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A High-Throughput Physiological Functional Phenotyping System for Time- and Cost-Effective Screening of Potential Biostimulants
View ORCID ProfileAhan Dalal, Ronny Bourstein, Nadav Haish, Itamar Shenhar, Rony Wallach, Menachem Moshelion
Ahan Dalal
1The Robert H. Smith Faculty of Agriculture, Food and Environment, Institute of Plant Sciences and Genetics in Agriculture, The Hebrew University of Jerusalem, Rehovot, Israel
ORCID record for Ahan Dalal
Ronny Bourstein
2The Robert H. Smith Faculty of Agriculture, Food and Environment, Department of Soil and Water Sciences, The Hebrew University of Jerusalem, Rehovot, Israel
Nadav Haish
Itamar Shenhar
Rony Wallach
Menachem Moshelion
For correspondence: menachem.moshelion@mail.huji.ac.il
The improvement of crop productivity under abiotic stress is one of the biggest challenges faced by the agricultural scientific community. Despite extensive research, the research-to-commercial transfer rate of abiotic stress-resistant crops remains very low. This is mainly due to the complexity of genotype◻×◻environment interactions and in particular, the ability to quantify the dynamic plant physiological response profile to a dynamic environment.
Most existing phenotyping facilities collect information using robotics and automated image acquisition and analysis. However, their ability to directly measure the physiological properties of the whole plant is limited. We demonstrate a high-throughput functional phenotyping system (HFPS) that enables comparing plants' dynamic responses to different ambient conditions in dynamic environments due to its direct and simultaneous measurement of yield-related physiological traits of plants under several treatments. The system is designed as one-to-one (1:1) plant–[sensors+controller] units, i.e., each individual plant has its own personalized sensor, controller and irrigation valves that enable (i) monitoring water-relation kinetics of each plant–environment response throughout the plant's life cycle with high spatiotemporal resolution, (ii) a truly randomized experimental design due to multiple independent treatment scenarios for every plant, and (iii) reduction of artificial ambient perturbations due to the immobility of the plants or other objects. In addition, we propose two new resilience-quantifying-related traits that can also be phenotyped using the HFPS: transpiration recovery rate and night water reabsorption.
We use the HFPS to screen the effects of two commercial biostimulants (a seaweed extract—ICL-SW, and a metabolite formula—ICL-NewFo1) on Capsicum annuum under different irrigation regimes. Biostimulants are considered an alternative approach to improving crop productivity. However, their complex mode of action necessitates cost-effective pre-field phenotyping. The combination of two types of treatment (biostimulants and drought) enabled us to evaluate the precision and resolution of the system in investigating the effect of biostimulants on drought tolerance. We analyze and discuss plant behavior at different stages, and assess the penalty and trade-off between productivity and survivability. In this test case, we suggest a protocol for the screening of biostimulants' physiological mechanisms of action.
To meet the food-security demands of an increasing global population, crop yields must double by 2050 (Ray et al., 2013). Despite an increase in crop productivity in the last few decades, the increased rate is not expected to match the demand, mainly due to the negative effects of climate change (abiotic environmental stresses such as drought, temperature extremes and flooding) and degrading soil quality. In fact, commercially grown crops are expected to achieve, on average, only about 50% of their potential yield under field conditions (Hatfield and Walthall, 2015; Foyer et al., 2016). In the last three decades, vast research had been invested in improving plant responses to various stresses. Nevertheless, the bench-to-field transfer rate (ratio of patents to marketed commercial seeds) of abiotic stress-resistant crops is very low, due to the high complexity of dynamic plant–environment interactions (Graff et al., 2013, Dalal et al., 2017).
Physiological phenotyping for crop improvement
The major gap between the successful breeding and yield improvement results from the unpredictable outcome of the complex genotype ◻×◻environment interactions (Miflin 2000; Moshelion and Altman 2015). To date, the major obstacle to bridging this gap has been the lack of an efficient method for identifying and quantifying yield-related traits at early stages of plant growth across vast numbers of plants/genes (Moshelion and Altman 2015, Negin and Moshelion 2017). Another potential bottleneck is the genotype–phenotype gap. The availability of new molecular tools has enhanced the efficiency of classical breeding and crop improvement (Spindel et al., 2015; Bhat et al., 2016; Collard and Mackill 2008; Gosa et al., 2018). To achieve meaningful results in drought tolerance, molecular approaches to crop improvement must be linked to suitable phenotyping protocols at all stages, such as the screening of germplasm collections, mutant libraries, mapping populations, transgenic lines and breeding materials, and the design of OMICs and quantitative trait locus experiments (Salekdeh et al., 2009). Thus, to improve crops and to meet the challenges ahead, the genotypic view and emphasis on genomics need to be balanced by a phenocentric approach with an emphasis on phenomics, to minimize the genotype–phenotype gap (Miflin 2000). The development of a high-resolution, high-throughput diagnostic screening platform for the study of whole-plant physiological performance that serves for phenotypic screening might bridge this gap (Moshelion and Altman 2015).
Indeed, the number of phenotyping facilities has increased dramatically in the last decade. Most of these facilities collect information using robotics and automated image acquisition and analysis (White et al., 2012; Kumar et al., 2015; Ghanem et al., 2015; Fischer et al., 2014; Fiorani and Schurr 2013; Gosa et al., 2018). Nevertheless, the quest for more detailed and in-depth phenotyping of the dynamic genotype◻×◻environment interactions and plant stress responses (in particular during drought) has put the capability of the existing methods into question (Ghanem et al., 2015; Li et al., 2014; Halperin et al., 2017; Rahaman et al., 2015; reviewed by Gosa et al., 2018). Herein, we demonstrate a high-throughput functional phenotyping system (HFPS) composed of gravimetric systems that enable us to compare plants' dynamic responses to different ambient conditions in dynamic environments, due to its direct and simultaneous measurement of the yield-related physiological traits of all plants under several treatments.
Phenotyping for biostimulants in drought response
Apart from the traditional strategies to improve crop productivity under an uncertain environment and abiotic stress, an alternative approach is evolving. This approach considers the use of organic molecules, externally applied to the plant at low concentrations, to stimulate many aspects of growth and development, pathogen defense, stress tolerance and reproductive development. These organic molecules, collectively termed biostimulants, have become more and more common in the global market in the last two and a half decades (reviewed by Yakhin et al., 2017). Biostimulants have been defined in many different ways. In the scientific literature, the term biostimulant was first defined by Kauffman et al. (2007) in a peer-reviewed paper, with modifications: "biostimulants are materials, other than fertilizers, that promote plant growth when applied in low quantities" (reviewed by du Jardin, 2015). However, the definition of biostimulants adopted by the European Biostimulants Industry Council specifies that these materials should not function by virtue of the presence of essential mineral elements, known plant hormones or disease-suppressive molecules (Brown and Saa 2015). Recently, biostimulants were defined by Yakhin et al. (2017) as "a formulated product of biological origin that improves plant productivity as a consequence of the novel, or emergent properties of the complex of constituents, and not as a sole consequence of the presence of known essential plant nutrients, plant growth regulators, or plant protective compounds." However, due to their complex composition and diversity, biostimulants are classified differently by different research groups. Many categorize biostimulants based on the natural raw materials used, the origin of their active ingredients and modes of action, inclusion or exclusion of microorganisms, and/or mode of action of the biostimulant (Ikrina and Kolbin 2004; Basak 2008; Du Jardin 2012; Bulgari et al. 2015; Yakhin et al., 2017).
Biostimulants are used in all stages of agriculture, namely, in seed treatments, during plant growth, and postharvest. They are applied both as foliar sprays and through the soil. Biostimulants may function in various ways, as comprehensively summarized by Yakhin et al. (2017). Their mechanism of action may comprise activation of nitrogen metabolism or phosphorus release from soils, generic stimulation of soil microbial activity, or stimulation of root growth and enhanced plant establishment. They stimulate plant growth by enhancing plant metabolism, stimulating germination, improving photosynthesis, and/or increasing the absorption of nutrients from the soil, thus increasing plant productivity. Studies have shown a clear protective role of a diverse number of biostimulants against abiotic stress, as reviewed by Van Oosten et al. (2017). Nevertheless, and despite the extensive literature suggesting that biostimulants decrease the effects of abiotic stress (and in particular drought stress), information regarding their physiological mechanisms of action is limited. The large number of potential candidate biostimulants and the need to elucidate their particular modes of action, optimal concentrations, and types of application, create a substantial bottleneck in the research and development of new biostimulant products. High-throughput phenotyping technologies have been successfully employed in some aspects of plant breeding (Araus and Cairns, 2014; Tardieu et al., 2017), but their application to assess plant biostimulant action has been limited (Petrozza et al., 2014; reviewed by Rouphael et al., 2018), despite the potential benefits of using these technologies in biostimulant product screening (Rouphael et al., 2018).
In this study, we tested the effectiveness of physiological phenotyping for understanding the physiological 'mode of action' of biostimulant activity on the whole plant's drought response. We tested the impact of biostimulants on several quantitative yield-related physiological traits: transpiration rate, growth rate, and water-use efficiency (WUE).
