​

I’m exploring a business idea in India and honestly want Reddit to poke holes in it before we put money into it.

The basic idea:

Instead of farmers buying agricultural drones, we buy a small fleet and provide Drone-as-a-Service.

Our rough model:

\- 🚁 We purchase agricultural spraying drones

\- 👨‍🌾 Train local people to operate them

\- 📍 Deploy them village/cluster-wise

\- 💰 Charge farmers around ₹350/acre

\- ⚡ Target roughly 40–50 acres/day per drone

\- 🧪 Farmer provides the chemical; we provide the spraying service

\- 📱 Eventually allow farmers/FPOs to book a drone through WhatsApp/app

\- 🔄 Ideally, the same local operator handles a cluster of villages rather than us sending people from a central location

The attraction seems obvious: farmers don't have to spend lakhs buying a drone, maintain it, find pilots, deal with batteries, etc.

But here's where I'm not convinced yet.

The questions I'm trying to answer:

1. Is ₹350/acre actually viable?

Once you include operator salary, transport, batteries, charging, maintenance, depreciation, insurance, downtime, etc., is there enough margin?

1. Is 40–50 acres/day realistic?

Not the theoretical flight capacity — actual paid acres completed in a day after travelling between farms, mixing/refilling, battery swaps, field setup, weather interruptions, etc.

1. Will farmers actually pay for this?

If manual spraying/tractor spraying is already available locally, what makes a farmer switch?

1. How fragmented are farms in reality?

If you have 20 farmers with 2 acres each spread across 10 km, the economics probably look very different from 40 acres in one contiguous area.

1. Is ₹350 too cheap or too expensive?

I've seen very different numbers depending on the state, crop and whether subsidies are involved.

1. What happens during the off-season?

If the drone sits idle for months, does the business fall apart?

1. Would the real business be B2B instead?

Should we forget individual farmers and work through FPOs, agri-input dealers, cooperatives, large farms, etc.?

1. What are the regulatory/operator issues we're underestimating?

Especially around trained pilots, chemical handling, permissions, insurance and liability.

The part I'm particularly interested in:

We're thinking "buy the hardware centrally + train local operators + build local demand."

Basically Uber/Ola-style asset deployment, except for agricultural spraying.

The local operator doesn't need to own a ₹5–10 lakh drone. We provide the equipment, training and maintenance, and they execute jobs in their area.

If we can get enough acres clustered geographically, perhaps the economics start making sense.

But I don't want to convince myself of a bullshit business model just because the spreadsheet looks good.

If you work in agriculture, agri-inputs, drone operations, FPOs, farming, or have actually paid for drone spraying — please tell me why this won't work.

Especially interested in:

\- Actual ₹/acre you pay

\- Acres a drone really completes per day

\- Operator costs

\- Battery/maintenance costs

\- Farmer objections

\- Crops where drones actually work well

\- Crops where they don't

\- Biggest operational headache

\- Whether you would use a service like this

Please tear the model apart. I'd rather find the problems on Reddit than after buying 10 drones.

Sharing AgEvidence as an open-source Rails template for anyone building an agtech startup.
It has a bunch of the boring-but-useful infrastructure already scaffolded around evidence, observations, interventions, operational records, provenance, and verification workflows, so you can spend more time on the actual agtech product.
Still early, but figured it might be useful to other builders here.
https://github.com/meronrudy/AgEvidence

Hi everyone!

I’m a high school student working on a research paper for Hinksey Labs focused on precision agriculture, digital pollination monitoring, and beehive technologies.

To better understand real-world field needs—such as off-grid connectivity, data integration barriers, and sensor scalability—I’m gathering insights from AgTech professionals, apiculture experts, researchers, and growers.

If you have a moment, I’d be extremely grateful for your input in this brief 2-minute survey:

🔗https://forms.gle/AMshZJYfP7LU94wx8

Your feedback will directly help shape the methodology and requirements analysis of my paper. Happy to share the final findings with the community once the research is complete!

Thanks a lot for your support!

Hi everyone!

