scholarly journals A cost-effective and customizable automated irrigation system for precise high-throughput phenotyping in drought stress studies

PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0198546 ◽  
Author(s):  
Diego Ortiz ◽  
Alexander G. Litvin ◽  
Maria G. Salas Fernandez
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Irrigation System ◽  
Cost Effective ◽  
Stress Studies ◽  
High Throughput Phenotyping ◽  
Automated Irrigation System

scholarly journals High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Large Scale ◽  
Crop Yields ◽  
Plant Traits ◽  
Rapid Development ◽  
Plant Responses ◽  
Phenotypic Data ◽  
Agricultural Technologies ◽  
High Throughput Phenotyping

Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.

scholarly journals Review: Cost-Effective Unmanned Aerial Vehicle (UAV) Platform for Field Plant Breeding Application

2020 ◽  
Vol 12 (6) ◽  
pp. 998 ◽  
Author(s):  
GyuJin Jang ◽  
Jaeyoung Kim ◽  
Ju-Kyung Yu ◽  
Hak-Jin Kim ◽  
Yoonha Kim ◽  
...  
Keyword(s):  
Plant Breeding ◽  
Unmanned Aerial Vehicle ◽  
High Throughput ◽  
New Technologies ◽  
Cost Effective ◽  
New Wave ◽  
Breeding Programs ◽  
Modern Agriculture ◽  
Aerial Vehicle ◽  
High Throughput Phenotyping

Utilization of remote sensing is a new wave of modern agriculture that accelerates plant breeding and research, and the performance of farming practices and farm management. High-throughput phenotyping is a key advanced agricultural technology and has been rapidly adopted in plant research. However, technology adoption is not easy due to cost limitations in academia. This article reviews various commercial unmanned aerial vehicle (UAV) platforms as a high-throughput phenotyping technology for plant breeding. It compares known commercial UAV platforms that are cost-effective and manageable in field settings and demonstrates a general workflow for high-throughput phenotyping, including data analysis. The authors expect this article to create opportunities for academics to access new technologies and utilize the information for their research and breeding programs in more workable ways.

scholarly journals Smart irrigation system based on IoT

2020 ◽  
Author(s):  
arushi dheer ◽  
M. L. sharma ◽  
krishna tripathi
Keyword(s):  
Large Scale ◽  
Soil Analysis ◽  
Irrigation System ◽  
Cost Effective ◽  
Water Shortage ◽  
Home Garden ◽  
Agriculture Sector ◽  
Indian Agriculture ◽  
Shared Network ◽  
Automated Irrigation System

<div><div><div><div><p>Agriculture is the backbone of the Indian economy. The Indian agriculture sector accounts for 18% of the gross domestic product and employs nearly 50% of the country's workforce, with increasing population, water shortage and ever-growing demand for food. Since the acres of land available for cultivation remains unchanged, it is critical that we take steps towards increasing productivity and optimizing water usage to increase yield from the land currently available for cultivation. Soil Analysis has become an essential factor for effective cultivation. The need for the automated irrigation system is to overcome over-irrigation and under-irrigation.[1] This research paper proposes an automated irrigation system using Arduino microcontroller, which is cost-effective and can be used on a farm field or average home garden. IoT is an upcoming technology with huge prospects. IoT is a technology which connects things, people, applications, data. Internet of Things (IoT)is a shared network of objects or things which can interact with each other provided the Internet connection—using this technology to implement this system at a lower scale to act as a base model. With the implementation of this project at a large scale, it could bring a significant change in the overall yield and water consumption in agriculture.</p></div></div></div></div>

scholarly journals Solar Powered Smart Irrigation System

2021 ◽  
pp. 898-901
Author(s):  
Bhavna Dhole ◽  
Pratiksha Patle ◽  
Onkar Patole ◽  
Suprriya Lohar
Keyword(s):  
Soil Moisture ◽  
Irrigation System ◽  
Cost Effective ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Energy Needs ◽  
Electricity Crisis ◽  
Remote Station ◽  
Solar Powered ◽  
Automated Irrigation System