The seeds of pepper (Capsicum annuum var. Rita) were obtained from Zeraim Gedera-Syngenta, Israel. For germination, the seeds were sown in a tray with 10-mL cones filled with commercial growing medium (Matza Gan, Shaham, Givat-Ada, Israel), composed of (w/w) 55% peat, 20% tuff and 25% puffed coconut coir fiber. The trays were well irrigated and kept in the same greenhouse (on side-tables) where the experiment was performed. When the seedlings were 4 weeks old, the growing medium was carefully washed off (to avoid root damage) the seedling roots and the seedlings were immediately transferred to 4-L pots filled with 20/30 sand (Negev Industrial Minerals Ltd., Israel). The numbers 20/30 refer to the upper and lower size of the mesh screen through which the sand was passed (20 = 20 squares across one linear inch of screen), resulting in a sand particle size of between 0.595 and 0.841 mm. The volumetric water content (VWC) of the freely drained substrate, noted as pot capacity, was ~24% (for details, see Experimental Setup section).
The Physiological Phenotyping Platform
The experiment was conducted in June–July 2018 in a commercial-like greenhouse located at the Faculty of Agriculture, Food and Environment in Rehovot, Israel. The greenhouse temperature was controlled using fans that blow air through a moist mattress, keeping it below 38°C. The temperature and relative humidity (RH) were 21–38°C and 30–80%, respectively. The plants were grown under natural light (midday maximum of 1300 μmol◻ s-1 m-2), representative values for natural conditions during the summer in the central part of Israel, including Rehovot. The temperature, RH, photosynthetically active radiation, barometric pressure and vapor pressure deficit in the greenhouse were continuously monitored by Plantarray meteorological station (Plant-Ditech Ltd., Israel).
The functional phenotyping system Plantarray 3.0 platform (Plant-Ditech) was used to monitor the plants' performance during the entire experimental period by controlling the schedule and quantity of irrigation. This platform (Figure 1A and Supplementary Figure 1), which enables performing high-throughput physiological functional phenotyping, includes 72 units of highly sensitive, temperature-compensated load cells that are used as weighing lysimeters. Each unit is connected to its personalized controller, which collects the data and controls the irrigation to each plant separately. An independent controller for each pot enables tight feedback irrigation, based on the plant's transpiration rate. Each controller unit is connected to its neighbor for serial data collection and loading to a server. A pot with a single plant is placed on each load cell (for more details, see Experimental Setup section). The data were analyzed by SPAC-analytics (Plant-Ditech), a designated online web-based software that enables viewing and analyzing the real-time data collected from the Plantarray system.
Experimental setup. (A) View of the randomized experimental setup array consisting of 72 measuring units loaded with Capsicum annuum. (B) Block diagram of the system. Solid circles – well-irrigated plants; empty circles – plants subjected to the drought-recovery scenario. Green – ICL-SW-treated plants, orange – ICL-NewFo1-treated plants, blue – control (no biostimulants) plants. Note that all pot surfaces were covered to reduce evaporation, and irrigation was injected into the soil via multi-outlet drippers to ensure even distribution of fertigation and biostimulants (see Supplementary Figure 1).
Nutrition and Treatments
The composition of the nutrients supplied to the plants by the irrigation system (fertigation) is provided in Table 1. Two different commercial biostimulants were used: seaweed extract (ICL-SW) and a metabolite extract formula (ICL-NewFo1) (both supplied and produced by ICL Specialty Fertilizers, Holland). The biostimulants were prepared in two different containers that were placed on two additional load cells to precisely track their application. The biostimulants were provided to the plants together with the nutrients via the controlled irrigation system (Supplementary Figure 1). The biostimulant concentration and dosage were as per the manufacturer's instructions: ICL-NewFo1 (3.53 mg/L) was provided daily and ICL-SW (0.133 mg/L) once a week.
The experiment lasted 36 days and included two treatments: (i) ample irrigation that aimed to provide non-stressed conditions for the plants throughout the experiment (termed well-irrigated plants), (ii) controlled drought (days 13–30) preceded by a period of ample irrigation, noted as pretreatment (days 1–12), and followed by resumption of ample irrigation (recovery period) (see Figure 2B and Experimental Setup section for details). The treatments included ICL-SW, ICL-NewFo1 or no biostimulants (control). Overall, we had six different experimental groups: three with ample irrigation (control–well irrigated, ICL-SW–well irrigated and ICL-NewFo1– well irrigated) and three groups subjected to drought (control–drought, ICL-SW– drought, and ICL-NewFo1–drought). Each of these groups consisted of 8–12 repetitions (plants) that were arranged in a randomized fashion on the array to ensure uniform exposure of all groups, thereby overcoming the inherent variations in ambient conditions (Figure 1B).
Atmospheric conditions and experimental progress represented as system relative weight throughout the experiment. (A) Daily vapor pressure deficit (VPD) and photosynthetically active radiation (PAR) during 36 consecutive days of experiment. (B) Raw data showing variation in the weight of the plants (relative to their respective initial weight) over the course of the experiment. Each line represents one plant/pot. During the day, the plant transpires and therefore the system loses weight, seen as a slope in the line curves. The pots were irrigated four times per night (each time to pot capacity), seen as peaks in the line curves. The irrigation was followed by drainage to reach water saturation (nighttime baseline). Note that there is no weight loss during the night. The increase in the nighttime baseline (dashed line) every day results from an increase in plant biomass. During pretreatment, all of the plants were well irrigated; from day 13, half of the plants were exposed to differential drought to reach a similar degree of stress, while the other half continued to be well-irrigated till the end of the experiment. On day 31, the water-deprived plants were recovered and continued to be well-irrigated till the end of the experiment. The three colored lines represent a single plant from each of the three groups: blue line – untreated (with biostimulants) control plants; green line – ICL-SW-treated plants; orange line – ICL-NewFo1-treated plants. Note the different drought-response behaviors of the different plants. The inset figure presents system relative weight change of one plant/pot for two consecutive days.
The experimental setup was generally similar to Halperin et al. (2017) with some modifications. Briefly, before the start of the experiment, all load-cell units were calibrated for reading accuracy and drift level under constant load weights (1 kg and 5 kg). Sand was used as the growing substrate because (i) it is an inert substance (sand is free of any nutrients, helping to precisely understand the effect of any chemical applied externally through irrigation), (ii) it is easily washed off the roots (helping to study the roots after the completion of the experiment), and (iii) pot capacity is reached rapidly with a repeatable pattern after each irrigation (at the end of free drainage), helping to study the plants' short-term resilience trait, noted as "night water reabsorption" (see Measurement of Quantitative Physiological Traits section for details). The sand in all of the pots was washed thoroughly several times prior to transfer of the seedlings. Each pot was placed into a Plantarray plastic drainage container on a lysimeter. The container fit the pot size to prevent evaporation. The container has orifices on its side walls at different heights to enable different water levels after drainage of excess water following irrigation. Evaporation from the sand surface was prevented by a plastic cover with a circle cut out at its center through which the plants grew.
Each pot was irrigated by multi-outlet dripper assemblies (Netafim, Israel) that were pushed into the soil to ensure that the medium in the pot was uniformly wetted at the end of the free drainage period following each irrigation event. Irrigations were programmed to run during the night in four consecutive pulses. A 2-h interval was maintained between the first irrigation pulse and the last three. This irrigation regime enabled determining the plants' night water reabsorption, one of the traits indicating plant resilience (see Measurement of Quantitative Physiological Traits section). The amount of water left in the drainage containers underneath the pots at the end of the irrigation events was intended to provide water to the well-irrigated plants beyond the water volume at pot capacity. The associated monotonic weight decrease throughout the day hours was essential for the calculation of the different physiological traits by the data-analysis algorithms.
The drought treatment started on day 13 and ended when the plants' daily transpiration had reached ~80 mL per day. To prevent rapid depletion of the water in the sandy soil in the pots, we conducted gradual deficit irrigation that reduces the irrigation levels every day to 80% of the previous day's transpiration, for each plant separately and independently (using Plantarray's automated feedback irrigation system; Figure 2B).
Measurement of Quantitative Physiological Traits
The following water-relations kinetics and quantitative physiological traits of the plants were determined simultaneously, following Halperin et al.'s (2017) protocols and equations implemented in the SPAC-analytics software: daily transpiration, transpiration rate, normalized transpiration (E), transpiration rate vs. calculated VWC using a piecewise linear fit, and WUE. Cumulative daily transpiration was calculated as the sum of daily transpiration for all 36 days of the experiment. The VWC in the sand medium was calculated by a mass balance between the system weight at pot capacity when free drainage ceases and its concurrent weight.
The estimated plant weight at the beginning of the experiment was calculated as the difference between the total system weight and the sum of the tare weight of pot + drainage container, weight of soil at pot capacity, and weight of water in the drainage container at the end of the free drainage. The plant weight at the end of a growth period (calculated plant weight) was calculated as the sum of the initial plant weight and the multiplication of the cumulative transpiration during the period by the WUE. The latter, determined as the ratio between the daily weight gain and the daily transpiration during that day, was calculated automatically on a daily basis by the SPAC-analytics software. Note that the WUE approached a constant value during the pretreatment period.
The plant's recovery from drought was described by the rate at which the plant gained weight following resumption of irrigation (recovery stage). The physiological trait representing the plant's transpiration recovery from drought was determined as the ratio between the slope of the daily transpiration increase during the recovery phase (recovery slope) and the slope of the daily transpiration decrease during the drought period (stress degree). The slopes were calculated using a linear regression.
