Agriculture

XAG’s New P150 Max Drone Brings Smart, Heavy-Duty Automation to Modern Farming

When farm challenges grow, smart tools need to grow with them.

Updated

November 27, 2025 3:26 PM

A drone spraying water over an agricultural field. PHOTO: FREEPIK

Farms today are under pressure. Fields are getting bigger, workers are harder to find and many jobs still rely on long hours of manual labor. XAG’s new P150 Max agricultural drone is designed for exactly this reality. Instead of replacing farmers, it takes over the heavy, repetitive fieldwork that slows them down, making farm operations more efficient and more precise.

The P150 Max is built around one simple idea: a single machine that can handle multiple farming tasks. Most farm drones focus only on spraying or mapping, but this one is fully modular. With a quick switch of attachments, it can spray crops, spread seeds or fertilizer, map fields or transport supplies. This flexibility helps farmers keep up with changing tasks throughout the day without needing different machines, improving both productivity and cost-efficiency.

A key challenge in agriculture is that fields are rarely smooth or predictable. Tractors can get stuck, smaller drones can’t carry much and some areas—like orchards or hilly plots—are simply hard to reach. The P150 Max fills that gap with an 80-kilogram payload and fast flight speed, letting it cover more ground per trip. Fewer takeoffs mean less downtime and more work completed before weather or daylight cuts operations short.

When it’s time to spray, the drone uses a smart spraying system that allows farmers to adjust droplet size based on the crop’s needs. This matters because precise spraying reduces waste and improves targeting. With an output of up to 46 liters per minute, the drone can serve both large open fields and dense orchards where consistent coverage is traditionally difficult.

The spreading system applies the same logic. Instead of dropping seeds or fertilizer unevenly, the vertical mechanism spreads material smoothly and resists wind drift. This ensures uniform application across irregular or hard-to-reach land—an ongoing challenge for modern farms aiming for higher yield and better resource use.

Another everyday issue for farmers is understanding and surveying the land before working on it. The P150 Max helps here with a built-in mapping tool that covers up to 20 hectares per flight and instantly converts the images into detailed maps. With AI detecting obstacles like trees or irrigation lines, the drone can plan safe and efficient autonomous routes, reducing manual planning time.

Beyond spraying and spreading, the drone can transport tools, produce and farm supplies using a sling attachment. This is particularly helpful after heavy rain, when vehicles cannot easily move across muddy or flooded fields.

Under all these functions is XAG’s upgraded flight control system, which provides centimeter-level accuracy even when network signals are weak. Integrated sensors—including 4D radar and a wide-angle camera—help the drone recognize hazards such as poles and wires. Farmers can manage all operations through the XAG One app or a handheld controller, both of which automatically generate the best route based on field shape and terrain.

Since long field days require long operating hours, the fast-charging battery system can recharge in about seven minutes using a dedicated kit. This supports continuous drone use throughout the day with minimal interruptions.

After years of testing, the XAG P150 Max is essentially an effort to make practical, scalable farm automation more accessible. By combining spraying, spreading, mapping and transport into one heavy-duty platform, it offers a way to ease labor shortages while keeping operations efficient and sustainable. Instead of focusing on one task, the drone aims to take over the time-consuming physical work so farmers can focus on decisions, planning and crop management.

Keep Reading

Biotechnology

How AI Is Helping Decode the Tumor Microenvironment — and What It Means for Cancer Care

A closer look at how machine intelligence is helping doctors see cancer in an entirely new light.

Updated

November 28, 2025 4:18 PM

Serratia marcescens colonies on BTB agar medium. PHOTO: UNSPLASH

Artificial intelligence is beginning to change how scientists understand cancer at the cellular level. In a new collaboration, Bio-Techne Corporation, a global life sciences tools provider, and Nucleai, an AI company specializing in spatial biology for precision medicine, have unveiled data from the SECOMBIT clinical trial that could reshape how doctors predict cancer treatment outcomes. The results, presented at the Society for Immunotherapy of Cancer (SITC) 2025 Annual Meeting, highlight how AI-powered analysis of tumor environments can reveal which patients are more likely to benefit from specific therapies.

Led in collaboration with Professor Paolo Ascierto of the University of Napoli Federico II and Istituto Nazionale Tumori IRCCS Fondazione Pascale, the study explores how spatial biology — the science of mapping where and how cells interact within tissue — can uncover subtle immune behaviors linked to survival in melanoma patients.

Using Bio-Techne’s COMET platform and a 28-plex multiplex immunofluorescence panel, researchers analyzed 42 pre-treatment biopsies from patients with metastatic melanoma, an advanced stage of skin cancer. Nucleai’s multimodal AI platform integrated these imaging results with pathology and clinical data to trace patterns of immune cell interactions inside tumors.

The findings revealed that therapy sequencing significantly influences immune activity and patient outcomes. Patients who received targeted therapy followed by immunotherapy showed stronger immune activation, marked by higher levels of PD-L1+ CD8 T-cells and ICOS+ CD4 T-cells. Those who began with immunotherapy benefited most when PD-1+ CD8 T-cells engaged closely with PD-L1+ CD4 T-cells along the tumor’s invasive edge. Meanwhile, in patients alternating between targeted and immune treatments, beneficial antigen-presenting cell (APC) and T-cell interactions appeared near tumor margins, whereas macrophage activity in the outer tumor environment pointed to poorer prognosis.

“This study exemplifies how our innovative spatial imaging and analysis workflow can be applied broadly to clinical research to ultimately transform clinical decision-making in immuno-oncology”, said Matt McManus, President of the Diagnostics and Spatial Biology Segment at Bio-Techne.

The collaboration between the two companies underscores how AI and high-plex imaging together can help decode complex biological systems. As Avi Veidman, CEO of Nucleai, explained, “Our multimodal spatial operating system enables integration of high-plex imaging, data and clinical information to identify predictive biomarkers in clinical settings. This collaboration shows how precision medicine products can become more accurate, explainable and differentiated when powered by high-plex spatial proteomics – not limited by low-plex or H&E data alone”.

Dr. Ascierto described the SECOMBIT trial as “a milestone in demonstrating the possible predictive power of spatial biomarkers in patients enrolled in a clinical study”.

The study’s broader message is clear: understanding where immune cells are and how they interact inside a tumor could become just as important as knowing what they are. As AI continues to map these microscopic landscapes, oncology may move closer to genuinely personalized treatment — one patient, and one immune network, at a time.