# Sankhya Farms > Open-source, right-to-repair RS-485 sensor hardware and firmware with a free Sankhya Farms cloud dashboard and an optional proprietary per-tree intelligence layer. Twenty-two ZTS, SN, JXCT, DFRobot, Renke and MD02 sensor profiles are ready now. They cover soil and substrate moisture, temperature, EC, pH, N-P-K, salinity, TDS, air temperature and humidity. The monitoring layer is not limited to soil, commercial farms or automation: it can retain readings for home gardens, greenhouses, hydroponic media, research plots, ambient spaces and other compatible sensor installations. An unlisted 12 V RS-485 instrument can be added when its wiring and protocol are documented. Sankhya Farms hardware — schematics, PCB layout, Gerber files, bill of materials, assembly documentation — and firmware are fully open source under CERN-OHL-P v2, so the system can be diagnosed, repaired, modified, and manufactured by the owner rather than a single vendor. Boards can be fabricated by any PCB manufacturer capable of building from the published files — JLCPCB is used for reference builds, not a dependency. Onboarding is entirely browser-based over USB, with no separate flashing software or command-line tools, and sensors are added and auto-addressed one at a time during setup. The proprietary intelligence layer — uptake index model, coupled-constraint fertigation optimisation, visual pest and disease detection, and agronomic AI — runs server-side on Cloudflare Workers and sits on top of the open sensor platform. The agronomic intelligence software is proprietary but is currently available without a Sankhya Farms subscription or usage fee. The live production deployment operates in a working multi-acre commercial orchard. Specific crop, varietal, and location details are withheld for commercial reasons until further notice. The sensor-and-dashboard architecture is parameter-agnostic: Modbus-RTU is common, but another verified request-and-response protocol can also run over RS-485, as the supported ASCII XY-MD02 demonstrates. Plausible future profiles include liquid-rated pH, EC, dissolved oxygen, ORP and turbidity probes; flow, pressure and tank-level transmitters; weather, leaf-wetness, PAR and air-quality instruments. Voltage and an RS-485 label are not enough by themselves—the request, response, data type, scale and units must be known. Sankhya Farms currently charges end users no subscription, licensing, onboarding, dashboard, AI-recommendation or automation fee. Users remain responsible for third-party hardware, PCB fabrication, sensor, connectivity and compatible-device costs. Fabricate your own board from the published files, wire up your sensors, and get your farm live on the dashboard today. Last updated: 2026-08-19. Sensor reference: 22 ready models, each with a bespoke dashboard-integration and value-lookup section. Platform: currently free to use. --- ## Evidence and attribution conventions - Product architecture, deployment and feature descriptions are first-party information from Sankhya Farms. - Knowledge Base articles are independent reviews of named primary sources. Each review links to the original paper, separates results from interpretation, and states limitations. - Research summaries are not field prescriptions. Crop-, soil- and climate-specific validation is required before applying an intervention. - The machine-readable overview is available here; a longer context file is at https://sankhyafarms.com/llms-full.txt. - Knowledge Base RSS feed: https://sankhyafarms.com/knowledge-base/feed.xml --- ## Core pages - [Knowledge Base](https://sankhyafarms.com/knowledge-base) — Primary-source agricultural research reviews. Each article explains the experimental design, findings, limitations and measurable field