Manoj Karkee

Washington State University | WSU · Department of Biological Systems Engineering

Molecular-based detection of pathogens from potato tubers hold promise, but the initial sample extraction process is labor-intensive. Developing a robotic tuber sampling system, equipped with a fast and precise machine vision technique to identify optimal sampling locations on a potato tuber, offers a viable solution. However, detecting sampling lo...

In this study, we developed a customized instance segmentation model by integrating the Convolutional Block Attention Module (CBAM) with the YOLO11 architecture. This model, trained on a mixed dataset of dormant and canopy season apple orchard images, aimed to enhance the segmentation of tree trunks and branches under varying seasonal conditions th...

This work presents a framework for localizing ground robots within fruit tree orchards. The standard practice of managing orchards at the large block-level does not maximize the potential of farms — individual plants have different needs due to variations in soil, pests, disease, irrigation, etc. In order to make selective management decisions for...

Currently, deep learning-based instance segmentation for various applications (e.g., Agriculture) is predominantly performed using a labor-intensive process involving extensive field data collection using sophisticated sensors, followed by careful manual annotation of images, presenting significant logistical and financial challenges to researchers...

Collision damage is the most common type of damage during the mechanized harvesting, stacking and transportation of strawberries. Aiming at the problem that hidden bruises on fruits caused by collision behaviors are difficult to detect and accurately quantify in the early stage of damage, this paper carried out simulation and experimental research...

In this study, a robust method for 3D pose estimation of immature green apples (fruitlets) in commercial orchards was developed, utilizing the YOLO11 object detection and pose estimation algorithm alongside Vision Transformers (ViT) for depth estimation (Dense Prediction Transformer (DPT) and Depth Anything V2). For object detection and pose estima...

This study conducted a comprehensive performance evaluation on YOLO11 and YOLOv8, the latest in the "You Only Look Once" (YOLO) series, focusing on their instance segmentation capabilities for immature green apples in orchard environments. YOLO11n-seg achieved the highest mask precision across all categories with a notable score of 0.831, highlight...

Object detection, specifically fruitlet detection, is a crucial image processing technique in agricultural automation, enabling the accurate identification of fruitlets on orchard trees within images. It is vital for early fruit load management and overall crop management, facilitating the effective deployment of automation and robotics to optimize...

There is great interest in alternative pollination strategies for crop production in the face of climate change and perennial threats to the traditional pollination mechanisms. This review explores the potential for robotic pollination in response to these challenges to crop fertilization and global food production. Herein we describe the viability...

Training machine learning (ML) models for artificial intelligence (AI) and computer vision-based object detection process typically requires large, labeled datasets, a process often burdened by significant human effort and high costs associated with imaging systems and image acquisition. This research aimed to simplify image data collection for obj...

Global food production depends upon successful pollination, a process that relies on natural and managed pollinators. However, natural pollinators are declining due to different factors, including climate change, habitat loss, and pesticide use. Thus, developing alternative pollination methods is essential for sustainable crop production. This pape...

One of the major challenges for the agricultural industry today is the uncertainty in manual labor availability and the associated cost. Automated flower and fruit density estimation, localization, and counting could help streamline harvesting, yield estimation, and crop-load management strategies such as flower and fruitlet thinning. This article...

Given the rapid emergence and applications of multi-modal Large Language Models (LLMs) across various scientific fields, insights regarding their applicability in agriculture are still only partially explored. This paper conducts an in-depth review of LLMs in agriculture, focusing on understanding how multi-modal LLMs can be developed and implement...

Blossom thinning is one of the key steps in apple crop load management that improves the quality of apples, reduces stress on the trees, and avoids the likelihood of biennial bearing. Conventional chemical blossom thinning such as air‐blast spraying can lead to excessive use of chemical thinner to ensure full coverage, which can also cause leaf dam...

Given the rapid emergence and applications of Large Language This review systematically examines the progression of the You Only Look Once (YOLO) object detection algorithms from YOLOv1 to the recently unveiled YOLO11 (or YOLOv11). Employing a reverse chronological analysis, this study examines the advancements introduced by YOLO algorithms, beginn...

