Drought is a complex stress which elicits a wide variety of plant responses. As such, genetic studies of drought are particularly difficult. Elucidation of the genetic basis of components contributing to drought tolerance is likely to be more tractable than that of overall drought tolerance. Certain of the traits which contribute to drought tolerance in plants and the high-throughput phenotyping techniques available to measure those traits are described in this paper. On the basis of the dynamic nature of drought, plant development, and the resulting stress response, the focus is on non-destructive imaging techniques which allow a temporal resolution and monitoring of the same plants throughout the experiment. Information on the physiological changes in response to drought over time is vital in order to identify and characterize different drought-tolerance mechanisms. High-throughput imaging provides a valuable new tool which allows the dissection of plant responses to drought into a series of component traits.

/pdf/high-throughput-shoot-imaging-to-study-drought-responses-z2auudsxff.pdf

High-throughput shoot imaging to study drought responses

Evaluation of a strawberry-harvesting robot in a field test

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=3087&context=usdaarsfacpub

Review: Development of soft computing and applications in agricultural and biological engineering

Vision-based extraction of spatial information in grape clusters for harvesting robots

In the photosynthesis process, part of the absorbed photon energy in photosystem II (PSII) may be reemitted as chlorophyll a fluorescence (ChlF). Environmental and plant physiological changes affect the emission of ChlF, which makes ChlF a potentially useful tool to sense these changes. Volumes of research on ChlF are published each year and some published work has been controversial. To facilitate the application of ChlF, it is important to have a holistic picture of the field. This review summarizes ChlF applications published in the last 10 years.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/php.12362

Recent advances in the application of chlorophyll a fluorescence from photosystem II.

In this study, dynamic optimization of heat treatment for reducing the water loss in fruit during storage was
investigated using intelligent approaches. Over a temperature range from 15.C to 40.C, the control process was divided into
l steps (l = 6). The dynamic change in the rate of water loss as affected by temperature was first identified using neural
networks, and then the optimal combination of the l–step setpoints for temperature that minimized the rate of water loss was
searched for through simulation of the identified model using genetic algorithms. Two types of optimal values, a single
application of heat stress and a double application of heat stress, were obtained under the range of 15.C < T < 40.C. The
length of each step was 24 h. The former treatment is useful for short–term storage, and the latter is useful for comparatively
long–term storage. With the single heat treatment, the temperature first rises to the highest level (40.C), which is maintained
over a period of 24 h, and then suddenly drops to the lowest level (15.C). In particular, the sudden drop in temperature from
the highest level to the lowest level provided lower values of the rate of water loss than maintaining the temperature constantly
at the lowest level throughout the control process. These results suggest that application of heat stress to fruit is effective in
maintaining freshness of fruit during storage.

Dynamic optimization using neural networks and genetic algorithms for tomato cool storage to minimize water loss

Early detection of drought stress in tomato plants with chlorophyll fluorescence imaging–practical application of the speaking plant approach in a greenhouse–

https://www.jstage.jst.go.jp/article/ecb/52/3/52_183/_pdf

Evapotranspiration Model Analysis of Crop Water Use in Plant Factory System

内成り栽培されたイチゴを自動的に収穫することを目的として, マニピュレータ, エンドエフェクタ, 視覚センサ, 移動機構からなるロボットを試作し, 収穫実験を行った.その結果, 特にエンドエフェクタについて以下の知見が得られた.1) ほとんどの果実は, エンドエフェクタ先端から20mm内外の距離で吸引可能であり, その位置ではマルチを吸引することはなかった.2) 吸引方式の採用は, 果実を傷つけることなく, 迅速に収穫できることおよび視覚センサの位置検出誤差を吸収できるため, イチゴ収穫に対して有効な方法と考えられた.3) 本エンドエフェクタの問題点として, (1) 開閉部に取り付けたマルチ押さえが目的果実の近隣の果実に損傷を与えることがあること, (2) 果柄が内層筒の中心に位置しているときに果柄を切断できないことがあること, (3) 目的果実が他の果実と接触しているときに果皮の摩擦によって吸引できないことがあること, (4) 超音波センサの距離計測では, 茎葉が果実の近くにあるときに大きな誤差を生むことがあることがあげられた.

/pdf/harvesting-robot-for-strawberry-grown-on-annual-hill-top-28ffkd80xx.pdf

Harvesting robot for strawberry grown on annual hill top (part 1) manufacture of the first prototype robot and fundamental harvesting experiment.

One of the essential factors in the root zone environment that affects plant growth is temperature. Determining the optimal root zone temperature condition in a hydroponic system during cultivation could lead to an improvement in plant growth. An optimal control strategy can be determined by identifying the eco-physiological process using a dynamic model. However, it is difficult to develop a dynamic model of the responses of plant growth to root zone temperature because the eco-physiological processes of plants are quite complicated. We propose an intelligent approach that can deal with this complex system. Non-linear autoregressive with exogenous input (NARX) neural networks were used to develop a dynamic model of the responses of plant growth to root zone temperature. The responses of chili pepper plant growth as affected by root zone temperature were measured during 60 days of cultivation inside a growth chamber using a non-destructive and continuous system based on a load cell. Five datasets of dynamic responses of plant growth were obtained for system identification. The results suggest that the application of a neural network is useful for modeling the dynamic response of plant growth to root zone temperature in hydroponic cultivation, with promising performance.

Kenji Hatou

Papers

Dynamic optimization using neural networks and genetic algorithms for tomato cool storage to minimize water loss

Early detection of drought stress in tomato plants with chlorophyll fluorescence imaging–practical application of the speaking plant approach in a greenhouse–

Evapotranspiration Model Analysis of Crop Water Use in Plant Factory System

Harvesting robot for strawberry grown on annual hill top (part 1) manufacture of the first prototype robot and fundamental harvesting experiment.

Modeling the Dynamic Response of Plant Growth to Root Zone Temperature in Hydroponic Chili Pepper Plant Using Neural Networks