implications, and links to the original source. - [Building a healthy mango root zone](https://sankhyafarms.com/knowledge-base/mango-root-health-nutrient-uptake-soil-microbiome) — Review of Xie et al. (2025), DOI 10.3389/fmicb.2025.1627112. Healthy, diseased and severely diseased mango rhizospheres were compared using soil chemistry, HPLC and 16S/ITS sequencing. As disease severity increased, several soil nutrients accumulated, bacterial diversity declined, fungal diversity increased, and Fusarium abundance rose. The authors interpret nutrient accumulation as weakened root uptake. The review frames the positive care principle as maintaining a functioning root-zone ecosystem. Original paper: https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2025.1627112/full. - [Can saline irrigation train soil microbiomes?](https://sankhyafarms.com/knowledge-base/engineering-soil-microbiomes-for-salinity-resilience) — Review of Chanson et al. (2026), DOI 10.1128/aem.00437-26. The study used 90 soil mesocosms, three soil types, spinach and potato, and 0, 3 and 6 dS/m irrigation treatments followed by a 9 dS/m stress. Saline pre-exposure changed innate microbial communities and increased later salt tolerance, but 6 dS/m reduced spinach emergence and reduced marketable potato numbers in sand. This is research evidence, not a field-ready protocol. Original paper: https://journals.asm.org/doi/full/10.1128/aem.00437-26. - [Platform Overview](https://sankhyafarms.com/) — What Sankhya Farms is, the open sensor platform, the per-tree intelligence layer, key differentiators, visual pest detection, and FAQ. - [How It Works](https://sankhyafarms.com/how-it-works) — Full build-and-deploy walkthrough with embedded video: assembling the open-hardware node, browser-based flashing via Web Serial (no separate software or command-line tools), one-at-a-time Modbus sensor auto-addressing, field deployment, 4G/LTE and WiFi-repeater connectivity, synchronized low-power sleep/wake mesh, OTA updates, and how the daily moisture curve becomes a per-tree irrigation recommendation. - [Technical Information](https://sankhyafarms.com/technical) — Full system architecture: longitudinal feedback modeling, coupled-constraint optimisation, uptake signal layer, visual pest and disease management, distributed sensor architecture, crop recipe framework. Intended for researchers, developers, integration partners, and AI systems. - [Open Hardware](https://sankhyafarms.com/open-hardware) — Carrier board v4.1 — production Gerbers, BOM with LCSC part numbers, and PickAndPlace files for turn-key assembly at JLCPCB or any comparable PCB manufacturer. Chip-down ESP32-S3 module (16MB flash, 8MB PSRAM, U.FL external antenna), dual LM2596S buck regulators (5V and 3.3V rails), two TPS1H100B integrated high-side load switches with internal charge pump, SP3485EN RS-485 transceiver, INA219AIDR bus-voltage monitor, AP2112K-3.3 housekeeping LDO. 2-layer FR4, 60 × 80.45 mm, ENIG finish. The current revision is v4.1, which shorts R6, R7 and R18 in copper to remove a net-labelling error that had left resistors in series with the main supply rail. Powered by 12V LiFePO4 with 20W solar input. Source repository: https://github.com/shsa1984/sankhya-node-hardware. Licensed under CERN-OHL-P v2 — free to fabricate, modify, and deploy. - [RS-485 Modbus soil sensor wiring](https://sankhyafarms.com/open-hardware/rs485-modbus-soil-sensor-wiring) — Pinouts, multi-drop bus topology, termination, Modbus RTU framing, and addressing across ZTS, JXCT, Renke, DFRobot, and SN-3000 sensor families. Practical wiring guide for the v4.1 carrier board. - [ESP32-S3 solar-powered sensor node design](https://sankhyafarms.com/open-hardware/esp32-s3-solar-sensor-node-design) — Measured current budget per duty