Seishi Ninomiya

The University of Tokyo | Todai · Graduate School of Agriculture and Life Sciences

Acid sulfate soil characterized by pyrite (FeS 2 ) which produces high acidity (soil pH < 3.5) and release high amount of Al ³⁺ and Fe ²⁺ . Application of 4 t ha ⁻¹ Ground Magnesium Limestone (GML), is a common rate used for acid sulfate soil by the rice farmers in Malaysia. Therefore, this study was conducted to evaluate the integral effect of gro...

To realize autonomous navigation and intelligent management in orchards, vehicles require real-time positioning and globally consistent mapping of surroundings with sufficient information. However, the unstructured and unstable characteristics of orchards present challenges for accurate and stable localization and mapping. This study proposes a fra...

The leaf phenotypic traits of plants have a significant impact on the efficiency of canopy photosynthesis. However, traditional methods such as destructive sampling will hinder the continuous monitoring of plant growth, while manual measurements in the field are both time-consuming and laborious. Nondestructive and accurate measurements of leaf phe...

Detailed observation of the phenotypic changes in rice panicle substantially helps us to understand the yield formation. In present studies, phenotyping of rice panicles during the heading-flowering stage still lacks comprehensive analysis, especially of panicle development under different nitrogen treatments. In this work, we proposed a pipeline t...

In this study, we use explainable artificial intelligence (XAI) based on class activation map (CAM) techniques. Specifically, we use Grad-CAM, Grad-CAM++, and ScoreCAM to analyze outdoor physical agricultural (agri-) worker image datasets. In previous studies, we developed body-sensing systems to analyze human dynamics with the aim of enhancing agr...

Developing automated soybean seed counting tools will help automate yield prediction before harvesting and improving selection efficiency in breeding programs. An integrated approach for counting and localization is ideal for subsequent analysis. The traditional method of object counting is labor-intensive and error-prone and has low localization a...

We use explainable artificial intelligence (XAI) based on Explain Like I’m 5 (ELI5), Partial Dependency Plot box (PDPbox), and Skater to analyze diverse physical agricultural (agri-) worker datasets. We have developed various promising body-sensing systems to enhance agri-technical advancement, training and worker development, and security. This in...

We use recent explainable artificial intelligence (XAI) based on SHapley Additive exPlanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), and Light Gradient Boosting Machine (LightGBM) to analyze diverse physical agricultural (agri-) worker datasets. We have developed various promising body-sensing systems to enhance agri-techn...

The increase in the number of tillers of rice significantly affects grain yield. However, this is measured only by the manual counting of emerging tillers, where the most common method is to count by hand touching. This study develops an efficient, non-destructive method for estimating the number of tillers during the vegetative and reproductive st...

The camera response function (CRF) that projects hyperspectral radiance to the corresponding RGB images is important for most hyperspectral image super-resolution (HSI-SR) models. In contrast to most studies that focus on improving HSI-SR performance through new architectures, we aim to prevent the model performance drop by learning the CRF of any...

Multispectral images (MSIs) are valuable for precision agriculture due to the extra spectral information acquired compared to natural color RGB (ncRGB) images. In this paper, we thus aim to generate high spatial MSIs through a robust, deep learning-based reconstruction method using ncRGB images. Using the data from the agronomic research trial for...

Training deep learning models typically requires a huge amount of labeled data which is expensive to acquire, especially in dense prediction tasks such as semantic segmentation. Moreover, plant phenotyping datasets pose additional challenges of heavy occlusion and varied lighting conditions which makes annotations more time-consuming to obtain. Act...

In contrast to the rapid advances made in plant genotyping, plant phenotyping is considered a bottleneck in plant science. This has promoted high-throughput plant phenotyping (HTP) studies, resulting in an exponential increase in phenotyping-related publications. The development of HTP was originally intended for use as indoor HTP technologies for...

It has not been fully understood in real fields what environment stimuli cause the genotype-by-environment (G × E) interactions, when they occur, and what genes react to them. Large-scale multi-environment data sets are attractive data sources for these purposes because they potentially experienced various environmental conditions. Here we develope...

It has not been fully understood in real fields what environment stimuli cause the genotype-by-environment (G × E) interactions, when they occur, and what genes react to them. Large-scale multi-environment data sets are attractive data sources for these purposes because they potentially experienced various environmental conditions. Here we develope...

Unmanned aerial vehicle (UAV) and structure from motion (SfM) photogrammetry techniques are widely used for field-based, high-throughput plant phenotyping nowadays, but some of the intermediate processes throughout the workflow remain manual. For example, geographic information system (GIS) software is used to manually assess the 2D/3D field recons...

