Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle

Sugiura, Ryo; Tsuda, Shogo; Tamiya, Sadafumi; Itoh, Atsushi; Nishiwaki, Kentaro; Murakami, Noriyuki; Shibuya, Yukinori; Hirafuji, Masayuki; Nuske, Stephen

doi:10.1016/j.biosystemseng.2016.04.010

Cited by 135 publications

(95 citation statements)

References 31 publications

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“…For the accurate estimation of the damaged leaf area, the diseased leaf was photographed as soon as the first necrotic damage was observed. Total areas of green color and chlorotic lesion area were measured with an estimation method for disease severity using RGB imagery [22] from Image J, a Java-based image processing tool (https://imagej.nih.gov/ij/). The damaged leaf area from Image J analyses was then used to evaluate the severity of late blight.…”

Section: Severity Of Late Blight Diseasementioning

confidence: 99%

Reducing Severity of Late Blight (Phytophthora infestans) and Improving Potato (Solanum tuberosum L.) Tuber Yield with Pre-Harvest Application of Calcium Nutrients

Seifu¹

2017

Agronomy

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Abstract:The efficiency of pre-harvest application of calcium chloride alone, calcium nitrate alone, and combined application of calcium chloride and calcium nitrate (1:1) was evaluated in reducing the severity of P. infestans and improving potato tuber yield. Pot experiment was conducted in randomized complete block design with four replications. The treatments consisted of combination of two potato varieties (Shenkola and Gera) and three types of calcium nutrients (calcium chloride alone, calcium nitrate alone, and calcium chloride mixed with calcium nitrate), each at three levels (5, 10, and 15 g per liter per plant) and the control treatment (0 g of calcium nutrients). In comparison to the control treatment, the application of calcium nutrients significantly decreased the severity of late blight disease and improved potato tuber yield. The effect of calcium nutrients on the severity of late blight disease and potato tuber yield differed among the two potato varieties. The maximum severity reduction (60%) was noticed in the Gera potato variety with the application of calcium chloride mixed with calcium nitrate (1:1), supplied at 15 g per plant. However, the highest average tuber yield was obtained with the application of calcium nitrate at 15 g per plant, and average tuber yield was increased by 77% in both potato varieties. Hence, foliar application of either calcium nitrate alone or calcium nitrate mixed with calcium chloride was found to be more efficient than the application of calcium chloride alone. This result suggests that the nitrate ion present in the calcium nitrate may make a difference in terms of reducing the severity of late blight disease and improving potato tuber yield. The lowered severity of late blight disease and the increased tuber yield in potato plants sprayed with calcium nutrients may be because of the higher accumulation of calcium in the plant tissue.

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Section: Severity Of Late Blight Diseasementioning

confidence: 99%

Reducing Severity of Late Blight (Phytophthora infestans) and Improving Potato (Solanum tuberosum L.) Tuber Yield with Pre-Harvest Application of Calcium Nutrients

Seifu¹

2017

Agronomy

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“…Previous research studies have found that the application of UAV remote sensing is mainly used for crop classification, disaster monitoring, wheat plants density, estimation of agronomic parameters and growth analysis in agricultural applications [9,10] In crop classification research, UAVs mainly acquire data on different types of planting areas to facilitate crop management and related decisionmaking [11]. Disaster monitoring has been an important topic in recent years, including both the monitoring of field pests and the abnormal growth of crops caused by external factors, such as the monitoring of lodging [12,13].…”

Section: Field Trialsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of Seed Emergence Uniformity of Mechanically Sown Wheat with UAV RGB Imagery

Liu

Jin

et al. 2017

Remote Sensing

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Abstract:The uniformity of wheat seed emergence is an important characteristic used to evaluate cultivars, cultivation mode and field management. Currently, researchers typically investigated the uniformity of seed emergence by manual measurement, a time-consuming and laborious process. This study employed field RGB images from unmanned aerial vehicles (UAVs) to obtain information related to the uniformity of wheat seed emergence and missing seedlings. The calculation of the length of areas with missing seedlings in both drill and broadcast sowing can be achieved by using an area localization algorithm, which facilitated the comprehensive evaluation of uniformity of seed emergence. Through a comparison between UAV images and the results of manual surveys used to gather data on the uniformity of seed emergence, the root-mean-square error (RMSE) was 0.44 for broadcast sowing and 0.64 for drill sowing. The RMSEs of the numbers of missing seedling regions for broadcast and drill sowing were 1.39 and 3.99, respectively. The RMSEs of the lengths of the missing seedling regions were 12.39 cm for drill sowing and 0.20 cm 2 for broadcast sowing. The UAV image-based method provided a new and greatly improved method for efficiently measuring the uniformity of wheat seed emergence. The proposed method could provide a guideline for the intelligent evaluation of the uniformity of wheat seed emergence.

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“…However, this visual assessment is generally time-consuming and quite subjective. In work [9] is proposed to use a new a new estimation technique for disease severity in a field using RGB imagery from an unmanned aerial vehicle (UAV). Potato late blight is one of the most serious diseases affecting potato production in Japan.…”

Section: Weed Control and Disease Monitoringmentioning

confidence: 99%

“…When monitoring the field, UAVs are widely used for aerial photography due to low cost, high resolution images compared to satellite images due to low flight altitude, the ability to move in any direction, hover, maintain a stable position in flight, etc. In work [9] images of the potato field were taken by a UAV (HiSystems GmbH Mikrokopter, Germany) with four counter rotating propeller pairs and eight brushless motors. The test field consisted of 36 rows laid out along the long side of the field in an area that was 53.8 m x 27.0 m, and the space between rows was 75 cm.…”

Section: Weed Control and Disease Monitoringmentioning

confidence: 99%

Hierarchical classification of robotic grippers applied for agricultural object manipulations

Kuzov

Ronzhin

2018

MATEC Web Conf.

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An overview of agricultural grippers used to control weeds and harvesting is presented. The classification of the grippers, which are installed on robotic agricultural tools for manipulation of fruits, weeds and other objects, is compiled. There are 22 types of grippers depending on 6 selected criteria: drive type, the presence of the drive in the grip, the number of fingers, the type of gripper movement, the type of mechanism, the type of sensors. In this classification, we mainly consider the characteristics of the gripper, which is installed at the end of the manipulator and is responsible for physical contact with the object. Therefore, the main attention is paid to problems requiring direct capture of objects by the agrobots. The issue of joint interaction of a group of heterogeneous terrestrial and airborne robots in the performance of the target agrarian task in an autonomous mission will also be investigated.

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Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle

Cited by 135 publications

References 31 publications

Reducing Severity of Late Blight (Phytophthora infestans) and Improving Potato (Solanum tuberosum L.) Tuber Yield with Pre-Harvest Application of Calcium Nutrients

Reducing Severity of Late Blight (Phytophthora infestans) and Improving Potato (Solanum tuberosum L.) Tuber Yield with Pre-Harvest Application of Calcium Nutrients

Evaluation of Seed Emergence Uniformity of Mechanically Sown Wheat with UAV RGB Imagery

Hierarchical classification of robotic grippers applied for agricultural object manipulations

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