The night water reabsorption trait was determined as the difference in system weight between the end of the last and first irrigations of a given irrigation event (i.e. single night), representing the water absorbed by the plant during the very short period when transpiration is practically negligible. This calculation is based on the fact that the drainage of surplus water in sand is rapid and pot capacity is reached prior to the subsequent irrigation (Supplementary Figure 2). We considered the plants' short-term water reabsorption capability during the recovery stage to be an additional physiological trait representing the plant's resilience to drought. Note that the water reabsorption by the plant during the night hours was normalized to its weight.
The recovery stage lasted 6 days, after which the experiment was stopped. As pepper is an indeterminate plant, it did not reach its full yield capacity. Consequently, the experiment was terminated at this stage as the treatment conducted to that point had a direct effect on the existing fruit. The shoots and fruit were harvested from ~10-week-old plants, irrespective of their size, in the early morning hours. The fresh shoot weight was calculated by the system as the difference in actual gravimetric weight between the day of shoot harvest at 0400 h (at the end of the last irrigation) and the following day at the same time. The fruit were collected from the harvested shoot and counted. The fruit and shoots (without fruit) were weighed when a constant weight had been reached during drying in a hot air oven at 60°C. The roots were collected from the pots, washed thoroughly to remove the sand particles, and dried in a hot air oven at 60°C until no further reduction in weight was measured, and finally weighed. The total dry plant weight is the sum of dry shoot weight, dry root weight and dry fruit weight.
Means were compared using analysis of variance (ANOVA) and Student's t-test (noted in the figure legends) in JMP Pro 14 software.
A randomized experimental design was performed to quantitatively compare the impacts of two biostimulants (seaweed extract ICL-SW and metabolite formula ICL-NewFo1) on the plant's key physiological traits. The effects of the two biostimulants were compared to controls (no biostimulant) under two irrigation scenarios: (i) well irrigated, and (ii) drought stress starting with a well-irrigated period, then a controlled drought phase and a successive recovery period (Figure 2B).
Biostimulants Affect Plant Water Loss
Daily transpiration increased gradually for all six groups during the well-irrigated period (pretreatment; Figure 3A). Conversely, daily transpiration and VWC in the pot gradually decreased throughout the drought period that started on day 13 of the experiment (Figures 3A and B, respectively). Daily transpiration and VWC and increased sharply upon irrigation resumption on day 31 of the experiment (recovery period) (Figures 3A and B, respectively). The physiological drought point (defined as the soil VWC value that begins to limit transpiration rate [critical VWC, θcritical (θc)]) was determined for the plants subjected to drought (Figure 3C). A θc = 0.15 was obtained for the control and two biostimulant treatments, but due to the different pattern of VWC decrease in the ICL-SW-treated plants compared to the other two groups (Figure 3B), they reached θc on different days. The θc for the control and ICL-NewFo1-treated plants was reached on day 22.5, and on day 21 for the ICL-SW-treated plants (Figure 3B,C). The impact of drought on the daily transpiration rate pattern of the treated and untreated plants relative to that of the three well-irrigated groups is illustrated in Figure 3D for days 27–29, revealing that the ICL-SW-treated plants experienced a significantly lower midday (between 1200 and 1400 h) transpiration rate under drought but reached a significantly higher transpiration rate under full irrigation (Figure 3E). Under ample irrigation, the ICL-NewFo1-treated plants had a significantly higher transpiration rate than the control plants, and a similar reduction in transpiration rate under drought (Figure 3E).
Effect of biostimulants on plant transpiration. (A) Mean ± SE continuous daily whole-plant transpiration during the entire experimental period (36 days). (B) Mean ± SE calculated volumetric water content (VWC) of the water-deprived plants throughout the experiment. (C) Piecewise linear fit between transpiration rate and calculated VWC for the plants subjected to drought treatment. (D) Mean ± SE diurnal transpiration rate from 0600 to 1900 h during the late drought phase (day 27–29). (E) Mean ± SE transpiration rate for days 27–29 from 1200 to 1400 h. Blue bars – no biostimulant control plants; green bars – ICL-SW-treated plants; orange bars – ICL-NewFo1-treated plants. Solid bars – well-irrigated conditions; stippled bars – drought conditions. Groups were compared using ANOVA by Tukey HSD test. Different letters above columns represent significant differences (P < 0.05). Each mean ± SE is from at least 8 plants per group.
Biostimulants Enhance Biomass and WUE
Transpiration was normalized to biomass by using the calculated plant weight for the entire experimental period (36 days) for all six groups (Figure 4A). The rate of plant weight gain during the well-irrigated period (pretreatment) was similar for all six groups, and decreased during the drought period for the three drought-stressed groups. The rate of weight gain for the latter groups began to increase again during the recovery period (Figure 4A). Nevertheless, the higher rate of weight gain for the ICL-SW-treated plants during this latter period resulted in significantly higher dry shoot biomass than for controls at the end of the experiment, probably due to the cumulative effect of this trend (Figure 4B). The correlation between shoot dry biomass and cumulative daily transpiration, which is, in fact, the dry-weight-related WUE, was relatively high (R2 > 0.8) for both the well-irrigated and water-deprived plants (Figure 4C). Plant transpiration normalized to plant weight, E (Figure 4D), was low for biostimulant-treated plants under both well-irrigated and drought conditions compared to its value for untreated controls. Here again, the ICL-SW-treated plants showed significantly lowest midday E under drought (in accordance with the transpiration rate, Figure 3E). The higher measured transpiration rates (Figure 3E) and higher dry shoot biomass (Figure 4B) for the biostimulant-treated plants compared to the controls under ample irrigation indicate an improvement in fresh weight-related WUE. However, this improvement (increase of ~18% for ICL-SW-treated and ~14% for ICL-NewFo1-treated plants) was not significant (P-value for ICL-SW was 0.067 and for ICL-NewFo1, 0.16; Figure 4E).
(A) Mean ± SE calculated whole-plant weight during the entire experimental period. (B) Mean ± SE shoot dry weight, harvested at the end of the experiment. (C) Correlation between shoot dry weight and cumulative daily transpiration. (D) Midday mean ± SE E (transpiration rate normalized to plant biomass) for days 27–29 from 1200 to 1400 h. (E) Mean ± SE water-use efficiency (WUE). Blue bars – untreated (with biostimulants) control plants; green bars – ICL-SW-treated plants; orange bars – ICL-NewFo1-treated plants. Solid bars – well-irrigated conditions; stippled bars – drought conditions. Groups were compared using ANOVA by Tukey HSD test and Student's t◻test. Different letters above columns represent significant differences (P < 0.05). Each mean ± SE is from at least 8 plants per group.
Biostimulant Effect on Plant Resilience
The two considered traits for an estimation of the plants' recovery from drought stress, i.e., resilience, were: (i) whole-plant transpiration recovery: the rate at which the daily transpiration increases following irrigation resumption was compared to the rate at which the daily transpiration decreases during the drought period. For the sake of simplicity, both rates were determined as the linear regression of the respective data points (Figure 5A), showing that ICL-SW reduced plant resilience compared to control plants (Figure 5B); (ii) the night water reabsorption (namely, regaining the water that was lost during the day; see Supplementary Figure 2) for the pretreatment and recovery periods, depicted in Figures 5C,D and 5E,F, respectively. The night water reabsorption during the pretreatment period was significantly higher for the biostimulant-treated plants compared to the control, with the highest values for the ICL-NewFo1-treated plants (Figure 5C). The drought stress reduced night water reabsorption capability during recovery for all three groups. Nevertheless, compared to the control, the biostimulants improved the reabsorption capability during recovery, with significantly highest capability for ICL-NewFo1-treated plants (Figure 5E). A similar trend was observed when the night water reabsorption was normalized to the plant weight, with significantly highest reabsorption capability in ICL-NewFo1-treated plants compared to the control (Figures 5D,F).
Effect of biostimulants on plant resilience during recovery. (A) Mean ± SE continuous total whole-plant daily transpiration of drought-treated plants during the entire experimental period of 36 days. Graph shows days from when stress degree and recovery slope were calculated for analysis. (B) Mean ± SE resilience measured as the ratio of the recovery slope (day 31–32) to stress degree (day 18–30). (C) Mean ± SE water reabsorption during pretreatment (day 11–14), and (D) its mean ± SE normalized to calculated plant weight. (E) Mean ± SE water reabsorption during recovery phase (day 33–36), and (F) its mean ± SE normalized to calculated plant weight. Blue bars – untreated (with biostimulants) control plants; green bars – ICL-SW-treated plants; orange bars – ICL-NewFo1-treated plants. Solid bars – well-irrigated conditions; stippled bars – drought conditions. Groups were compared using ANOVA by Tukey HSD test and Student's t◻test. Different letters and asterisk above columns represent significant differences (P < 0.05). Each mean ± SE is from at least 8 plants per group.
Biostimulant Effect on Fruit Number
As pepper plants are indeterminate, we decided to terminate the experiment shortly after recovery, despite the fact that full fruit weight potential had not been reached. Nevertheless, at this stage, fruit set in all groups was assumed to reflect the treatment, as seen in the distribution of the three different fruit sizes (small, medium and commercial) (Supplementary Figure 3). For the well-irrigated plants, 33% of the control fruit reached a commercial size, compared to only 19% of ICL-SW-treated and 14% of ICL-NewFo1-treated plants' fruit. The total number of fruit was counted for all six groups and correlated to cumulative daily transpiration (Figure 6). ICL-SW significantly enhanced the total fruit number under ample irrigation (Student's t-test); however, the ICL-SW-treated plants were significantly affected by the drought relative to their well-irrigated condition (Figure 6A). As similar results were observed for the transpiration rate of these treated plants (Figure 3E), we calculated the correlation between total fruit number and cumulative daily transpiration. The correlation for well-irrigated plants was slightly better (R2 = 0.5) than that for plants subjected to drought (Figure 6B).