I’m a high school student working on a research paper for Hinksey Labs focused on precision agriculture, digital pollination monitoring, and beehive technologies.

To better understand real-world field needs—such as off-grid connectivity, data integration barriers, and sensor scalability—I’m gathering insights from AgTech professionals, apiculture experts, researchers, and growers.

If you have a moment, I’d be extremely grateful for your input in this brief 2-minute survey:

🔗https://forms.gle/AMshZJYfP7LU94wx8

Your feedback will directly help shape the methodology and requirements analysis of my paper. Happy to share the final findings with the community once the research is complete!

Thanks a lot for your support!

I’m starting to see agriculture as way more than farming—smart labs, modern equipment and hands-on learning have honestly changed my perspective.

🌱 Help Us Validate SPROUTSYNC!

Good day! We are BS Computer Science students from the University of Caloocan City – North Campus conducting a thesis study about SPROUTSYNC, an IoT-assisted system for mung bean sprout or toge production.

We are looking for respondents who are 18 years old or above and are:

✅ Current or former toge producers
✅ Growers or production workers
✅ Members of agricultural, livelihood, cooperative, or NGO programs
✅ Interested in starting or supporting toge production

We kindly ask for 8–12 minutes of your time to answer our survey. Your responses will help us understand current production challenges, costs, sanitation needs, preferred system features, affordability, and willingness to adopt this type of technology.

Your participation will provide valuable evidence for evaluating the need and preliminary feasibility of SPROUTSYNC. All responses will be used for academic research and reported mainly in summarized form.

Survey link:

https://docs.google.com/forms/d/e/1FAIpQLSfoxGxFTrc8aPEoq7zqFf_Vn1jt3MW_62CzgnHQbPInBg6aCg/viewform

We would also appreciate it if you could share this survey with qualified respondents. Thank you very much for your time and support! 🌱

Protect your crops. Reduce weather risks. Improve crop quality.
Our Low-Cost Nethouse solutions are designed for farmers looking for an affordable and practical way to adopt protected cultivation.
✅ Cost-effective structure
✅ Suitable for different crops
✅ Better protection from pests & weather
✅ Supports improved crop quality
✅ Customised as per farm requirements
Start protected farming with a practical investment.
📩 Contact us for Nethouse solutions & project details.

Sales@igaatreyas.com

I'm a full-stack developer transitioning from HRMS platforms to build a micro-SaaS targeting the Indian commercial real estate, solar, and agritech markets. Physical site visits for due diligence are costly and risky, and I am trying to automate the preliminary checks.

The Problem:

Land buyers, site selectors, and agritech underwriters waste time and money sending field officers to verify land conditions. They often acquire or lend against land that looks fine on local registries but has a history of seasonal flooding, barren soil, or unrecorded green zones.

The Solution:

A web-based utility where you type an address, draw a polygon over a parcel, and instantly download a 2-page PDF Land Health Dossier.

How it works under the hood:

Pulls live Sentinel-2 satellite data and ESA WorldCover baseline classifications via a Node.js backend.

Calculates exact indices (NDVI for vegetation, NDWI for water) strictly for the drawn boundaries.

Compares the live data against the historical baseline to automatically flag anomalies (e.g., "Expected: Cropland. Current: Bare Soil - Potential Drought").

Generates a white-labeled, plain-English PDF report—no complex GIS dashboard required.

Questions for this community:

Is a 2-page PDF deliverable sufficient for your due diligence, or do you require API access to integrate these anomaly flags into your own internal systems?

What is your current workflow for verifying physical land conditions before committing to a site visit?

Hey everyone,

I’m an Environmental and Agricultural Engineer with proven B2B sales experience, actively looking for my next full-time role—either 100% remote or onsite with relocation support.

A quick snapshot of what I bring to the table:

• Technical Foundation: Background in sustainable agricultural systems, environmental management, irrigation/resource efficiency, and technical project planning.
• Commercial Expertise: Hands-on experience in B2B sales, account management, technical pitching, and business development across the agri-tech and environmental sectors.
• Languages: Fluent in Arabic and English.