Given the rapid emergence and applications of Large Language This review systematically examines the progression of the You Only Look Once (YOLO) object detection algorithms from YOLOv1 to the recently unveiled YOLO11 (or YOLOv11). Employing a reverse chronological analysis, this study examines the advancements introduced by YOLO algorithms, beginn...

This paper presents the subsystem descriptions and testing of a small robotic platform intended to harvest strawberries that are grown on elevated beds in open field conditions. Agricultural robots can assist in the optimization of farm resources and help solve issues related to increasing farm costs and labor shortages. Monolithic, large size harv...

The United States (US) apple industry relies heavily on semi‐skilled manual labor force for essential field operations such as training, pruning, blossom and green fruitlet thinning, and harvesting. Blossom thinning is one of the crucial crop‐load management practices to achieve desired crop load, fruit quality, and return bloom. While several tech...

Agriculture has witnessed transformative innovation and technology adoption over the past 100 years including tractors, combine harvesters, and auto-steering techniques. These mechanized or automated machines relieved a huge population around the world from hard labor in challenging farming environments while also increasing food production. This t...

This research investigated the role of artificial intelligence (AI), specifically the DALL.E model by OpenAI, in advancing data generation and visualization techniques in agriculture. DALL.E, an advanced AI image generator, works alongside ChatGPT's language processing to transform text descriptions and image clues into realistic visual representat...

Training machine learning (ML) models for computer vision-based object detection process typically requires large, labeled datasets, a process often burdened by significant human effort and high costs associated with imaging systems and image acquisition. This research aimed to simplify image data collection for object detection in orchards by avoi...

This research investigated the role of artificial intelligence (AI), specifically the DALL.E model by OpenAI, in advancing data generation and visualization techniques in agriculture. DALL.E, an advanced AI image generator, works alongside ChatGPT's language processing to transform text descriptions and image clues into realistic visual representat...

Detecting and estimating size of apples during the early stages of growth is crucial for predicting yield, pest management, and making informed decisions related to crop-load management, harvest and post-harvest logistics, and marketing. Traditional fruit size measurement methods are laborious and time-consuming. This study employs the state-of-the...

Highlights An automated green shoot thinning system was developed by integrating machine vision and mechanical systems. Mask R-CNN used for segmenting cordons at different shoot growth stages. Point cloud registration used to accurately stitch cordon trajectories for continuous thinning operation. Field and lab tests demonstrated the integrated sys...

In order to meet the global food demand amidst the growing population, there’s a critical need to augment productivity in the specialty crop industry. However, workforce shortage in agriculture presents a significant challenge to increasing agricultural productivity, emphasizing the need for. automating various farm operations such as harvesting, c...

This research presents a novel, robotic pollination system designed for targeted pollination of apple flowers in modern fruiting wall orchards. Developed in response to the challenges of global colony collapse disorder, climate change, and the need for sustainable alternatives to traditional pollinators, the system utilizes a commercial manipulator...

Instance segmentation, an important image processing operation for automation in agriculture, is used to precisely delineate individual objects of interest within images, which provides foundational information for various automated or robotic tasks such as selective harvesting and precision pruning. This study compares the one-stage YOLOv8 and the...

Dormant pruning is an important orchard activity for maintaining tree health and producing high-quality fruit. Due to decreasing worker availability, pruning is a prime candidate for robotics. However, pruning also represents a uniquely difficult problem, requiring robust systems for perception, pruning point determination, and manipulation that mu...

Lag-phase in wine grapes refers to a critical stage in the growth cycle of berries when there is a significant slowdown in their growth rate roughly at half the harvest size. This stage is essential for predicting the crop yield at harvest as there is a strong relationship between the lag-phase berry size and the final berry size in grape clusters....