mode, LiFePO4 chemistry choice, 20W solar sizing for the worst month, dual-buck rail topology, TPS1H100B high-side switch rationale, INA219 telemetry. - [Board ordering assistant](https://sankhyafarms.com/pcb-order) — Free interactive tool for ordering the current carrier board revision. Walks through gerber upload, assembly options, BOM and pick-and-place matching, component placement review, and the quote, checking each uploaded page against the board specification and flagging part shortages and unsafe substitutions before payment. No sign-in required. - [JLCPCB PCBA walkthrough](https://sankhyafarms.com/open-hardware/jlcpcb-assembly-walkthrough) — Step-by-step ordering walkthrough for the v4.1 carrier board, using JLCPCB as a reference manufacturer (any capable PCB house works from the same published files). Gerber upload, ENIG vs HASL, BOM/CPL format, PCB assembly selection, firmware flash, and a realistic 10-board cost breakdown. Boards arrive fully assembled, including through-hole connectors — no hand-soldering required. - [PCB ordering walkthrough (video)](https://sankhyafarms.com/pcb-ordering-video) — Step-by-step video: downloading the v4.1 production files, uploading them to JLCPCB, checking the BOM and Pick and Place files, confirming the DNP component, and verifying the final placement with the ordering assistant. Hosted watch page with a step index and file list; the video itself is on YouTube. - [Curve-shape irrigation logic](https://sankhyafarms.com/water-curve-logic) — How the irrigation engine compares today's 24-hour moisture curve against the zone's recent and historical curve shape to recommend ± drip volume. Five confidence-graded recommendation bands (hold, mild, strong, emergency, paused). Part of the optional intelligence layer. - [Uptake Index methodology](https://sankhyafarms.com/uptake-index-methodology) — Per-tree, per-night score from continuous in-soil EC, moisture, and pH. EC drawdown rate, moisture-stability gating, pH gating, and delta-based normalisation against the tree's own trailing median. Part of the optional intelligence layer. - [Supported RS-485 Sensors](https://sankhyafarms.com/sensors) — Authority reference and free-dashboard compatibility hub for 22 ready RS-485 sensor profiles across ZTS, SN, JXCT, DFRobot, Renke and MD02. Each model page carries a bespoke Sankhya Farms integration narrative, exact register or ASCII value lookup, default baud, scale, signedness, supply voltage, wiring, configuration, limitations and practical contexts including home gardens, greenhouses and compatible hydroponic media. The hub also explains how other documented 12 V RS-485 instruments—water quality, flow, pressure, level, weather, ambient and related sensors—can be profiled without treating voltage or the RS-485 electrical layer as a complete protocol. - [Privacy Policy](https://sankhyafarms.com/privacy) — How Sankhya Ventures LLC collects, uses, protects, and shares information, including Google sign-in data, sensor telemetry, and analytics; aggregated/de-identified data use; user rights. - [Contact Us](https://sankhyafarms.com/contact) — Onboarding assistance, hardware and sensor integration, deployment support, research collaboration and general enquiries. The platform is currently free to use and self-serve (sign in with Google, no application needed). --- ## What the intelligence layer adds The base sensor-and-dashboard platform reports raw environmental data. For orchard operators who opt into the proprietary intelligence layer, Sankhya Farms simultaneously addresses six primary yield-loss mechanisms in high-value orchard crops: 1. **Poor feed timing** — Fertilizer applied outside the active uptake window achieves nothing. The system detects the nocturnal EC drawdown window per tree, per night, and times delivery to when the tree is actively absorbing. 