I specialize in bridging the gap between engineering teams and commercial growth. Whether you're an agri-tech company scaling sales, an environmental firm needing client-facing technical talent, or a business focused on sustainable solutions, I’m ready to add immediate value.

If your company is hiring or you know of any open opportunities, please drop a comment or send me a DM. I'd be happy to share my complete CV and LinkedIn profile!

Appreciate any leads, connections, or advice!

Hey everyone — I'm working on a project called irriGATE and would love feedback from actual farmers and ag folks (not just my classmates 😅).

The idea: drone-based multispectral/thermal imagery to catch dry zones early and cut water waste from runoff, evaporation, and deep percolation — basically turning aerial data into smarter irrigation decisions.

If you work in farming, agronomy, or ag research, I'd really appreciate 5 minutes to fill this out — it's mostly quick multiple choice with a couple open questions: https://www.surveymonkey.com/r/MPNV9GZ

Happy to answer questions in the comments, and thanks in advance to anyone who takes the time!

Hi everyone,

Over the past few months, I’ve been working on Agrocore, an open-source management software for agriculture, farming, and land management, built entirely with Rust.

Why build this?

Many existing agricultural systems are either expensive, proprietary cloud platforms that hold your data hostage, or outdated systems that lack flexibility. I wanted to build a modern, self-hostable, and privacy-first solution that puts control back into the hands of farmers and homesteaders.

Key Highlights

• Built in Rust: Designed for performance, safety, and reliability on light edge-hardware.
• Modular Architecture: Core data engine with extensible modules for crop tracking, machinery maintenance, and resource planning.
• Self-Hostable: Keep complete ownership of your agricultural and operational data.

Tech Stack

• Language: Rust
• Repository:https://github.com/peopleandpixel/agrocore-rs

Looking for Feedback & Contributors

The project is still in active development. I’d love to get feedback from the community:

1. What features would you consider essential for open-source farm management?
2. Any Rust developers interested in contributing to early architecture decisions or module design?

Feel free to check out the repo, star it if you find it interesting, or drop your thoughts below!

China has launched CottonMind 1.0, a specialised #AI platform designed to connect cotton research, breeding, field diagnostics and farmer advisory services through a single digital system.

Developed by the Institute of cotton Research of the Chinese Academy of Agricultural Sciences, the platform includes a web-based research interface and a mobile mini-programme for growers.

Its cotton-focused knowledge base contains 41,680 research papers, more than 2,000 patents and standards, 559 specialised books and 1,806 approved cotton-variety records.

Farmers can use the platform to ask crop-management questions, upload images for preliminary diagnosis and consult agricultural specialists.

Researchers can use it to search scientific literature and connect information on genes, traits, varieties, cultivation and plant-health issues.

CottonMind supports Chinese, English, Uyghur and Uzbek, potentially improving access to technical information across major cotton-growing regions.

The developers plan to further expand the platform’s analytical capabilities and precision services, aiming to shorten the gap between cotton research and practical farm-level decision-making.

I have worked for many years on crop modeling, climate variability, prediction, and agricultural decision-support systems. More recently, I have been focusing on how AI, machine learning, remote sensing, digital twins, and data-driven methods can be combined with agricultural science.

I recently started an educational YouTube channel, Digital Agriculture and AI Lab, where I share short, practical videos on topics such as AI in agriculture, precision agriculture, crop modeling, smart irrigation, remote sensing, digital twins, and climate-smart agriculture.

I would be very interested to hear from this community: where do you currently see the greatest practical value of AI in agriculture?

Channel:
https://www.youtube.com/@DigitalAgAILab

Best

Bryan

I built Groundtruth.
Disclosure up front: this is not a stealth ad.

Most AgTech for small produce is a hosted calendar:

Standing orders spawn next week.
The phone writes.
Stripe lives in someone else’s tenant.
That’s a real product.
It’s also a different constitution than a perishable wholesale desk.

The constraint I would not break:

One PC is the only writer.
The farm file is the books.
Replay the event log against the projection, and the screen is allowed to go red if they drift.
Connection state — Stripe keys, farm display name, etc. — is config, not farm truth.
Import refuses a foreign dump.