Effect of biostimulants on yield. (A) Mean ± SE total fruit number per plant. (B) Correlation between mean ± SE total fruit number and cumulative daily transpiration. Blue bars – untreated (with biostimulants) control plants; green bars – ICL-SW-treated plants; orange bars – ICL-NewFo1-treated plants. Solid bars – well-irrigated conditions; stippled bars – drought conditions. Groups were compared using ANOVA by Tukey HSD test and Student's t◻test. Different letters and asterisk above columns represent significant differences (P < 0.05). Each mean ± SE is from at least 8 plants per group.
Advantages of the HFPS in Pre-Field Screening for Promising Candidates and Effective Treatments
Most high-throughput phenotyping facilities are based on remote sensing or imagers (Araus et al., 2018), and are expected to show improved temporal phenotypic resolution. However, their effective spatial resolution is still relatively limited to morphological and indirect physiological traits. In addition, measurements are not taken simultaneously; given the fact that the plant response to a dynamic environment is dynamic, simultaneous measurements are needed for comparative analyses. Thus, the selection of candidates and treatments for testing remains a challenge. High-throughput phenotyping platforms in greenhouses have the advantage of characterizing individual pot-grown plants without the constraints imposed by overlapping canopies from neighboring plants or variable climatic conditions that can hamper data-acquisition accuracy (Fernandez et al., 2017). Although an effective approach would be to screen biostimulants for their mode of action from "field to greenhouse", the "greenhouse-to-field" approach is not only time- and cost-effective but also narrows the number of products to be tested later under field conditions (Rouphael et al., 2018). On the other hand, the accuracy of controlled growth environments in targeting genetically complex traits is questionable, as phenotypes from spaced pots and controlled conditions are poorly correlated with phenotypes in field environments, where plants compete with their neighbors (Nelissen et al., 2014; Poorter et al., 2016; Fernandez et al., 2017; Fischer et al., 2018; Rebetzke et al., 2018). We suggest that to better correlate a plant's response to its environment, it is important to phenotype under conditions that are as similar as possible to those in the field. Thus, an efficient pre-field phenotype-screening experiment should offer the possibility to predict yield penalties in response to environmental adversity in the early stages of plant growth. Choice of the appropriate phenotyping method is one of the key components in pre-field screens (phenotyping) for complex traits under abiotic stress conditions (reviewed by Negin, 2017). This improves the chances of the selected candidates performing well under field conditions. The following principles, tested in this study, may contribute to this goal.
Conducting experiments under semi-controlled conditions that are typical of farmers' growing facilities (see Figure 2A). The spaces between the pots were kept to a minimum to mimic commercial growth conditions.
Using a truly randomized experimental design to mimic the biological variability, as well as the spatial and temporal variability in ambient conditions in the growth facility. Here, we used a randomized experimental design with one-to-one (1:1) plant– [sensors+controller] units which enabled running an independent feedback irrigation scenario for every plant (Figure 1, Supplementary Figure 1). Each controller was associated with a dual-valve system that allowed creating a specific combination of irrigation scenarios independently for each plant. Moreover, it overcame many of the experimental artifacts that could result from the "pot effect" (Gosa et al., 2018) by using controlled-deficit irrigation that reduced the irrigation levels every day to 80% of the previous day's transpiration (for each plant separately and based on its individual performance), preventing rapid reduction in pot soil water content. This created a relatively homogeneous drought scenario for all plants (Figure 2).
Conducting comparative and continuous measurements for all plants' water-relations kinetics (direct physiological traits) in response to the three-phase scenario (control–drought–recovery). This experimental approach offered several advantages in interpreting the plant's interactions with the environment as it compared each plant's profile to its own profile in the different phases (Figure 3A) as well as to all other plants' profiles in the experiment, simultaneously. Moreover, clarity of the stress conditions, providing the ability to repeat the exact stress scenario in other experiments, is also important when studying a desired stress-related trait. The trait in question might respond differently in plants showing different types of drought tolerance under different drought conditions (Negin and Moshelion, 2017). Therefore, for better resolution of the drought response in pot experiments, the severity and strategy of the drought stress must be well defined. To achieve a quantitative and cooperative response of the plants to a combination of biostimulants and drought treatment, we divided the experiment into three phases: before drought (pretreatment), during drought which was defined by the physiological drought point (θc), and recovery immediately after drought (resilience).
High temporal and spatial resolution of the plant–environment interactions. The ultimate trait, yield, is a cumulative trait, measured at the end of the experiment and reflecting the sum of all genetic and ambient parameters affecting the plant throughout the season. This calls for high temporal resolution and continuous measurement of the dynamic plant–environment response. The high-capacity data acquisition (480 measurements per day) of the HFPS enabled tight measurements of the plant's response to the ambient conditions, and also comparing plant performances at different time points during the day (i.e., different ambient conditions), where the differences between the treatments became significant (Figures 3 D,E).
In this study, we show that the HFPS might be an efficient diagnostic tool for a better understanding of pre-field plant x environment interactions by studying water-related physiological mechanisms under different phases of control–drought–recovery scenarios. In this pursuit, we used biostimulants as a test case due to their reported impact on the plant stress response (Van Oosten et al., 2017). Nevertheless, information on the influence of biostimulants on physiological mechanisms of action is relatively scarce. Moreover, the use of biostimulants, as with other biotic and abiotic screening studies, is highly complex, and thus identification and characterization of their activity is time-consuming and expensive, as it requires large-scale field experiments. The combination of the two types of treatment (biostimulants and drought) enabled us to evaluate the benefits of the HFPS in investigating the mechanistic effect of biostimulants in drought tolerance.
Quantitative Comparison to Understand the Interactions between Key Physiological Traits and Their Trade-Offs
Both biostimulants increased plant transpiration rate under ample irrigation compared to control plants (Figure 3). However, while the impact of ICL-SW translated to productive mechanisms (faster growth rate and later, higher fruit number), the impact of ICL-NewFo1 translated to survivability mechanisms (lower transpiration rate under drought and faster recovery—i.e., better resilience). Interestingly, the sensitivity of the plants to drought in terms of the critical VWC drought point (θc), at which a further reduction in water content reduces transpiration, remained the same, possibly due to similar root sizes (Supplementary Figure 4). This is because under water-deficit conditions, when water becomes less available to the roots, plants with smaller roots will be limited more quickly (early θc) than plants with larger roots (reviewed by Gosa et al., 2018). Thus θc might be useful in predicting root phenotype. Nevertheless, as soon as the plants were exposed to drought, the two biostimulants induced different response patterns (beyond θc): ICL-NewFo1 treatment resulted in a gradual reduction in transpiration rate, reaching a minimum at a relatively lower VWC than the control and ICL-SW-treated plants (Figure 3C). Again, this type of behavior could explain the better survivability of the ICL-NewFo1-treated plants during the drought period.
In addition, the functional phenotyping approach revealed good correlations among key agronomical traits within the short study period. For example, our results revealed a high correlation between plant total dry weight and plant weight calculated by the system (Supplementary Figure 5). The fact that the system can calculate the plant biomass throughout the experiment is highly beneficial as it enables a direct measurement of the whole-plant biomass gain, in real time and in a non-destructive manner. In addition, key agronomic traits (such as grain yield) are linearly correlated to water consumption (WUE, reviewed by Gosa et al., 2018). Indeed, throughout the entire experiment, water taken up by the system (representing plant agronomic WUE, slope in Figure 4C) was almost identical to the fresh-weight WUE (taken on the first few days of the experiment; Figure 4E). Namely, ~0.003 g of plant dry weight per 1 mL of transpired water vs. ~0.035 g of plant fresh weight per 1 mL of transpired water, respectively, showing a ratio of 1:10, which is similar to the ratio between the fresh and dry shoot weight (Supplementary Figure 6). This trait is highly beneficial as it enables use of the fresh-weight WUE (determined on the first few days of the experiment), which is calculated for the entire growth period rather than the dry-weight WUE. Interestingly, these results also indicate that WUE is nearly constant throughout the growth period.
Phenotyping Resilience
Resilience is one of the key stress-response traits. Nevertheless, the term "resilience" is being used more and more freely, and with popularity comes confusion; thus, it must assume its broadest definition. Resilience is commonly used to represent resistance, or recovery, or both (Hodgson et al., 2015). Plant stress resilience indicates plant survival and productivity after stress. In this study, we introduced two functional traits to quantify resilience: (i) transpiration recovery rate after stress (return of irrigation) and (ii) the plant's ability to reabsorb water at night during recovery from drought. We found that while the biostimulants did not affect the transpiration recovery rate, they did increase the nighttime water reabsorption ability of both the well-irrigated and recovering plants, compared to the non-treated controls (Figures 5C,E). This phenomenon can be explained by the positive impact on the fresh biomass (Figure 4A), as normalizing the water reabsorption volume to the plant biomass still resulted in higher values of both biostimulant-treated plants compared to the non-treated control (Figures 5E,F). The difference between the water reabsorption of well-irrigated and recovering plants within the same group (i.e., control, ICL-SW or ICL-NewFo1) indicated drought-inflicted tissue damage, thus the night water reabsorption trait can be used as a tool to estimate tissue damage due to stress.