1. High-throughput 3D phenotyping is a rapidly emerging field that has widespread application for measurement of individual plants. Despite this, high-throughput plant phenotyping is rarely used in ecological studies due to financial and logistical limitations. 2. We introduce EasyDCP, a Python package for 3D phenotyping, which uses photogrammetry...

India Meteorological Department (IMD) has started block-level level agromet advisory (AA) service from the year 2015 and is currently operating in a few blocks of each state across India. In a block-level AA service, on every Tuesday and Friday, AA is being prepared for each block based on the block-level Medium Range weather Forecast (MRF). In thi...

In this study, we are developing a work assist system using Augmented Reality (AR) using a hyperspectral camera. In recent years, spectral information has been used to analyze agricultural products. In the analysis, it is expected that the understanding of the analysis will be improved by comparing it with human visual information such as RGB image...

• Recent advances in Unmanned Aerial Vehicle (UAVs) and image processing have made high‐throughput field phenotyping possible at plot/canopy level in the mass grown experiment. Such techniques are now expected to be used for individual level phenotyping in the single grown experiment. • We found two main challenges of phenotyping individual plants...

Automatic detection of intact tomatoes on plants is highly expected for low-cost and optimal management in tomato farming. Mature tomato detection has been wildly studied, while immature tomato detection, especially when occluded with leaves, is difficult to perform using traditional image analysis, which is more important for long-term yield predi...

Background: Panicle density of cereal crops such as wheat and sorghum is one of the main components for plant breeders and agronomists in understanding the yield of their crops. To phenotype the panicle density effectively, researchers agree there is a significant need for computer vision-based object detection techniques. Especially in recent tim...

Microplot extraction (PE) is a necessary image processing step in unmanned aerial vehicle- (UAV-) based research on breeding fields. At present, it is manually using ArcGIS, QGIS, or other GIS-based software, but achieving the desired accuracy is time-consuming. We therefore developed an intuitive, easy-to-use semiautomatic program for MPE called E...

Panicle density of cereal crops such as wheat and sorghum is one of the main components for plant breeders and agronomists in understanding the yield of their crops. To phenotype the panicle density effectively, researchers agree there is a significant need for computer vision-based object detection techniques. Especially in recent times, research...

Microplot extraction (MPE) is a necessary image-processing step in unmanned aerial vehicle (UAV)-based research on breeding fields. At present, it is manually using ArcGIS, QGIS or other GIS-based software, but achieving the desired accuracy is time-consuming. We therefore developed an intuitive, easy-to-use automatic program for MPE called Easy MP...

Active learning approaches in computer vision generally involve querying strong labels for data. However, previous works have shown that weak supervision can be effective in training models for vision tasks while greatly reducing annotation costs. Using this knowledge, we propose an adaptive supervision framework for active learning and demonstrate...

Background: Accurate estimation of heading date of paddy rice greatly helps the breeders to understand the adaptability of different crop varieties in a given location. The heading date also plays a vital role in determining grain yield for research experiments. Visual examination of the crop is laborious and time consuming. Therefore, quick and p...

The yield of cereal crops such as sorghum (Sorghum bicolor L. Moench) depends on the distribution of crop-heads in varying branching arrangements. Therefore, counting the head number per unit area is critical for plant breeders to correlate with the genotypic variation in a specific breeding field. However, measuring such phenotypic traits manually...

Accurate estimation of heading date of paddy rice greatly helps the breeders to understand the adaptability of different crop varieties in a given location. The heading date also plays a vital role in determining grain yield for research experiments. Visual examination of the crop is laborious and time consuming. Therefore, quick and precise estima...

Micro-plot extraction (MPE) is a needed pre-processing step to any kind of UAV-based phenotyping researches on breeding fields. It is nowadays mostly made by hand, using software such as ArcGIS, QGIS or other GIS-based software. It is a long process that usually does not reach the wanted accuracy unless more time is spend on it. This research aims...

Weather-based decision support systems (DSSs) are being built to improve the efficiency of the production systems in the domains of healthcare, agriculture, transport, governance and so on. Normally, a weather condition (WC) is represented by the statistical values of weather variables for a given duration (e.g. a day or a week). In a weather-based...

Precision horticulture: Peachy method for monitoring orchard growth A rapid automated system for monitoring peach tree growth had been developed that could replace laborious field measurements and enable farmers to manage their orchards more effectively. Knowing a tree’s crown width—the mass of branches and foliage growing outwards from its trunk—e...

Sorghum (Sorghum bicolor L. Moench) is a C4 tropical grass that plays an essential role in providing nutrition to humans and livestock, particularly in marginal rainfall environments. The timing of head development and the number of heads per unit area are key adaptation traits to consider in agronomy and breeding but are time consuming and labor i...