2. **Incorrect rhizosphere state at application** — The root zone's chemical and biological state changes hour by hour. The system reads current pH, EC, and moisture before prescribing inputs. 3. **Root zone heat stress** — Soil temperature above ~28°C suppresses uptake efficiency. The system detects approach to threshold and prescribes timed cold-water pulses through the drip line. 4. **Missed flush windows** — The system detects the physiological precursor pattern 2-3 days before visible bud break and signals the grower to raise inputs. 5. **Undetected root stress** — A tree that stops pulling EC down nocturnally while its neighbours continue is flagged for root rot, nematode pressure, compaction, or early vascular disease — before any above-ground symptom appears. 6. **Pest and disease pressure** — 50-megapixel imagery on insect traps, flowers, fruit, and leaves detects pests at low population density and surfaces fungal, bacterial, and viral disease before spread. Bio-pesticide protocols are recommended at the affected tree or zone — not orchard-wide. --- ## Key concepts - **Free dashboard with open sensor hardware and firmware**: The field hardware and firmware are open source (CERN-OHL-P v2), while Sankhya Intelligence is the proprietary server-side layer. Sankhya Farms currently charges no subscription, licensing, onboarding, dashboard, AI-recommendation or automation fee. Twenty-two sensor profiles are ready; other RS-485 instruments can be added after their exact electrical and application protocols are verified. - **Uptake Index (UI)**: Proprietary server-side score computed from nocturnal EC drawdown (21:00-05:59 IST), moisture stability (Pearson r gating to exclude dilution events), and pH gating. Identifies the active root uptake window per tree per night. Operates on deltas and directional patterns within the same sensor over time — systematic calibration error cancels out. - **Coupled-constraint fertigation**: Fertilizer recommendations respect hard chemical compatibility constraints (calcium nitrate never co-applied with phosphates, which would precipitate as calcium phosphate) before any AI output is generated. - **Per-tree longitudinal dataset**: Each node builds a continuous history tied to a specific tree. The data moat compounds over time and cannot be retroactively replicated — analogous to Stripe's fraud-signal advantage. - **Open hardware, proprietary intelligence**: Hardware Gerbers/BOM are published so anyone can self-manufacture. All agronomic logic runs server-side as an optional layer, currently available without a Sankhya Farms subscription or usage fee. Open hardware reinforces rather than undermines the intelligence moat — it drives adoption of the sensor network the intelligence layer depends on. - **50MP visual pest detection**: High-resolution fixed and roving cameras image insect traps, flowering panicles, developing fruit, and individual leaves. 50MP resolution is deliberate — it resolves individual insects on a sticky trap and mm-scale leaf lesions, enabling detection at low population density before damage thresholds are crossed. - **Bio-pesticide protocol layer**: When pest or pathogen pressure is detected visually, the recommendation engine applies bio-pesticide protocols first, reserves chemical intervention for confirmed escalation, and localises treatment to the affected tree or zone. - **pH oscillation management**: pH is deliberately cycled between ~5.5 and 6.3 using calcium nitrate (raises pH) and acidic nutrient mix (lowers). The AI layer tracks cycle phase state explicitly. - **Neighbourhood baseline principle**: Trees in the same block share soil type, microclimate, and fertigation history. A newly