A comparison of the effects of two biostimulants on drought tolerance using a HFPS revealed known and new relationships between physiological traits. The two studied biostimulants (ICL-SW and ICL-NewFo1) improved the overall transpiration and biomass gain compared to control plants. However, only ICL-SW improved fruit number (Figure 6A) under ample irrigation, which was significantly reduced when the plants were exposed to drought. This might be explained by the shift in resource allocation from the reproductive to non-reproductive or vegetative biomass, for survival. A schematic depiction of the behavior of plants treated with biostimulants is given in Figure 7. The behavior can be explained in terms of risk-taking and non-risk-taking behavior. Under optimal conditions, ICL-SW-treated plants (risk-taking) sustained a longer period of higher transpiration rate and thus a longer period of substantial CO2 assimilation, resulting in increased productivity (Figure 7A) compared to the ICL-NewFo1-treated plants. This behavior is advantageous only under well-irrigated conditions or during mild stress, but there is a risk of losing water faster during severe stress (Lin et◻al. 2007; Peng et◻al. 2007; McDowell et◻al. 2008; Sade et◻al. 2009; Moshelion et al., 2015). On the other hand, ICL-NewFo1-treated plants (non-risk-taking) maintain a moderate transpiration rate under optimal conditions, thus not contributing much to their productivity, but resulting in more gradual water loss under drought conditions, thereby reaching the minimal VWC (desiccation) later than the ICL-SW-treated plants, resulting in increased survivability. Thus there is a trade-off between productivity and survivability for the ICL-SW- and ICL-NewFo1-treated plants, respectively, as depicted in Figure 7B (Moshelion et al., 2015).
Schematic model of plant responses to biostimulants (ICL-NewFo1 – orange line, ICL-SW – green line, untreated – blue line) under drought and recovery (modified from Moshelion et al., 2015). (A) Plant productivity vs. intensity and duration of stress. Under conditions characterized by an ample water supply, ICL-SW-treated plants have a higher transpiration level than ICL-NewFo1-treated and control plants, and thus higher levels of productivity (e.g., photosynthesis) (Phase I). As mild water stress develops (Phase II), ICL-SW-treated and control plants reduce transpiration steeply with decreasing water availability, limiting productivity. In contrast, ICL-NewFo1-treated plants show a relatively gradual decrease in transpiration and productivity as a trade-off to the decline in leaf water potential and relative water content. Nevertheless, after the initial drought (Phase II), their productivity may still be higher than that of ICL-SW-treated and control plants which have already reached minimal productivity. As drought stress becomes more severe (Phase III), the transpiration values and productivity of ICL-NewFo1-treated plants continue to decline to their minimum. (B) Evaluation of recovery from drought is an important step in assessing drought resilience. It reveals the plant's resistance to desiccation and ability to recover its pre-stress productivity, reflecting the extent of the damage caused by severe drought, such as cavitation or leaf/root loss. Both the ICL-SW-treated and control plants recover slowly compared to the ICL-NewFo1-treated plants. ICL-NewFo1 contributes to drought resistance by inducing more gradual water loss and resilience, thus contributing less to plant productivity and more to plant survivability. However, ICL-SW induces relatively faster water loss, and only increases productivity under optimal conditions while having no effect on the survivability of the plants under drought.
We suggest that these two different stimulation approaches should be implemented in different agricultural practices. Thus, the beneficial stimuli of ICL-SW may be implemented in controlled-irrigated crops, while the resilience impact of ICL-NewFo1 can be implemented for non-irrigated crops that are naturally subjected to the uncertainty of the environment. This survivability trait may also be very beneficial for annual crops (e.g., vines, turfs and silviculture) which need to overcome longer stress periods between seasons.
RW and MM conceived the original research plan. AD, NH and IS performed the experiments. RB adapted the algorithms suggested by Halperin et al. (2017) to the calculations performed in this manuscript. AD, RB and MM analyzed the data. AD and MM wrote the manuscript. All authors were involved in reviewing and editing the manuscript.
This work was supported by a grant from Israel Chemicals Ltd. (grant no. 0336396).
The authors declare that the research was conducted independently and in the absence of any commercial relationships that could be construed as a potential conflict of interest.
AD and MM gratefully acknowledge the United States–Israel Binational Science Foundation (BSF) for the postdoctoral scholarship awarded to AD.
Ahan Dalal: ahan.dalal{at}mail.huji.ac.il, Ronny Bourstein: ronny.bourstein{at}mail.huji.ac.il, Nadav Haish: nadohaish{at}gmail.com, Itamar Shenhar: itamar.shenhar{at}mail.huji.ac.il, Rony Wallach: rony.wallach{at}mail.huji.ac.il
Araus, J.L. and Cairns, J.E., 2014. Field high-throughput phenotyping: the new crop breeding frontier. Trends in plant science, 19(1), pp.52–61.
Araus, J.L., Kefauver, S.C., Zaman-Allah, M., Olsen, M.S. and Cairns, J.E., 2018. Translating high-throughput phenotyping into genetic gain. Trends in plant science.
H. Gawrońska
Basak, A. (2008). "Biostimulators – definitions, classification and legislation," in Monographs Series: Biostimulators in Modern Agriculture. General Aspects ed H. Gawrońska (Warsaw: Wieś Jutra), 7–17.
Bhat, J.A., Ali, S., Salgotra, R.K., Mir, Z.A., Dutta, S., Jadon, V., Tyagi, A., Mushtaq, M., Jain, N., Singh, P.K. and Singh, G.P., 2016. Genomic selection in the era of next generation sequencing for complex traits in plant breeding. Frontiers in genetics 7, p.221.
Brown, P. and Saa, S., 2015. Biostimulants in agriculture. Frontiers in plant science 6, p.671.
Bulgari, R., Cocetta, G., Trivellini, A., Vernieri, P., and Ferrante, A. (2015). Biostimulants and crop responses: a review. Biol. Agric. Hortic. 31, 1–17. doi: 10.1080/01448765.2014.964649
Collard, B.C. and Mackill, D.J., 2008. Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society of London B: Biological Sciences 363(1491), pp.557–572.
Dalal, A., Attia, Z. and Moshelion, M., 2017. To Produce or to Survive: How Plastic Is Your Crop Stress Physiology?. Frontiers in plant science 8, p.2067.
Du Jardin, P. (2012). The Science of Plant Biostimulants - A Bibliographic Analysis, Ad hoc Study Report. Brussels: European Commission. Available online at: http://hdl.handle.net/2268/169257 (Accessed April 25, 2013).
du Jardin, P., 2015. Plant biostimulants: definition, concept, main categories and regulation. Scientia Horticulturae 196, pp.3–14.
Fernandez, M.G.S., Bao, Y., Tang, L. and Schnable, P.S., 2017. A high-throughput, field-based phenotyping technology for tall biomass crops. Plant physiology pp.pp-00707.
Fiorani, F. and Schurr, U., 2013. Future scenarios for plant phenotyping. Annual review of plant biology 64, pp.267–291.
Fischer, R.A., Byerlee, D. and Edmeades, G., 2014. Crop yields and global food security. ACIAR: Canberra, ACT pp.8–11.
Fischer, R.A. and Rebetzke, G.J., 2018. Indirect selection for potential yield in early-generation, spaced plantings of wheat and other small-grain cereals: a review. Crop and Pasture Science 69(5), pp.439–459.
Ghanem, M.E., Marrou, H. and Sinclair, T.R., 2015. Physiological phenotyping of plants for crop improvement. Trends in Plant Science 20(3), pp.139–144.
Gosa, S.C., Lupo, Y. and Moshelion, M., 2018. Quantitative and comparative analysis of whole-plant performance for functional physiological traits phenotyping: New tools to support pre-breeding and plant stress physiology studies. Plant Science.
Halperin, O., Gebremedhin, A., Wallach, R. and Moshelion, M., 2017. High[throughput physiological phenotyping and screening system for the characterization of plant–environment interactions. The Plant Journal 89(4), pp.839–850.
Hodgson, D., McDonald, J.L. and Hosken, D.J., 2015. What do you mean,'resilient'?. Trends in ecology & evolution 30(9), pp.503–506.
Ikrina, M. A., and Kolbin, A. M. (2004). Regulators of Plant Growth and Development, Vol. 1, Stimulants. Moscow: Chimia.
Kumar, J., Pratap, A. and Kumar, S. eds., 2015. Phenomics in crop plants: trends, options and limitations (No. 8, p. 296). Springer India.
Li, L., Zhang, Q. and Huang, D., 2014. A review of imaging techniques for plant phenotyping. Sensors 14(11), pp.20078–20111.
Lin, W., Peng, Y., Li, G., Arora, R., Tang, Z., Su, W. and Cai, W., 2007. Isolation and functional characterization of PgTIP1, a hormone-autotrophic cells-specific tonoplast aquaporin in ginseng. Journal of experimental botany 58(5), pp.947–956.
McDowell, N., Pockman, W.T., Allen, C.D., Breshears, D.D., Cobb, N., Kolb, T., Plaut, J., Sperry, J., West, A., Williams, D.G. and Yepez, E.A., 2008. Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought?. New phytologist 178(4), pp.719–739.
Miflin, B., 2000. Crop improvement in the 21st century. Journal of experimental botany 51(342), pp.1–8.
