping tools that contain image capture systems and software source code for morphology and growth of rosette-shaped plants.
- Cyanobacteria: synthetic biology tools such as plasmids, which McCormick Lab supplies.
GrowBot is a project which aims to develop light and low-volume robots that can anchor, negotiate voids, and climb inspired by climbing plants’ move-by-growing abilities.
The scientists observe various aspects of climbing plants and prepare mathematical models to replicate the plant decision-making process in response to environmental stimuli, understand communication pathways, and the growth of plants. Once ready, the robot will have sensors and communication systems powered by biological batteries. The scientists hope the green robots can be used on construction sites, search for disaster survivors, and do archeological and environmental research.
The toolkit for plant investigation is shared on the website and includes the following:
- Plant Image Analysis Software
- Digital Plat atlas, which is a collection of atlases and handbooks.
- NCBI genome database with over 400 plant genomes.
- EnsemblPlants with sequenced genomes of selected plants, viruses, metazoa, protists, fungi, and bacteria.
- Gramene has data on comparative functional genomics
- Plant Genome DataBase Japan is a website with information on models and crop plants.
- PlantsDB is a database “for integrative and comparative plant genome research.”
- Plaza is an online resource for comparative genomics.
- Arabidopsis Information Resource (TAIR) is a database of Arabidopsis
- PlantGDB, which consists of resources and tools for plant genomics.
Rutgers University Libraries has a website with botany and plant systematics research resources. The systematics plant science software listed on the website includes the following:
- Delta (DEscription Language for TAxonomy) encodes taxonomy descriptions, including cladistic or phenetic classifications for computer processing.
- MacClade by Maddison & Maddison is a computer program focusing on phylogenetic analysis and character evolution. It also has tools for entering and editing phylogenies and data and making tree diagrams and charts.
- PHYLIP by J. Felsenstein is a program for inferring phylogenies.
- Sequin is a software tool developed by the NCBI. It helps “submit and update entries to the GenBank sequence database.”
- MAFFT (Multiple Alignment using Fast Fourier Transform) is a multiple sequence alignment program.
- MUSCLE (MUltiple Sequence Comparison by Log- Expectation) is more accurate and faster than software such as ClustalW2 or T-Coffee.
- Mesquite is a modular software that can help evolutionary biologists organize and analyze comparative data of organisms.
- RAxML (Randomized Axelerated Maximum Likelihood) is a program for significant phylogenies inference.
- CyVerse (formerly iPlant) designs and supplies cyberinfrastructure for life sciences research.
The US Department of Agriculture provides free downloads of plant science software for agricultural research, farm operations, and resource conservation.
The models cover a wide range of themes like water management, watershed research, water efficiency, salinity research, irrigation, hydrology, soils, biocontrol, crop production models, economics, bees, genetic algorithms, germplasm testing, nitrogen index tool, rangeland resources and systems research, stored products insects and engineering research, great plains research, grazing lands, hydraulic engineering, conservation, cropping systems, wind and soil erosion, food animal environmental systems, forage-animal production, application technology, dairy forage, horticultural research, epidemiology, genetics, plant resistance, aquaculture, market quality, food composition, remote sensing, and pasture systems.
The models can be species-specific (like cotton, sugarbeet, etc.), based on categories like seed and forage.
7. Top Statistical Software Packages for Agricultural Research
The Business Complier lists many free and commercial statistical software for general analysis, whereas others are designed specifically for agricultural research. The software tools are for agricultural data collection, experimental designs, sampling methods, and data analysis. The software supports several languages and is available in desktop and mobile versions.
The field data collection software tools are FieldLAb, ODK Collect, and MAgpi+
Agricultural experiment design and data analysis software tools are – R, Statistical Tool for Agricultural Research (STAR), Plant Breeding Tools (PBTools), Statistical Package for Animal Breeding (SPAB), CropStat, Statistical Package for Augmented Design (SPAD), Statistical Package for Balanced Incomplete Block Designs, Software for Survey Data Analysis (SSDA), JMP, SPSS, Develve, InvivoStat, SAS, Minitab, GraphPad Prism, and Statistica.
8. Top 9 Farm Management Software
Farm management software helps growers manage farming as a business. Several commercial options exist and can be used with devices like desktops, mobile, tablets, and iPad.
Growers can use the software to manage and optimize daily operations and schedules, planning, budgeting, record keeping, data storage, and farm monitoring and analysis. Growers could develop crop plans, forecast profits, track and measure farm activities, and manage risk portfolios.
The top farm management software providers listed on the website are Agrivi, Agworld, AgriWebb, Conservis, FarmLogs, FarmERP, Granular, and Trimble.
9. Scientific Review of 34 Studies
A 2017 scientific paper by Kamilaris, Kartakoullis, and Boldú has reviewed 34 studies on Big Data analysis in agriculture. The paper covers the problems, solutions, tools, algorithms, nature of big data, and scale of the software used in Big Data analysis.
Though Big Data applications in agriculture are just starting, many software and hardware, techniques, and methods for data analysis already exist. There is also an increasing tendency to provide open access to software to make them immediately beneficial to research, business ventures, and the public sector. They have categorized the software tools into nine groups listed in Table 2.
Table 2: “Common software tools used for big data analysis in agriculture,” Kamilaris et al. 2017. (Credits: https://doi.org/10.1016/j.compag.2017.09.037)
EOS Data Analytics partners with government, scientific, and commercial organizations to provide geospatial analytics for agriculture, forestry, and land viewing.