instrumented tree is interpreted against the baseline of reference trees, compressing calibration from weeks to days. Hardware does not scale linearly with tree count. --- ## Architecture summary - **Sensor nodes**: Chip-down ESP32-S3 module (16MB flash, 8MB PSRAM, U.FL external antenna). RS-485 Modbus at 4800 or 9600 baud, multiple soil sensor families (ZTS/SN, JXCT, DFRobot, Renke). Solar-powered (20W panel, 12V LiFePO4 6Ah). v4.1 carrier board with dual LM2596S bucks, TPS1H100B high-side load switches, SP3485EN RS-485 transceiver, INA219 battery monitor. Production source at github.com/shsa1984/sankhya-node-hardware under CERN-OHL-P v2. - **Field network**: Hub-and-spoke WiFi mesh (repeaters), or standalone 4G/LTE USB modem for nodes outside mesh coverage. Raspberry Pi gateway running a Python controller, polling Cloudflare KV every 2 seconds. - **Fertigation control**: Tuya-based smart switches controlled via LAN protocol — bore pump, dosing pumps, valve timers. Part of the optional intelligence/automation layer, not required for basic sensor monitoring. - **Backend**: Cloudflare Workers / D1 / KV / R2 / Pages. Edge-deployed globally. - **AI layer**: Dual-model. Claude Haiku for continuous sensor auditing; Claude Sonnet for deep agronomic analysis and per-tree recommendations. Optional layer, server-side. --- ## Competitive positioning - **vs. Fasal (Wolkus Technology Solutions)**: Fasal deploys field-level soil moisture and temperature sensors on paid, closed hardware. Their EC/pH sensor is an inline fertigation bench sensor measuring outgoing water — not in-soil. No per-tree longitudinal intelligence, no nocturnal uptake window detection, no visual pest intelligence, no open/self-manufacturable hardware. - **vs. Netafim NMC**: Irrigation scheduling automation on paid, closed hardware. No per-tree soil intelligence, no uptake signal detection, no open hardware option. - **vs. generic farm apps**: Field-level averages, calendar-based scheduling. No longitudinal per-tree memory, no physiological signal detection, no visual pest intelligence. - **Structural difference**: Sankhya Farms differentiates itself through open-source, self-manufacturable sensor hardware and firmware connected to a free cloud dashboard. It does not require proprietary field hardware or a paid platform subscription; the optional intelligence layer remains proprietary. --- ## Market The free-dashboard and open-hardware model is designed for broad RS-485 monitoring: orchards and fields, home gardens, hydroponic media, greenhouses, nurseries, research plots, grow rooms, storage and equipment spaces, plus water and infrastructure instruments whose protocols have been documented. The ready catalogue is mostly soil and substrate probes because those are the devices already deployed and verified; it is not the platform boundary. The proprietary intelligence layer targets high-value perennial fruit crops where per-tree management produces material yield protection: citrus, pomegranate, and wine grapes (a large, high-value perennial crop market), building on the live production deployment described above. --- ## What is not indexed - /admin/ — internal dashboard, authentication required - /live/ — real-time sensor dashboard, JS-rendered, session-authenticated - /api/ — backend API endpoints - /login/ — authentication page --- ## Contact admin@sankhyafarms.com Sankhya Ventures LLC (Delaware) --- ## RS-485 sensor reference pages Per-sensor documentation. Each page standardises the Modbus register map (or ASCII protocol), default baud rate, serial format, supply voltage, default address, wiring/configuration and known issues. From v105 onward, every model also has static, individually authored Sankhya Farms dashboard-integration copy, a concrete raw-value