Moshelion, M. and Altman, A., 2015. Current challenges and future perspectives of plant and agricultural biotechnology. Trends in biotechnology 33(6), pp.337–342.
Moshelion, M., Halperin, O., Wallach, R., Oren, R.A.M. and Way, D.A., 2015. Role of aquaporins in determining transpiration and photosynthesis in water-stressed plants: crop water◻use efficiency, growth and yield. Plant, Cell & Environment 38(9), pp.1785–1793.
Negin, B. and Moshelion, M., 2017. The advantages of functional phenotyping in pre-field screening for drought-tolerant crops. Functional Plant Biology 44(1), pp.107–118.
Nelissen, H., Moloney, M. and Inzé, D., 2014. Translational research: from pot to plot. Plant biotechnology journal 12(3), pp.277–285.
Peng, Y., Lin, W., Cai, W. and Arora, R., 2007. Overexpression of a Panax ginseng tonoplast aquaporin alters salt tolerance, drought tolerance and cold acclimation ability in transgenic Arabidopsis plants. Planta 226(3), pp.729–740.
Petrozza, A., Santaniello, A., Summerer, S., Di Tommaso, G., Di Tommaso, D., Paparelli, E., Piaggesi, A., Perata, P. and Cellini, F., 2014. Physiological responses to Megafol® treatments in tomato plants under drought stress: a phenomic and molecular approach. Scientia Horticulturae 174, pp.185–192.
Poorter, H., Fiorani, F., Pieruschka, R., Wojciechowski, T., Putten, W.H., Kleyer, M., Schurr, U. and Postma, J., 2016. Pampered inside, pestered outside? Differences and similarities between plants growing in controlled conditions and in the field. New Phytologist 212(4), pp.838–855.
Rahaman, M., Chen, D., Gillani, Z., Klukas, C. and Chen, M., 2015. Advanced phenotyping and phenotype data analysis for the study of plant growth and development. Frontiers in plant science 6, p.619.
Rebetzke, G.J., Jimenez-Berni, J., Fischer, R.A., Deery, D.M. and Smith, D.J., 2018. High-throughput phenotyping to enhance the use of crop genetic resources. Plant Science.
Rouphael, Y., Spíchal, L., Panzarová, K., Casa, R. and Colla, G., 2018. High-Throughput Plant Phenotyping for Developing Novel Biostimulants: From Lab to Field or From Field to Lab?. Frontiers in plant science 9.
Sade, N., Vinocur, B.J., Diber, A., Shatil, A., Ronen, G., Nissan, H., Wallach, R., Karchi, H. and Moshelion, M., 2009. Improving plant stress tolerance and yield production: is the tonoplast aquaporin SlTIP2; 2 a key to isohydric to anisohydric conversion?. New Phytologist 181(3), pp.651–661.
Salekdeh, G.H., Reynolds, M., Bennett, J. and Boyer, J., 2009. Conceptual framework for drought phenotyping during molecular breeding. Trends in plant science 14(9), pp.488–496.
Spindel, J., Begum, H., Akdemir, D., Virk, P., Collard, B., Redona, E., Atlin, G., Jannink, J.L. and McCouch, S.R., 2015. Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines. PLoS genetics 11(2), p.e1004982.
Tardieu, F., Cabrera-Bosquet, L., Pridmore, T. and Bennett, M., 2017. Plant phenomics, from sensors to knowledge. Current Biology 27(15), pp.R770–R783.
Van Oosten, M.J., Pepe, O., De Pascale, S., Silletti, S. and Maggio, A., 2017. The role of biostimulants and bioeffectors as alleviators of abiotic stress in crop plants. Chemical and Biological Technologies in Agriculture 4(1), p.5.
White, J.W., Andrade-Sanchez, P., Gore, M.A., Bronson, K.F., Coffelt, T.A., Conley, M.M., Feldmann, K.A., French, A.N., Heun, J.T., Hunsaker, D.J. and Jenks, M.A., 2012. Field-based phenomics for plant genetics research. Field Crops Research 133, pp.101–112.
Yakhin, O.I., Lubyanov, A.A., Yakhin, I.A. and Brown, P.H., 2017. Biostimulants in plant science: a global perspective. Frontiers in plant science 7, p.2049.
Yoo, C.Y., Pence, H.E., Hasegawa, P.M. and Mickelbart, M.V., 2009. Regulation of transpiration to improve crop water use. Critical Reviews in Plant Science 28(6), pp.410–431.
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You are going to email the following A High-Throughput Physiological Functional Phenotyping System for Time- and Cost-Effective Screening of Potential Biostimulants
Ahan Dalal, Ronny Bourstein, Nadav Haish, Itamar Shenhar, Rony Wallach, Menachem Moshelion


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The Relevance of Faith Actors' Partnerships for the Global Compact on Refugees
Forum on the Partnership Principle in the UN Global Compact on Refugees
Contribution by Stephanie Acker, School of Transnational Governance, European University Institute & Leiza Brumat, Migration Policy Centre, European University Institute
The Global Compact on Refugees (GCR) cements a call to the international community: the refugee response needs everyone. In 2018 nearly every country joined in adopting[i] the GCR (with exception of Hungary and the United States opposing it and abstentions from Eritrea, Liberia, and Libya). They affirmed a commitment to leveraging civil society and partnering with all relevant stakeholders, including faith-based actors and organizations. This marked the first time that faith-based actors were explicitly included in an international agreement comprised of most countries in the world.
Faith actors include faith-based organizations, local faith communities, and faith leaders (see Box 1 with the definitions) and they have a long history of involvement with forcibly displaced populations (Ferris, 2005; Milner and Klassen, 2021). The GCR uses the terms faith-based organizations and faith-based actors largely interchangeably. We use the term faith actors from UNHCR's 2014 partnership guidance, as a more precise phrase to encompass the diversity of various faith actors. There is evidence that faith actors alongside other members of civil society, have for centuries 'led responses to displacement' (Milner and Klassen, 2021, p.1) and that they have played an 'important role…in humanitarian responses in all regions of the world [emphasis added]' (Ferris, 2011, pp.607–608). Faith actors play multiple roles in refugee protection—from conflict prevention, to immediate aid, to integration and self-reliance. Their ability to play a role in all of these areas makes them a unique and critical partner (Thomson, 2014; Joint Learning Initiative on Faith and Communities, 2018; Sulewski, 2020; UNHCR, 2014). Specifically in the Global South, which hosts most of the world's refugees (Adamson and Tsourapas 2020 ), faith actors are a widely accepted part of both public and private life, have a significant role in development, and have played key roles in refugee governance (Clarke, 2006; Haynes, 2013; Wurtz and Wilkinson, 2020). They often have high-trust from the community, are 'widely present in all parts of a country' and 'often remain long after international attention has faded, and funding has declined.' (UNHCR, 2014, p.8).
Box 1: Definition of Faith Actors*
Source: Summary from UNHCR's 2014 Partnership Note On Faith-Based Organizations, Local Faith Communities, and Faith Leaders.
Despite playing key roles in refugee protection, there has been 'surprisingly little academic research' on faith actors' roles in humanitarian spheres (Ferris, 2011, p.607). As Carbonnier, (2013, p.6) argues,
the lack of attention to religion and faith in development research and policy […] stands in stark contrast to the paramount role played by religion in the daily lives of individuals and communities, particularly in the most active field of international development cooperation, the developing world.
There is even less research on the impact of the GCR's broader call for civil society's participation, and more specifically faith actors' participation (Milner and Klassen, 2021; Sulewski, 2020). While faith actors have a long history of engagement in refugee protection and are named as a relevant stakeholder in the GCR, we know little about the formal role they have in achieving the objectives of the GCR and if their relevance is recognized by other stakeholders.
This blog contribution sheds light on the role of faith actors in the implementation of a key international agreement: the GCR. To do this, we ask whether and how the GCR's call for partnering with faith actors is legitimizing their involvement in refugee protection?
To develop our analysis, we draw from existing literature on faith actors in humanitarian and refugee response, UNHCR publications, and the empirical data from the ASILE project's country case studies in Bangladesh, Brazil, Canada, Jordan, Turkey, and South Africa. We analyse how norms are globalized and localized and what is the role of faith actors in this process. After this, we trace the evolution of UNHCR initiatives that have normalized faith actors' roles in refugee governance on a global scale. We then critically assess how the GCR's call for partnering with faith actors is being globalized and adapted to local contexts.
Faith Actors: Between globalization and localization processes.
There is rich literature and debate on how international and domestic norms influence each other (Acharya, 2004; Brumat, Geddes, and Pettrachin, 2021). The literature identifies two main processes: globalization, the process by which international norms are incorporated into domestic standards, and localization, which assesses how global norms are adapted into domestic contexts (Brumat, Geddes, and Pettrachin 2021).
It is commonly argued that international organizations (IOs) play a key role in 'disseminating new international norms' and 'teach[ing] states new norms of behavior' (Finnemore and Sikkink, 2001, p.401). However, more contemporary studies have emphasized that states and local actors are not 'simply passive recipients in either accepting or rejecting international norms' and obligations under international law but there is a constant back and forth occurring (Hellmüller, 2020, p.409).