This paper addresses water scarcity and electricity crisis by designing and implementing smart irrigation system. This system presents the details of a solar-powered automated irrigation system that turns ON/OFF the motor to pass water through the pump required to soil depending on the soil moisture, hence this system minimize the wastage of water. Soil moisture sensor sense the humidity of soil which is transmitted to a remote station. This data will be analyzed and used to pass out water by water pump. This system conserves electricity and conserves water. It is the proposed solution for the now a days energy crisis for the Indian farmers. Cost-effective solar power can be the answer to our energy needs. Solar powered smart irrigation systems are the acknowledgement to the Indian farmer.This system does not work at night in areas without a grid.

scholarly journals HIGH THROUGHPUT PHENOTYPING OF PHYSIOLOGICAL GROWTH DYNAMICS FROM UAS-BASED 3D MODELING IN SOYBEAN

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 357-361 ◽  
Author(s):  
M. Herrero-Huerta ◽  
K. M. Rainey
Keyword(s):  
High Throughput ◽  
Digital Camera ◽  
Growth Dynamics ◽  
Cost Effective ◽  
Growing Season ◽  
3D Modelling ◽  
Crop Genetics ◽  
High Throughput Phenotyping ◽  
Research And Education ◽  
Selection Of

<p><strong>Abstract.</strong> Nowadays, an essential tool to improve the efficiency of crop genetics is automated, precise and cost-effective phenotyping of the plants. The aim of this study is to generate a methodology for high throughput phenotyping the physiological growth dynamics of soybeans by UAS-based 3D modelling. During the 2018 growing season, a soybean experiment was performed at the Agronomy Center for Research and Education (ACRE) in West-Lafayette (Indiana, USA). Periodic images were acquired by G9X Canon compact digital camera on board senseFly eBee. The study area is reconstructed in 3D by Image-based modelling. Algorithms and techniques were combined to analyse growth dynamics of the crop via height variations and to quantify biomass. Results provide practical information for the selection of phenotypes for breeding.</p>

scholarly journals Smart irrigation system based on IoT

2020 ◽  
Author(s):  
arushi dheer ◽  
M. L. sharma ◽  
krishna tripathi
Keyword(s):  
Large Scale ◽  
Soil Analysis ◽  
Irrigation System ◽  
Cost Effective ◽  
Water Shortage ◽  
Home Garden ◽  
Agriculture Sector ◽  
Indian Agriculture ◽  
Shared Network ◽  
Automated Irrigation System

<div><div><div><div><p>Agriculture is the backbone of the Indian economy. The Indian agriculture sector accounts for 18% of the gross domestic product and employs nearly 50% of the country's workforce, with increasing population, water shortage and ever-growing demand for food. Since the acres of land available for cultivation remains unchanged, it is critical that we take steps towards increasing productivity and optimizing water usage to increase yield from the land currently available for cultivation. Soil Analysis has become an essential factor for effective cultivation. The need for the automated irrigation system is to overcome over-irrigation and under-irrigation.[1] This research paper proposes an automated irrigation system using Arduino microcontroller, which is cost-effective and can be used on a farm field or average home garden. IoT is an upcoming technology with huge prospects. IoT is a technology which connects things, people, applications, data. Internet of Things (IoT)is a shared network of objects or things which can interact with each other provided the Internet connection—using this technology to implement this system at a lower scale to act as a base model. With the implementation of this project at a large scale, it could bring a significant change in the overall yield and water consumption in agriculture.</p></div></div></div></div>

scholarly journals Custom built scanner and simple image processing pipeline enables low-cost, high-throughput phenotyping of maize ears

2019 ◽  
Author(s):  
Cedar Warman ◽  
John E Fowler
Keyword(s):  
Image Processing ◽  
High Throughput ◽  
Low Cost ◽  
Digital Camera ◽  
Cost Effective ◽  
Source Image ◽  
Processing Pipeline ◽  
Effective Combination ◽  
Transmission Data ◽  
High Throughput Phenotyping

AbstractHigh-throughput phenotyping systems are becoming increasingly powerful, dramatically changing our ability to document, measure, and detect phenomena. Unfortunately, taking advantage of these trends can be difficult for scientists with few resources, particularly when studying nonstandard biological systems. Here, we describe a powerful, cost-effective combination of a custom-built imaging platform and open-source image processing pipeline. Our maize ear scanner was built with off-the-shelf parts for <$80. When combined with a cellphone or digital camera, videos of rotating maize ears were captured and digitally flattened into projections covering the entire surface of the ear. Segregating GFP and anthocyanin seed markers were clearly distinguishable in ear projections, allowing manual annotation using ImageJ. Using this method, statistically powerful transmission data can be collected for hundreds of maize ears, accelerating the phenotyping process.