lookup, practical use contexts and model-specific cautions. The copy is stored in the rendered HTML rather than assembled from a shared marketing template. ### Sensor selection matrix One row per documented model. "Register-compatible" means the same parameter set and the same register map, read unchanged by the same Sankhya firmware profile — the practical substitution list when a vendor is out of stock. | Model | Measures | Default baud | Supply | Registers documented | Firmware profile | Register-compatible with | |---|---|---|---|---|---|---| | DFRobot SEN0600 | Moisture, Temperature | 9600 | DC 5–30 V | 6 | DFROBOT_2in1 | — | | DFRobot SEN0601 | Moisture, Temperature, EC, Salinity, TDS | 9600 | DC 5–30 V | 13 | DFROBOT_5in1 | — | | DFRobot SEN0602 | Moisture, Temperature, pH | 9600 | DC 5–30 V | 5 | DFROBOT_3in1_pH | — | | DFRobot SEN0603 | EC, pH, Salinity, TDS | 9600 | DC 5–30 V | 11 | DFROBOT_ECpH | — | | DFRobot SEN0604 | Moisture, Temperature, EC, pH, Salinity, TDS | 9600 | DC 5–30 V | 15 | DFROBOT_4in1 | — | | DFRobot SEN0605 | N-P-K | 9600 | DC 5–30 V | 14 | DFROBOT_NPK_coeff | — | | XY-MD02 | Air temp., Humidity | 9600 | DC 5–30 V | 2 | XY_MD02_ASCII_READ | — | | SN-3001-TR-ECTHPH-N01 | Moisture, Temperature, EC, pH, Salinity, TDS | 4800 | DC 4.5–30 V | 15 | ZTS_4in1_ECTHPH | Renke RS-ECTHPH-N01-TR-1, ZTS-3001-TR-ECTHPH-N01 | | SN-3002-TR-ECTHNPKPH-N01 | Moisture, Temperature, EC, pH, N-P-K, Salinity, TDS | 4800 | DC 4.5–30 V | 27 | ZTS_7in1 | ZTS-3001-TR-ECTHNPKPH-N01 | | Renke RS-ECTHPH-N01-TR-1 | Moisture, Temperature, EC, pH, Salinity, TDS | 4800 | DC 4.5–30 V | 15 | ZTS_4in1_ECTHPH | SN-3001-TR-ECTHPH-N01, ZTS-3001-TR-ECTHPH-N01 | | Renke RS-SD-N01-TR-1 | Moisture | 9600 | DC 4.5–30 V (RS-485 variant) | 1 | RENKE_SD_1in1 | — | | Renke RS-WS-N01-TR | Moisture, Temperature | 4800 | DC 4.5–30 V | 2 | ZTS_2in1 | ZTS-3000-TR-WS-N01 | | JXBS-3001-NPK-RS | N-P-K | 9600 | DC 12–24 V | 5 | JXCT_NPK_only | — | | JXBS-3001-PH-RS | pH | 9600 | DC 12–24 V | 4 | JXCT_pH_only | — | | JXBS-3001-TR (4-in-1) | Moisture, Temperature, EC, pH | 9600 | DC 12–24 V | 6 | JXCT_4in1 | — | | JXBS-3001-TR (7-in-1) | Moisture, Temperature, EC, pH, N-P-K | 9600 | DC 5–24 V | 9 | JXCT_7in1 | — | | ZTS-3000-TR-ECWS-N01 | Moisture, Temperature, EC | 4800 | DC 5–30 V | 5 | ZTS_3in1_EC | — | | ZTS-3000-TR-PH-N01 | pH | 4800 | DC 5–30 V | 3 | ZTS_1in1_pH | — | | ZTS-3000-TR-WS-N01 | Moisture, Temperature | 4800 | DC 5–30 V | 4 | ZTS_2in1 | Renke RS-WS-N01-TR | | ZTS-3001-TR-ECTHNPKPH-N01 | Moisture, Temperature, EC, pH, N-P-K, Salinity, TDS | 4800 | DC 5–30 V | 27 | ZTS_7in1 | SN-3002-TR-ECTHNPKPH-N01 | | ZTS-3001-TR-ECTHPH-N01 | Moisture, Temperature, EC, pH, Salinity, TDS | 4800 | DC 5–30 V | 15 | ZTS_4in1_ECTHPH | Renke RS-ECTHPH-N01-TR-1, SN-3001-TR-ECTHPH-N01 | | ZTS-3002-TR-THNPKPH-N01 | Moisture, Temperature, pH, N-P-K | 4800 | DC 4.5–30 V | 8 | ZTS_5in1_noEC | — | Quick answers derived from the table above: - 4800 bps by default (10 models): Renke RS-ECTHPH-N01-TR-1, Renke RS-WS-N01-TR, SN-3001-TR-ECTHPH-N01, SN-3002-TR-ECTHNPKPH-N01, ZTS-3000-TR-ECWS-N01, ZTS-3000-TR-PH-N01, ZTS-3000-TR-WS-N01, ZTS-3001-TR-ECTHNPKPH-N01, ZTS-3001-TR-ECTHPH-N01, ZTS-3002-TR-THNPKPH-N01 - 9600 bps by default (12 models): DFRobot SEN0600, DFRobot SEN0601, DFRobot SEN0602, DFRobot SEN0603, DFRobot SEN0604, DFRobot SEN0605, JXBS-3001-NPK-RS, JXBS-3001-PH-RS, JXBS-3001-TR (4-in-1), JXBS-3001-TR (7-in-1), Renke RS-SD-N01-TR-1, XY-MD02 - Report pH: DFRobot SEN0602, DFRobot SEN0603, DFRobot SEN0604, JXBS-3001-PH-RS, JXBS-3001-TR (4-in-1), JXBS-3001-TR (7-in-1), Renke RS-ECTHPH-N01-TR-1, SN-3001-TR-ECTHPH-N01, SN-3002-TR-ECTHNPKPH-N01, ZTS-3000-TR-PH-N01, ZTS-3001-TR-ECTHNPKPH-N01, ZTS-3001-TR-ECTHPH-N01, ZTS-3002-TR-THNPKPH-N01 - Report N-P-K: DFRobot