Subsequently, in the processes of globalization and localization, there is an interplay between local, civil society actors and international actors, particularly IOs. Research demonstrates that civil society can act as 'agents of normative change' or 'brokers' (Hönke and Müller, 2018) in how norms get adapted and translated into local practice and that faith actors are a part of civil society who are especially influential in this process (Boesenecker and Vinjamuri, 2011). Characterized by deeply held conceptions of justice and peace, studies show that in some contexts and particularly in areas of limited statehood (ALS) and in some global South countries, faith actors play a leading role as international norm 'makers' and 'adapters' (Boesenecker & Vinjamuri, 2011). For example, their pivotal role in setting and adapting international human rights norms in peacebuilding processes had been documented in the cases of post-apartheid South Africa and and Northern Ireland.
We will now look at whether and how a norm of partnering with faith actors in international refugee governance has evolved.
A global norm of partnering with faith actors in refugee governance
The role of and view towards faith actors in refugee protection has evolved. These changes have been well documented by (Barnett and Stein, 2012; Clarke, 2006; Haynes, 2013; Sulewski, 2020; Wilkinson, 2018; Wurtz and Wilkinson, 2020). Over the course of the 20th century, as the humanitarian field became increasingly professionalized, more formal legal and institutional frameworks began to replace the more informal humanitarian leadership of faith organizations. This eventually resulted in faith actors being biased against by secular organizations; UN agencies specifically were sceptical of engaging with religious organizations (UNHCR, 2014, p.20). Beginning after the Cold War, there was broad resurgence in recognizing the role of civil society, and specifically the role of faith actors and while some of this resulted from the increasing recognition of living in a post-secular world where faith is accepted, there was an increasing 'institutionalized presence' of faith actors, across the entire UN system (Haynes, 2013, p.9).
One way we can understand the role of faith actors in the translation and adaptation of global norms is through the actions and initiatives of the UN, and in this case specifically through UNHCR. Over the past decade, UNHCR publications and forums demonstrate the evolving recognition of faith actors' role in the modern-day refugee response. Figure 1 (see below) details a timeline of such evolution in UNHCR publications and events.
Figure 1: Timeline of Key UNHCR initiatives on partnering with faith actors
Source: Summary of UNHCR publications and initiatives involving faith actors compiled by the authors.
The active recognition of faith actors arguably began in 2012 when UNHCR's annual forum was dedicated to discussing this topic. The tenor of the gathering however was one of cautious intrigue; faith actors' roles needed to be justified, partnerships with them needed guidance. But, by 2016 and 2018, when the international community affirmed the New York Declaration and the GCR respectively, no specific justification was needed; instead, faith actors appear in the texts seemingly on par with other civil society organizations. Formal publications by UNHCR after the GCR helped to further elaborate and formalize the roles they could play (for example, the Guide to Action (Wilkinson et al., 2019) and the Policy Brief (Joint Learning Initiative on Faith and Communities, 2018). Come 2021, almost a decade later, when UNHCR further institutionalized faith actors in establishing the Multi-Religious Council of Leaders, UN High Commissioner for Refugees Filippo Grandi described faith actors as 'key' in refugee protection (UNHCR, 2020, para.4).
Thus, while faith actors have played a role in refugee protection for decades, their institutionalization and formal recognition as global governance actors is quite recent (see figure 2 below). The bottom-up process through which this occurred demonstrates both a globalization and localization of their role. As international norms and institutions gradually incorporated faith actors who were already informally diffused, especially in the Global South, their role became 'globalized'—incorporated into domestic standards (Brumat, Geddes, and Pettrachin, 2021, p.2). At the same time, we hypothesize that as faith actors' legitimacy on a global scale increase, their local involvement in refugee governance will do so as well, giving them a role in localization—adapting international norms and standards. Figure 2 models this hypothesized co-constitutive, simultaneous process. We will look at some empirical examples in the next section.
Figure 2: Hypothesized cycle of localization local-global norm development
Beginning at local practice
Source: Authors' elaboration
Globalizing and localizing refugee protection and partnerships with faith actors: what about the GCR?
Building on our hypothesized cycle, we will look at how the formalization of faith actors' role in international refugee governance is increasing their role in local refugee protection. The fieldwork that we have developed in the ASILE project shows an uneven picture. We interviewed officials representing IOs, various levels of government, civil society, and FBOs in six countries: in Bangladesh, Brazil, Canada, Jordan, Turkey, and South Africa. The focus of interviews was on assessing how the GCR was being implemented at a country-level and who key actors were as part of that process. Here we provide two examples of how the GCR is being globalized or localized and the role of faith actors as translators in those processes.
In both Brazil and South Africa, faith actors' role in refugee protection was highlighted. In Brazil, FBOs, in particular Caritas and the Scalabrinian Sisters, play a key role in the process of refugee status determination because they do the initial processing of the refugee status request they assess people to fill in the forms and make their case and by doing this, they are the ones who do an initial selection of who can apply to refugee status (Jubilut and Apolinàrio, 2008). In the context of Venezuelan forced displacement, the worst forced displacement crisis in the history of South America, it was a FBOs that partnered with UNHCR and successfully pushed for the group recognition of Venezuelans as refugees:
We worked for around a year in the recognition of Venezuelans as refugees. We argued, insisted, we showed the reasons [why we had to do this|, we analysed… we insisted so that the government would accept the serious and generalized violation of human rights in Venezuela. For me, it was a conquer, but the government didn't want it. […] now we keep pushing so that this decision is extended to [individuals from] other regions of the world, especially where Boko Haram is acting (interview with FBO official in Brazil, December 2020).
Similarly, in South Africa faith actors are attributed to having an expansive role in refugee protection:
there is [a faith organization] who are working at the border between South Africa and Mozambique…with unaccompanied and separated children…and [a] mission… offering pastoral care to migrants and refugees…and it [has] just expanded from this; so in a way…[it] has always meant that there are available links to faith actors…there is also pastoral care actors across the country…[who] first identify or see migrants and refugees and…offer them guidance and assistance…[and there is] great respect for the groundwork done by many kind[s] of small churches in quite rural areas (interview with FBO official in South Africa, January 2022).
However, in both countries, despite their recognized roles in refugee protection broadly, there was not an equal recognition of their roles specifically in achieving the objectives of the GCR. Some faith actors acknowledged the GCR as 'guidelines' and not really a new norm that is resulting in increased partnerships and activities to improve refugee protection. In the case of Brazil, this is because 'the government presents proposals and data as part of the implementation of the GCR, but many of these things were already implemented in Brazil' (interview with FBO official in Brazil, December 2020). In South Africa, despite having 'powerful faith lobby' and 'a clear connection between high-level politicians and faith actors' (interview with FBO official in South Africa, January 2022), faith actors were not otherwise described as meaningfully involved in the formal country-level initiatives around of the GCR.
One of the powerful things that I saw…with the Global Compact of Refugees, it was the way in which UNHCR really engaged far more than just their implementing partners in country, to try and find ways to make the Global Compact … more real at a country level…Usually previously … UNHCR mainly would only interact with their implementing partners. And so, it was kind of a branching out for them and that was quite exciting to see… it was a something …[to] really bring people together. And so…when the pledges were made… there was a group pledge that was done as well as these individual pledges…. [but] I am actually not sure, whether many of the faith-based actors… signed pledges… it has been more civil society organizations and then the private sector (interview with FBO official in South Africa, January 2022).
In Turkey, Canada, Bangladesh, and Jordan, while the role of faith actors in refugee protection has been documented (Aslıhan Tezel Mccarthy, 2017; Barbour, Fan, and Lewa, 2021; Bompani, 2015; Fiddan-Qasmiyeh, 2020; Mencütek, 2020; Mulholland, 2017), and their role was mentioned in some of the ASILE case study interviews, interviewed actors did not highlight faith actors in any further way to draw conclusions about how the GCR was impacting the prominence of and partnership with faith actors. For example, while it is documented that in fact faith actors play a prominent role in Canada's private sponsorship program, beyond being mentioned this was not emphasized or expanded on by interviews conducted with officials in Canada. Thus, it is likely that the biggest conclusion we can draw is the sheer absence of faith actors in the interviews; the GCR might formally call for partnerships with faith actors, but in these case studies, there are not local signs of this formalisation. In line with recent ASILE findings, we can hypothesise that there is a strong path dependency regarding the role of faith actors in each local, national and regional context, which means that the role that faith actors were playing in each context before the GCR was implemented is very likely to persist. As seen in our research, many times, the GCR is used by governments as a framework to legitimize and 'visibilize' some policies and actions that were already being implemented.
Conclusion: Does it matter that the GCR calls for partnering with faith actors?
The GCR named faith actors as a relevant stakeholder. This ASILE blog post sought to better understand the role of faith actors in refugee response. It traced the evolution of faith actors' increasingly formalized role on the global stage and then sought to understand the impact of this in local refugee protection.
Literature suggests that faith actors have historically have been involved in refugee protection, yet their role was often overlooked. We can see that however at least within the UN system, faith actors in the 21st century have gained ground in their formal recognition and that their incorporation in the GCR has arguably 'globalized' their role (see also figure 1). However, this recognition in the international refugee regime is recent and thus, more research is needed to understand how this norm is playing out at a local level. Currently faith actors are largely absent in the empirical data on the implementation of the GCR (Appleby, 2020; Milner and Klassen, 2021; Sulewski, 2020). Further in the six ASILE country case studies with interviews of close to 100 actors in local refugee response, only actors in two countries—Brazil and South Africa—specifically highlighted the role of faith actors, and when they did it was not formally or seemingly meaningfully connected to GCR implementation.