Detecting and estimating size of apples during the early stages of growth is crucial for predicting yield, pest management, and making informed decisions related to crop-load management, harvest and post-harvest logistics, and marketing. Traditional fruit size measurement methods are laborious and time-consuming. This study employs the state-of-the...

This research presents a novel, robotic pollination system designed for targeted pollination of apple flowers in modern fruiting wall orchards. Developed in response to the challenges of global colony collapse disorder, climate change, and the need for sustainable alternatives to traditional pollinators, the system utilizes a commercial manipulator...

Tree fruit growers around the world are facing labor shortages for critical operations, including harvest and pruning. There is a great interest in developing robotic solutionsfor these labor- intensive tasks, but current efforts have been prohibitively costly, slow, or require a reconfiguration of the orchard in order to function. In this paper, w...

This study proposed a YOLOv5-based custom object detection model to detect strawberries in an outdoor environment. The original architecture of the YOLOv5s was modified by replacing the C3 module with the C2f module in the backbone network, which provided a better feature gradient flow. Secondly, the Spatial Pyramid Pooling Fast in the final layer...

Identification of individual king flowers within flower clusters is a critical step for developing a robotic apple pollination system. Typically, each cluster has five to six individual flowers, and the king flower can be occluded by the lateral flowers because of their central position in a flower cluster. King flowers share identical features (e....

Normalized canopy area is a measure of spatial canopy fill or canopy coverage in a tree. It is an important factor for growers to consider in making various farming decisions, such as timing and amount of fertilization, pesticide application, and irrigation, as it gives a sense of the overall canopy growth. This study focused on estimating the norm...

This chapter will discuss the opportunities and challenges of robotic solutions for tree fruit production with modern planar tree canopy management, including the importance of modern tree canopy system, robot-canopy interaction, robotic system control, in-field sensing for object detection, and three-dimensional (3D) reconstruction, and a case stu...

Early-stage identification of fruit flowers that are in both opened and unopened condition in an orchard environment is significant information to perform crop load management operations such as flower thinning and pollination using automated and robotic platforms. These operations are important in tree-fruit agriculture to enhance fruit quality, m...

The US apple industry relies heavily on semi-skilled manual labor force for essential field operations such as training, pruning, blossom and green fruit thinning, and harvesting. Blossom thinning is one of the crucial crop load management practices to achieve desired crop load, fruit quality, and return bloom. While several techniques such as chem...

The introduction of fruit tree harvesters on the market allows the opportunity to incorporate new yield monitors. Traditionally, yield has been measured by in-the-field fruit batch weighing systems that employ load cells, which present certain problems as well as oscillations and outliers. We propose the development and evaluation of two distance m...

Highlights A cartesian robotic spraying system was developed for precision apple blossom thinning. Flower clusters were detected and localized with deep learning model for target spraying. A communication algorithm was developed for positioning the spray end-effector to the target flowers. The cartesian robotic system greatly reduced chemical usage...

Modern high-density apple orchards utilize trellis support systems to provide robust tree architecture that improves overall orchard health, supports increasing crop load, and enhances the opportunity for orchard automation. However, these trellis wires can create a significant issue when agricultural robots interact with the apple trees to pick fr...

Automated or robotic harvesting methods are being investigated worldwide and have shown promising alternatives to manual harvesting in strawberry production. In robotic strawberry harvesting, the critical task of its machine vision system is to detect the presence and maturity of strawberries and estimate their precise location in the canopies. Thi...

Tree canopy density is an important parameter in developing a decision support system for precision orchard management including application of the right amount of nutrients at the right time and right location. Previous studies mostly focus on canopy characterization using the light detection and ranging (LiDAR) sensor which lacks critical color a...

Precise canopy management is critical in vineyards for premium wine production because maximum crop load does not guarantee the best economic return for wine producers. The growers keep track of the number of grape bunches during the entire growing season for optimizing crop load per vine. Manual counting of grape bunches can be highly labor-intens...

Many aspects of the agricultural industry such a field crop planting and harvesting and chemical application in fruit crops have been employing mechanization and automation solutions for decades. However, the de-handing operation in banana postharvest operations is usually performed manually. Mechanical or automated de-handing is a potential long-t...

