We present a simple and effective high-throughput experimental platform for simultaneous and continuous monitoring of water relations in the soil-plant-atmosphere continuum of numerous plants under dynamic environmental conditions. This system provides a simultaneously measured, detailed physiological response profile for each plant in the array, over time periods ranging from a few minutes to the entire growing season, under normal, stress and recovery conditions and at any phenological stage. Three probes for each pot in the array and a specially designed algorithm enable detailed water-relations characterization of whole-plant transpiration, biomass gain, stomatal conductance and root flux. They also enable quantitative calculation of the whole plant water-use efficiency and relative water content at high resolution under dynamic soil and atmospheric conditions. The system has no moving parts and can fit into many growing environments. A screening of 65 introgression lines of a wild tomato species (Solanum pennellii) crossed with cultivated tomato (S. lycopersicum), using our system and conventional gas-exchange tools, confirmed the accuracy of the system as well as its diagnostic capabilities. The use of this high-throughput diagnostic screening method is discussed in light of the gaps in our understanding of the genetic regulation of whole-plant performance, particularly under abiotic stress.

Water scarcity is a critical limitation for agricultural systems. Two different water management strategies have evolved in plants: an isohydric strategy and an anisohydric strategy. Isohydric plants maintain a constant midday leaf water potential (Y leaf ) when water is abundant, as well as under drought conditions, by reducing stomatal conductance as necessary to limit transpiration. Anisohydric plants have more variable Y leaf and keep their stomata open and photosynthetic rates high for longer periods, even in the presence of decreasing leaf water potential. This risk-taking behavior of anisohydric plants might be beneficial when water is abundant, as well as under moderately stressful conditions. However, under conditions of intense drought, this behavior might endanger the plant. We will discuss the advantages and disadvantages of these two water-usage strategies and their effects on the plant's ability to tolerate abiotic and biotic stress. The involvement of plant tonoplast AQPs in this process will also be discussed. Isohydric vs. Anisohydric Plant BehaviorDifferent regions of the world are characterized by different climatic and environmental conditions, which have led to the development of a wide range of plant adaptation mechanisms and survival strategies. Both anisohydric and isohydric behaviors have been observed in numerous plant groups 1 as well as within individual species, such as grapevine (Vitis vinifera 2 ) and poplar (Populus 3 ), suggesting that the availability of water in the natural environment and dynamic plant-environment relations influence these differences in behavior.4-7 A constant midday leaf water potential (Y leaf ), as a characteristic of isohydric plants, is the result of strict and conservative water-balance management, in which the loss of water is limited by the reduction of stomatal conductance. However, our current understanding of the molecular and cellular factors responsible for these two types of plant behaviors is limited. Evidently, differences in the behavior of isohydric and anisohydric plants are due to differences in the sensitivity of their respective guard cells to a critical Y leaf threshold. As a result, under optimal conditions and mild-tomoderate drought conditions, anisohydric plants maintain higher stomatal conductance (g s ) and CO 2 assimilation (A N ) than isohydric plants and, therefore, are more productive under those conditions. 3,6,[8][9][10]

Sensor-based phenotyping technologies may offer a non-destructive, high-throughput and efficient assessment of herbage yield (HY) to replace current inefficient phenotyping methods. This paper assesses the feasibility of combining normalised difference vegetative index (NDVI) from multispectral imaging and ultrasonic sonar estimates of plant height to estimate HY of single plants in a large perennial ryegrass breeding program. For sensor calibration, fresh HY (FHY) and dry HY (DHY) were acquired destructively, and plant height was measured at four dates each in 2017 and 2018 from a selected subset of 480 plants. Global multiple linear regression models based on K-fold and random split cross-validation methods were used to evaluate the relationship between observed vs. predicted HY. The coefficient of determination (R 2 ) = 0.67-0.68 and a root mean square error (RMSE) between 5.43-7.60 g was obtained for the validation of predicted vs. observed DHY. The mean absolute error (MAE) and mean percentage error (MPE) ranged between 3.59-5.44 g and 22-28%, respectively. For the FHY, R 2 values ranged from 0.63 to 0.70, with an RMSE between 23.50 and 33 g, MAE between 15.11 and 24.34 g and MPE between~22% and 31%. Combining NDVI and plant height is a robust method to enable high-throughput phenotyping of herbage yield in perennial ryegrass breeding programs. current methods on large numbers plants or plots is slow and expensive, making it difficult to include large numbers of individual plants or plots [5]. This makes it challenging to capture an accurate representation of the population and estimate the correct values for individual genotypes. Therefore, HY estimation requires rapid, non-destructive phenotyping methods that can also facilitate genomic tools (e.g., genomic selection, GS) to shorten the breeding time and accelerate genetic gain. However, the number of plants for GS is likely higher than the number of plants traditionally used by breeders to perform selection breeding (e.g., The DairyBio initiative has 48,000 individual plants for genomic sub-selection breeding) where phenotyping of individual plants require accurate evaluation [5]. In recent years, high-throughput phenotyping (HTP) technologies have brought new insights to evaluate phenotypic traits efficiently in large breeding programs [6][7][8][9].Previous studies have used sensor-based data sources from aerial and ground-based platforms to estimate biophysical characteristics of various vegetations, including herbage yield of forage crops [5,10,11]. The aerial-based phenotyping platforms are suitable for lightweight red-green-blue (RGB), multispectral, and hyperspectral imaging systems and have used vegetative indices to build models for herbage yield [10,12] and biomass [13-15] estimation of pasture and cereal crops respectively. Normalised difference vegetative index (NDVI) is a widely used vegetative index for estimates of biomass [16][17][18] with limitations at high-biomass and density of crop cover [19]. Small, low-cost unmanned aerial systems (U...