According to EOS, there are 50 software products on the market for agricultural analysis for various purposes.
- Farm management which covers crop management, finance and enterprise management, and enterprise resource planning, makes up 52 percent of the tools.
- Precision agriculture and predictive analytics account for 12 percent of the tools.
- Field monitoring and sensors for plant growth, soil, irrigation, weather, stress, and pest control cover 10 percent of software.
- Platforms for data aggregation use seven percent of the tools.
- Platforms that analyze geospatial data account for seven percent of the software tools.
- Spatial imagery and big data analytics processing spatial images account for four percent.
- Scouting software makes up two percent of the tools.
- The rest, or 6 percent of analytical tools, are for remote sensors, infield hardware, and software for robots and drones.
The website lists the most popular software: FarmLogs, Climate Fieldview, Farmers Edge, Agrian, Trimble, Agrivi, Granular, Farmshots, Strider, Proagrica, AgriEdge, and EOSDA Crop Monitoring.
The Cornell University Library provides a guide for agricultural data users that lists tools for finding, analyzing, and working with data on agriculture and food. The 24 software were developed by various third parties and is for researchers, the public, and non-profits. Some of the listed resources are only for Cornell University members.
- Community Commons has data to develop mapping and reporting capabilities to cover community health.
- The Community Platform helps communities and non-profits combine data with maps.
- DataFerrett is a data extraction and analysis tool that uses federal, state, and local data.
- DataUp is a free tool for researchers to document, manage, and store tabular data.
- Debategraph is a web-based, interactive visualization tool for brainstorming.
- Economic Profile System –Human Dimensions Toolkit is a free easy-to-use software application for Excel to make socio-economic reports.
- Free GIS Tools from Mann Library come from its CUGIR repository site.
- Google has several tools for producing, sharing, and using data, including Fusion tables, Google Apps, Charts, and Maps Engine.
- IMPLAN data, tools, and services can assess the economic impacts of local food systems.
- org‘s tools are for mapping regional and local food systems.
- New Venture Advisors Toolsite is for people with a food business or conducting food system assessments.
- OpenRefine is a free tool for cleaning, transforming, and combining messy data from one format to another.
- Progressive Agricultural Rankings is a tool for agricultural and food system practitioners.
- Silk helps create interactive websites to answer visitors’ questions supported by data.
- SimplyMap is a web-based mapping application for making illustrative maps and reports using United States data.
- Social Explorer is an online research tool to access census and demographic data to visualize and understand social and demographic changes throughout history.
- The SoilWeb: An Online Soil Survey Browser allows access to soil survey data in 48 US states.
- Tableau Public is a free tool for creating interactive data-driven narratives online.
- com has a “list of visualization resources.”
- Weave is a web-based platform to visualize any data.
Advancing Ag Research AgTech
The software converts science into usable products for the general public, policymakers, non-profits, ag tech providers, and users. We have long recognized software analytics’s value at Felix Instruments Applied Food Science and CID Bio-Science Inc. The NIR spectroscopy-based quality meters provide data and a basic model, which the scientific community has used to create new models for more species and cultivars. The software, especially the open access tools, offers the results of the latest modern research findings and technological advances to solve many of our challenges, like food security, climate change, and natural resource management.
Admin. (2022, May 3). Top statistical software packages for agricultural research. Business Compiler. Retrieved from https://www.businesscompilerng.com/2022/03/statistical-software-packages-for.html
A list of tools for plant investigation and analysis to know. (n.d.). Retrieved from https://growbot.eu/community/tools-for-plant-investigation
Imanuel. (2022, April 21). Top 9 farm management software in 2022 – reviews, features, pricing, comparison. PAT RESEARCH: B2B Reviews, Buying Guides & Best Practices. Retrieved from https://www.predictiveanalyticstoday.com/top-farm-management-software/
Kamilaris, A., Kartakoullis, A., & Prenafeta-Boldú, F. X. (2017). A review on the practice of Big Data Analysis in agriculture. Computers and Electronics in Agriculture, 143, 23–37. https://doi.org/10.1016/j.compag.2017.09.037
LibGuides: Agriculture Data Users Guide: Data Tools. Data Tools – Agriculture Data Users Guide – LibGuides at Cornell University. (n.d.). Retrieved from https://guides.library.cornell.edu/ag-food-data-guide/ag-food-data-tools
Open access software for scientists. Plone site. (n.d.). Retrieved from https://plantscience.psu.edu/research/labs/roots/methods/computer/opensoftware
Quantitative Plant | About. (n.d.). Retrieved from https://www.quantitative-plant.org/about
Research guides: Botany & Plant Sciences: Systematics Software. Systematics Software – Botany & Plant Sciences – Research Guides at Rutgers University. (n.d.). Retrieved March 25, 2023, from https://libguides.rutgers.edu/botany/Software
Software: USDA ARS. (n.d.). Retrieved from https://www.ars.usda.gov/research/software/
Tools. Tools | McCormick Lab. (n.d.). Retrieved from https://mccormick.bio.ed.ac.uk/tools
Top Farm Management software for successful agriculture. EOS Data Analytics. (2023, March 6). Retrieved from https://eos.com/blog/farm-management-software-is-a-key-to-successful-farming/
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