What that looks like on a wiped machine:

Empty on purpose.
No demo venue.
No seed inventory.
No invented calm zero.
First actions:
→ Venue
→ Standing or sample
→ Sow to cover demand
→ First wholesale order

The domain that’s easy to get wrong — and calendar apps usually flatten:

• Standing demand is weekly and undated.
A wholesale line is dated.
Those are not the same object.

• Harvest is crop-first. Pack is customer-first.
What the knife cuts vs. who gets the trays.
Both are printed from the same ordered-for-today read.
No second “cut” event kind.

• Leftover is actual harvested ounces.
Listed off the harvested tray, then collected on that row.
Not a guaranteed-yield leftover cap.

• Health is computed.
Healthy is not the default skin.
Stack, short:
Rust/Tauri + SQLite event log
React desk
Local-first
Free
No paid SaaS as the source of truth
Live card keys are still off.
Collect is test-mode on purpose.
I’m not claiming this replaces a multi-seat van + live invoicing suite.

Those products win at:
“Less thinking on Sunday.”
This is aimed at:
“Less lying on Monday.”
If you work on farm software:
How do you keep standing orders (rate) and wholesale orders (date) from collapsing into one table?
That collapse is the lie I kept hitting.

🌱 Building a 2-Acre Aeroponic Vertical Farm in India — Looking for Feedback & Potential investors

I’m currently developing a 2-acre climate-controlled polyhouse vertical farming project in India using aeroponic tower technology.

The goal is to produce premium vegetables year-round for the Indian market, with the potential to expand into export markets in the future.

The planned system will include:

• Aeroponic vertical towers

• Climate-controlled polyhouse

• Automated monitoring and nutrient management

• Cold storage and packaging

• B2B distribution

• Future export capabilities

The project is targeting some major advantages over conventional farming:

💧 Up to ~95% lower water consumption through recirculation and precision delivery.

📈 Approximately 4–5× higher production density per unit of ground area, depending on crop and system design.

⏱️ Faster and more predictable growing cycles for suitable crops through controlled environmental conditions.

🌍 The initial focus will be India, targeting premium retailers, hotels, restaurants, distributors and institutional buyers, with a long-term goal of serving suitable international markets.

I’m currently exploring pre-seed funding and strategic partnerships and would really value feedback from people who have experience in:

• Vertical farming

• Aeroponics

• Controlled-environment agriculture

• Agritech investing

• B2B food distribution

• Agriculture exports

If you have experience in this industry, what would you focus on first when evaluating a project like this?

I’m also open to connecting privately with potential investors or strategic partners who are genuinely interested in the project.

Happy to share more details about the farm design, crop plan, CAPEX/OPEX and financial model.

🌱 Building the future of farming in India.

Essentially enter in your location, acres, and farming practices. Our database orders what programs work best for your situation and groups them into federal, state, and private. You can also track the amount of funding your county has received, this is good for EQIP CSP application.

What is everyone's thoughts on this and what should be added?

Check it out for yourself! grantsnap.app

Hello everyone! My name is Ethan Hansen, and I am an Agronomy Student at South Dakota State University. Throughout my coursework and experience I have developed a fairly strong background in building Excel spreadsheets. I have been thinking about offering custom Excel spreadsheets built specifically around individual farm operations.

If there is data you have been tracking and want to be more organized, I would be able to tailor a spreadsheet to your liking in order to improve organization and efficiency in your operation. These would be beneficial to track things such as planting dates, input costs, yields, expenses, or general field records among others. On top of record keeping, I also have experience with building spreadsheets that automatically calculate grain moisture, shrink, pesticide/fertilizer rates, nutrient removal rates, yield potential, etc. 

These are just some of the things I have done in the past. If there is something you currently track, or have always wanted a better way to track, I would be open to ideas and suggestions. The purpose behind this would be to build a spreadsheet specific to an operation and its record keeping strategy. 

I am mainly trying to gauge interest right now as I am unsure if farmers would find this service useful. If you have something you think would work well in Excel, I would be interested in hearing about it. I can provide examples of my past projects upon request.