Spectral cameras can handle information on frequencies in a wide range. Therefore, it is frequently used for sensing purposes in agriculture and industrial fields. However, while spectral cameras can deal with enormous amount of information, complicated analysis is required. Thus, they have drawbacks in terms of immediacy of information. In this pa...

In weather-based decision support system (DSS), the domain experts provide suggestions to carry out appropriate measures to improve the efficiency of the respective domain by analyzing both the forecasted and observed weather values. In this paper, to provide suggestions for a given combination of forecasted and observed values, we have proposed a...

The measurement of air temperature is strongly influenced by environmental factors such as solar radiation, humidity, wind speed and rainfall. This is problematic in low-cost air temperature sensors, which lack a radiation shield or a forced aspiration system, exposing them to direct sunlight and condensation. In this study, we developed a machine...

Understanding interactions of genotype, environment, and management under field conditions is vital for selecting new cultivars and farming systems. Image analysis is considered a robust technique in high-throughput phenotyping with non-destructive sampling. However, analysis of digital field-derived images remains challenging because of the variet...

Seedling vigor in tomatoes determines the quality and growth of fruits and total plant productivity. It is well known that the salient effects of environmental stresses appear on the internode length; the length between adjoining main stem node (henceforth called node). In this study, we develop a method for internode length estimation using image...

Sorghum cereal breeding plays a significant role in generating step change in productivity at both the field and farm levels to ensure that crop production keeps up with the global demand for food. Here we explore the application and ability of RGB image (visible band)-based UAV remote sensing technologies to enhance plant breeding research outcome...

In response to human population increase, the utilization of acid sulfate soils for rice cultivation is one option for increasing production. The main problems associated with such soils are their low pH values and their associated high content of exchangeable Al, which could be detrimental to crop growth. The application of soil amendments is one...

Ground cover is an important physiological trait affecting crop radiation capture, water-use efficiency and grain yield. It is challenging to efficiently measure ground cover with reasonable precision for large numbers of plots, especially in tall crop species. Here we combined two image-based methods to estimate plot-level ground cover for three s...

Flowering (spikelet anthesis) is one of the most important phenotypic characteristics of paddy rice, and researchers expend efforts to observe flowering timing. Observing flowering is very time-consuming and labor-intensive, because it is still visually performed by humans. An image-based method that automatically detects the flowering of paddy ric...

A study was conducted to alleviate Al toxicity of an acid sulphate soils collected from paddy cultivation area in Kedah, Peninsular Malaysia. For this purpose, the collected acid sulphate soils were treated with calcium silicate. The treated soils were incubated for 120 days in submerged condition in a glasshouse. Subsamples were collected every 30...

Plant phenotyping becoming increasingly important in modern agriculture, it investigates how a plant's genome, interacting with the environment, affects the observable traits of a plant. To solve the destructive and labor-intensive limitations of phenotyping, new technique known as “image-based Phenotyping” is being conducted successfully under con...

Despite a growing awareness of the usefulness of various Information Communication and Dissemination Technologies (ICDTs) for precision agriculture, which requires soil/crop/weather/environmental data dynamically, there is a concern about the limited availability of a real-time decision support system (DSS) for ubiquitous decision-making. Using Geo...

The appearances of agricultural products are important indices for evaluating the quality of commodities and the characteristics of different varieties. In general, the appearances are evaluated by experts based on visual observations. However, the concern regarding this method is that it lacks objectivity, and it is not quantifiable because it dep...

Data driven precision agriculture aspects, particularly the dynamic disease management, require dynamic crop-weather-environment data at micro level. An experiment was conducted during four consecutive seasons (2009 Kharif, 2009–10 Rabi, 2010 Kharif and 2010–11 Rabi) in a semi-arid tropic region of India to understand the crop-weather-environment-d...

Fully automated yield estimation of intact fruits prior to harvesting provides various benefits to farmers. Until now, several studies have been conducted to estimate fruit yield using image-processing technologies. However, most of these techniques require thresholds for features such as color, shape and size. In addition, their performance strong...

Rice is a staple food for human being. The government of Malaysia realizes that it needs to increase the self-sufficiency level (SSL) in rice production from 73% to 86% for food security reason. Rice production can be increased by expanding the granary area planted with paddy and/or increase paddy yield per unit area. With minimal expansion in gran...

Proper technology transfer based on scientific data is inevitable for farmers to promote sustainable agriculture which is a common target of modern food production. In under-developing countries, illiteracy of farmers is one of the major reasons for them to receive sufficient information and knowledge for such sustainable food production. In this s...