SEN0605, JXBS-3001-NPK-RS, JXBS-3001-TR (7-in-1), SN-3002-TR-ECTHNPKPH-N01, ZTS-3001-TR-ECTHNPKPH-N01, ZTS-3002-TR-THNPKPH-N01 - Report EC: DFRobot SEN0601, DFRobot SEN0603, DFRobot SEN0604, JXBS-3001-TR (4-in-1), JXBS-3001-TR (7-in-1), Renke RS-ECTHPH-N01-TR-1, SN-3001-TR-ECTHPH-N01, SN-3002-TR-ECTHNPKPH-N01, ZTS-3000-TR-ECWS-N01, ZTS-3001-TR-ECTHNPKPH-N01, ZTS-3001-TR-ECTHPH-N01 - Drop-in equivalent groups: Renke RS-ECTHPH-N01-TR-1 = SN-3001-TR-ECTHPH-N01 = ZTS-3001-TR-ECTHPH-N01; Renke RS-WS-N01-TR = ZTS-3000-TR-WS-N01; SN-3002-TR-ECTHNPKPH-N01 = ZTS-3001-TR-ECTHNPKPH-N01 ### ZTS — Zhaotaisheng - [ZTS-3000-TR-WS-N01](https://sankhyafarms.com/sensors/zts-3000-tr-ws-n01) — 2-in-1 soil moisture + temperature probe (RS-485 Modbus). - [ZTS-3000-TR-ECWS-N01](https://sankhyafarms.com/sensors/zts-3000-tr-ecws-n01) — 3-in-1 soil moisture + temperature + EC probe. - [ZTS-3000-TR-PH-N01](https://sankhyafarms.com/sensors/zts-3000-tr-ph-n01) — Dedicated soil pH probe (single parameter). - [ZTS-3001-TR-ECTHPH-N01](https://sankhyafarms.com/sensors/zts-3001-tr-ecthph-n01) — 4-in-1 soil moisture + temperature + EC + pH probe. - [ZTS-3001-TR-ECTHNPKPH-N01](https://sankhyafarms.com/sensors/zts-3001-tr-ecthnpkph-n01) — 7-in-1 probe — moisture, temp, EC, pH, and live-probe N-P-K. - [ZTS-3002-TR-THNPKPH-N01](https://sankhyafarms.com/sensors/zts-3002-tr-thnpkph-n01) — Moisture, temp, pH + write-in N-P-K (no live nutrient probe). ### SN — Puruisenshe (普锐森社) - [SN-3001-TR-ECTHPH-N01](https://sankhyafarms.com/sensors/sn-3001-tr-ecthph-n01) — 4-in-1 probe (ZTS-compatible) — moisture, temp, EC, pH. - [SN-3002-TR-ECTHNPKPH-N01](https://sankhyafarms.com/sensors/sn-3002-tr-ecthnpkph-n01) — 7-register probe with write-in N-P-K (ZTS-3002-class behaviour). ### JXCT — Weihai JXCT Electronics - [JXBS-3001-TR (4-in-1)](https://sankhyafarms.com/sensors/jxbs-3001-tr-4in1) — JXCT 4-in-1 — moisture, temp, EC, pH. Distinct register family (baud 9600). - [JXBS-3001-TR (7-in-1)](https://sankhyafarms.com/sensors/jxbs-3001-tr-7in1) — JXCT 7-in-1 with live N-P-K. pH scale 0.01; config at 0x0100/0x0101. - [JXBS-3001-NPK-RS](https://sankhyafarms.com/sensors/jxbs-3001-npk-rs) — JXCT standalone N-P-K probe (3 registers from 0x001E). - [JXBS-3001-PH-RS](https://sankhyafarms.com/sensors/jxbs-3001-ph-rs) — JXCT standalone soil pH probe (pH scale 0.01). ### DFRobot — DFRobot - [DFRobot SEN0600](https://sankhyafarms.com/sensors/sen0600) — DFRobot 2-in-1 capacitive moisture + temperature probe. - [DFRobot SEN0601](https://sankhyafarms.com/sensors/sen0601) — DFRobot 5-in-1 — moisture, temp, EC, salinity, TDS. - [DFRobot SEN0602](https://sankhyafarms.com/sensors/sen0602) — DFRobot 3-in-1 — moisture, temperature, pH. - [DFRobot SEN0603](https://sankhyafarms.com/sensors/sen0603) — DFRobot EC + pH monitoring probe (with salinity/TDS). - [DFRobot SEN0604](https://sankhyafarms.com/sensors/sen0604) — DFRobot 4-in-1 — moisture, temp, EC, pH (with salinity/TDS). - [DFRobot SEN0605](https://sankhyafarms.com/sensors/sen0605) — DFRobot N-P-K probe. NPK uses an IEEE-754 coefficient model (two-register decode). ### Renke — Shandong Renke Control Technology - [Renke RS-WS-N01-TR](https://sankhyafarms.com/sensors/rs-ws-n01-tr) — Renke 2-in-1 moisture + temperature probe (ZTS-compatible registers). - [Renke RS-ECTHPH-N01-TR-1](https://sankhyafarms.com/sensors/rs-ecthph-n01-tr-1) — Renke 4-in-1 — moisture, temp, EC, pH (ZTS-compatible registers). - [Renke RS-SD-N01-TR-1](https://sankhyafarms.com/sensors/rs-sd-n01-tr-1) — Renke single-parameter TDR soil-moisture probe (×100 scale, baud 9600). ### MD02 — Generic OEM — air temperature & humidity - [XY-MD02](https://sankhyafarms.com/sensors/xy-md02) — Air temperature + relative humidity transmitter. ASCII protocol on the bench-tested revision.