scholarly journals High-throughput phenotyping to dissect genotypic differences in safflower for drought tolerance

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254908
Author(s):  
Sameer Joshi ◽  
Emily Thoday-Kennedy ◽  
Hans D. Daetwyler ◽  
Matthew Hayden ◽  
German Spangenberg ◽  
...  
Keyword(s):  
Drought Stress ◽  
Drought Tolerance ◽  
High Throughput ◽  
Crop Yields ◽  
Geometric Mean ◽  
Shoot Biomass ◽  
Screening Methods ◽  
Tolerance Index ◽  
Genotypic Differences ◽  
High Throughput Phenotyping

Drought is one of the most severe and unpredictable abiotic stresses, occurring at any growth stage and affecting crop yields worldwide. Therefore, it is essential to develop drought tolerant varieties to ensure sustainable crop production in an ever-changing climate. High-throughput digital phenotyping technologies in tandem with robust screening methods enable precise and faster selection of genotypes for breeding. To investigate the use of digital imaging to reliably phenotype for drought tolerance, a genetically diverse safflower population was screened under different drought stresses at Agriculture Victoria’s high-throughput, automated phenotyping platform, Plant Phenomics Victoria, Horsham. In the first experiment, four treatments, control (90% field capacity; FC), 40% FC at initial branching, 40% FC at flowering and 50% FC at initial branching and flowering, were applied to assess the performance of four safflower genotypes. Based on these results, drought stress using 50% FC at initial branching and flowering stages was chosen to further screen 200 diverse safflower genotypes. Measured plant traits and dry biomass showed high correlations with derived digital traits including estimated shoot biomass, convex hull area, caliper length and minimum area rectangle, indicating the viability of using digital traits as proxy measures for plant growth. Estimated shoot biomass showed close association having moderately high correlation with drought indices yield index, stress tolerance index, geometric mean productivity, and mean productivity. Diverse genotypes were classified into four clusters of drought tolerance based on their performance (seed yield and digitally estimated shoot biomass) under stress. Overall, results show that rapid and precise image-based, high-throughput phenotyping in controlled environments can be used to effectively differentiate response to drought stress in a large numbers of safflower genotypes.

scholarly journals Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress

2021 ◽  
Author(s):  
Nathan T Hein ◽  
Ignacio A Ciampitti ◽  
S V Krishna Jagadish
Keyword(s):  
Remote Sensing ◽  
Drought Stress ◽  
High Throughput ◽  
Complex Traits ◽  
Crop Improvement ◽  
Grain Filling ◽  
Time Of Day ◽  
Water Soluble ◽  
High Throughput Phenotyping ◽  
Improvement Programs

Abstract Flowering and grain-filling stages are highly sensitive to heat and drought stress exposure, leading to significant loss in crop yields. Therefore, phenotyping to enhance resilience to these abiotic stresses is critical for sustaining genetic gains in crop improvement programs. However, traditional methods for screening traits related to these stresses are slow, laborious, and often expensive. Remote sensing provides opportunities to introduce low-cost, less-biased, high-throughput phenotyping methods to capture large genetic diversity to facilitate enhancement of stress resilience in crops. This review focuses on four key physiological traits or processes that are critical in understanding crop responses to drought and heat stress during reproductive and grain-filling periods. Specifically, these traits include: i) time-of-day of flowering, to escape these stresses during flowering, ii) optimizing photosynthetic efficiency, iii) storage and translocation of water-soluble carbohydrates, and iv) yield and yield components to provide in-season yield estimates. An overview of current advances in remote sensing in capturing these traits, limitations with existing technology and future direction of research to develop high-throughput phenotyping approaches for these traits are discussed in this review. In the future, phenotyping these complex traits will require sensor advancement, high-quality imagery combined with machine learning methods, and efforts in transdisciplinary science to foster integration across disciplines.

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