In this research, an integrated detection model, Swin-transformer-YOLOv5 or Swin-T-YOLOv5, was proposed for real-time wine grape bunch detection to inherit the advantages from both YOLOv5 and Swin-transformer. The research was conducted on two different grape varieties of Chardonnay (always white berry skin) and Merlot (white or white-red mix berry...

Crop damage caused by pest birds is a big problem around the world. As many studies have shown, existing bird control methods have not met growers' expectations regarding efficacy, reliability, and cost. Researchers are investigating the potential of using unmanned aerial vehicles (UAVs) as a tool for bird deterrence in agricultural fields to addre...

Robotic strawberry harvesting requires machine vision system to have the ability to detect the presence, maturity, and location of strawberries. Strawberries, however, can easily be bruised, injured, and even damaged during robotic harvest if not picked properly because of their soft surfaces. Therefore, it is important to cut or pick the strawberr...

Dormant pruning of fruit trees is an important task for maintaining tree health and ensuring high-quality fruit. Due to decreasing labor availability, pruning is a prime candidate for robotic automation. However, pruning also represents a uniquely difficult problem for robots, requiring robust systems for perception, pruning point determination, an...

Flower and fruit count is a critical metric in developing crop-load management and harvesting strategies during flower/fruit development and harvest seasons. Growers currently rely on their prior experience and/or manual count in sample areas/trees to estimate the number of flowers/fruits in orchards. In this work, we propose a simplified yet robus...

Accurate detection of both immature and mature apples in orchard environments is essential for early crop load management. A near real-time method is proposed in this study for detecting green (early-stage), green–red-mixed (mid-stage; red varieties), or red apples (harvest-stage; red varieties). Both the number of fruits and fruit size were estima...

Machine vision technologies have been increasingly used in emerging monitoring, automation, and robotic applications such as autonomous vehicles, robotic manipulation, product inspection, and warehouse automation. Production agriculture, being heavily laborious and dependent on human experience, is one of the potential industries that can heavily l...

https://onlinelibrary.wiley.com/share/author/QVD9RAUFRQZ4CFU97ADG?target=10.1002/rob.22045 **************************************** To reduce the human effort involved in walk-behind paddy transplanter operation, a remote-control system consisting of an electronic control unit (ECU) was designed and developed. A separate remote handheld wireless k...

The biomechanical properties of plant stalk play an important role in the increase of crop production, the development of post-harvest mechanical equipment and the comprehensive utilization of biomass resources. Under the action of external forces in different forms and different loading directions, there are differences in the internal biomechanic...

Commonly accepted population growth models predict there will be more than nine billion people by 2050.

An agricultural or field robot consists of various component systems, including all or some of 2D color and 3D sensing systems, robot control system, field task management system, navigation and guidance system, manipulation and end-effector system, inspection and quality control system, and conveying and packaging system. Sensing and data/image pr...

Labor shortage has been and will continue to be one of the greatest challenges faced by agricultural industry worldwide. This issue is specifically concerning in specialty crop production, which often needs massive workforce during a short period of the growing season such as fruit harvesting and crop thinning. To address this issue, tree fruit ind...

Pushed by the critical needs for addressing insufficient field labor availability and rapidly increasing labor costs in agriculture and other field operations and pulled by the successes and realized benefits of adopting robotic technologies in other industrial applications, robotized agricultural and field operations have been envisioned (and adop...

Aiming at the problems of high labor intensity, low efficiency and potential health hazards in the manual de-handing operation in the current banana harvesting and de-handing process, we have studied the key technologies of mechanical banana de-handing and tested the stability and universality of the operations of banana de-handing device. The self...

Green shoot thinning in vineyards is an essential, perennial operation for maintaining canopy health and optimizing yield and quality of wine grapes. Use of mechanized thinning system, which is essential to reduce labor dependency and associated cost, causes high variability in shoot removal efficiency due to difficulty in precisely positioning the...