We surmise that faith actors' roles in refugee protection are not less relevant but that they are still less visible and more informal. We cannot conclude that GCR's naming of faith actors is increasing their role in refugee protection or in adapting global norms into local contexts. As (Wurtz and Wilkinson, 2020) also argue, to better understand the legitimacy of faith actors in international refugee governance, there are dynamics to unpack between the Global North, who is viewed as the influencer of norms such as the GCR, and the Global South, where most of the world's refugees live and where faith actors are ubiquitous. It is plausible that what we see in the implementation of the GCR is illustrative of the dynamics surrounding changing flows of power in the localization of international norms for refugee protection.
For now, we know that the GCR names faith actors as relevant and that this has arguably globalized their role as actors in international refugee governance. While we have evidence of their historic relevance in refugee response, we still know little about their relevance and power position in the implementation of the GCR and the localization or local adaptation of the GCR principles.
Acharya, A., 'How Ideas Spread: Whose Norms Matter? Norm Localization and Institutional Change in Asian Regionalism', International Organization, Vol. 58, No. 2, 2004, pp. 239–275.
Adamson, F. B., and G. Tsourapas (2020). The Migration State in the Global South: Nationalizing, developmental, and neoliberal models of migration management. International Migration Review, 54(3), 853-882.
Appleby, J.K., 'Implementation of the Global Compact on Safe, Orderly, and Regular Migration: A Whole-of-Society Approach', Journal on Migration and Human Security, Vol. 8, No. 2, June 1, 2020, pp. 214–229.
Aslıhan Tezel Mccarthy, 'Non-State Actors and Education as a Humanitarian Response: Role of Faith-Based Organizations in Education for Syrian Refugees in Turkey', Journal of International Humanitarian Action, Vol. 2, No. 1, November 1, 2017, pp. 1–9.
Barbour, B., L. Fan, and C. Lewa, 'A Whole-of-Society Approach to the Rohingya Refugee Crisis: Strengthening Local Protection Capacity in South and South-East Asia', Asia-Pacific Journal on Human Rights and the Law, Vol. 22, No. 1, June 1, 2021, pp. 28–48.
Barnett, M., and J. Stein, 'Faith in the Machine? : Humanitarianism in an Age of Bureaucratization', Sacred Aid : Faith and Humanitarianism, Oxford University Press, New York, 2012.
Boesenecker, A.P., and L. Vinjamuri, 'Lost in Translation? Civil Society, Faith-Based Organizations and the Negotiation of International Norms', International Journal of Transitional Justice, Vol. 5, No. 3, November 1, 2011, pp. 345–365.
Bompani, B., 'Local Religious Organisations Performing Development: Refugees in the Central Methodist Mission in Johannesburg', Journal of International Development, Vol. 27, No. 2, S.1, February 2, 2015, p. 197.
Brumat, L., A. Geddes, and A. Pettrachin, 'Making Sense of the Global: A Systematic Review of Globalizing and Localizing Dynamics in Refugee Governance', Journal of Refugee Studies, Vol. 00, No. 0, April 2021.
Carbonnier, G., 'Religion and Development: Reconsidering Secularism as the Norm', International Development Policy | Revue Internationale de Politique de Développement, No. 4, March 1, 2013, pp. 1–5.
Clarke, G., 'Faith Matters: Faith-Based Organisations, Civil Society and International Development', Journal of International Development, Vol. 18, No. 6, 2006, pp. 835–848.
Ferris, E., 'Faith and Humanitarianism: It's Complicated', Journal of Refugee Studies, Vol. 24, No. 3, September 1, 2011, pp. 606–625.
Ferris, E.,, 'Faith-Based and Secular Humanitarian Organizations', International Review of the Red Cross, Vol. 87, No. 858, June 2005, pp. 311–325.
Fiddan-Qasmiyeh, E., 'Religion and Social Justice for Refugees: Insights from Cameroon, Greece, Jordan, Lebanon, Malaysia and Mexico', JLI, 2020. https://jliflc.com/resources/religion-and-social-justice-for-refugees-insights-from-cameroon-greece-jordan-lebanon-malaysia-and-mexico/.
Finnemore, M., and K. Sikkink, 'TAKING STOCK: The Constructivist Research Program in International Relations and Comparative Politics', Annual Review of Political Science, Vol. 4, No. 1, June 2001, pp. 391–416.
Haynes, J., Faith-Based Organisations at the United Nations, Working Paper, EUI RSCAS RELIGIOWEST, 2013.
Hellmüller, S., 'Meaning‐Making in Peace‐Making: The Inclusion Norm at the Interplay between the United Nations and Civil Society in the Syrian Peace Process', Swiss Political Science Review, Vol. 26, No. 4, December 2020, pp. 384–405.
Hönke, J., and M.-M. Müller, 'Brokerage, Intermediation, Translation', in A. Draude, T.A. Börzel, and T. Risse (eds.), The Oxford Handbook of Governance and Limited Statehood, Oxford University Press, Oxford, 2018, pp. 333–352.
Joint Learning Initiative on Faith and Communities, 'Policy Brief: Faith Actors and the Implementation of The Global Compact on Refugees', JLI, 2018. https://jliflc.com/resources/policy-brief-faith-actors-and-the-implementation-of-the-global-compact-on-refugees/.
Jubilut, L.L., and M. de O.S.S. Apolinàrio, 'Refugee Status Determination in Brazil: A Tripartite Enterprise | Refuge: Canada's Journal on Refugees', Refuge: Canada's Journal on Refugees, Vol. 25, No. 2, 2008, pp. 29–40.
Mencütek, Z.Ş., 'Faith-Based Actors in Şanlıurfa, Turkey: Reducing Tensions Between Host Populations and Syrian Refugee Communities', Civil Society Knowledge Centre, Lebanon Support, June 15, 2020.
Milner, J., and A. Klassen, 'Civil Society and the Politics of the Global Refugee Regime', Vol. Paper No. 15, Local Engagement Refugee Research Network, September 2021, p. 44.
Mulholland, M.-L., 'Welcoming the Stranger in Alberta: Newcomers, Secularism and Religiously Affiliated Settlement Agencies', Canadian Ethnic Studies, Vol. 49, No. 1, January 1, 2017, p. 19.
Sulewski, D., 'Religious Actors and the Global Compact on Refugees: Charting a Way Forward', UNHCR, 2020.
Thomson, J., 'Local Faith Actors and Protection in Complex and Insecure Environments', Forced Migration Review, No. 48, November 1, 2014, pp. 5–6.
Turk, V., 'Religions for Peace World Assembly Affirmation of Welcome Special Session', , Vienna Hilton Hotel, November 21, 2013.
UNHCR, Multi-Religious Council of Leaders, 2020.
UNHCR, 'Partnership Note: On Faith-Based Organizations, Local Faith Communities and Faith Leaders', 2014.
UNHCR, The Impact of Government-Sponsored Refugee Resettlement: A Meta Study of Findings from Six Countries, UNHCR Resettlement and Complementary Pathways Service (RCPS), December 2020.
Wilkinson, O.J., '"It's Being, Not Doing": Hospitality and Hostility between Local Faith Actors and International Humanitarian Organizations in Refugee Response', Migration and Society, Vol. 1, No. 1, December 1, 2018, pp. 111–126.
Wilkinson, O., E. Tomalin, K. Logo, A. Wani Laki, and F. De Wolf, Bridge Builders: Strengthening the Role of Local Faith Actors in Humanitarian Response in South Sudan, Islamic Relief, Joint Learning Initiative on Faith and Local Communities, RedR UK, Tearfund, Tearfund Belgium, University of Leeds, 2020.
Wilkinson, O., S. Trotta, A. FitzGibbon, G. Diop, and M. Casagrande, Guide to Action on Mobilizing Faith Communities to Welcome Migrants & Refugees, Religions for Peace, New York, NY, 2019.
Wurtz, H., and O. Wilkinson, 'Local Faith Actors and the Global Compact on Refugees', Migration and Society, Vol. 3, No. 1, June 1, 2020, pp. 145–161.

redpajama_set_name: RedPajamaCommonCrawl


text:
Trefoil.tv | 電視頻道 | 孟加拉國 | NTV
孟加拉國 - 當地電視
ATN Bangla is a Bengali language digital cable television channel. The channel transmits from its studio in Dhaka, Bangladesh, and is also transmitted throughout South Asia, the Middle-East, Europe, and North America. The channel offers a wide variety of programming that includes news, movies, dramas and talk shows NTV is a Bengali language satellite television channel based in Bangladesh. It started operation in 2003. It is one of the most popular Bengali TV channels in the country. In the anniversary of the channel, the founder expressed interest in creating NTV2 to satisfy the watchers further. The channel broadcasts coverage of news, soap operas, educational, religious and politics related programs.
地址: BSEC Building (6th Floor) 102, Kazi Nazrul Islam Avenue Karwan Bazar Dhaka – 1215, Bangladesh
電話: +88 02 9143381 upto 5
NTV {Ball}/5 based on {num_rat} Votes
Canal TRO
Televisión Regional del Oriente Es un canal regional de...
ATM TV
斯洛文尼亚 - 當地電視
Program lokalne televizije Kranjska Gora....
Miracle Channel TV
泰國 - 一般
สถานีที่รวบรวมเรื่องราว มหัศจรรย์ เร้นลับ เหลือเชื่อ...
Nata nel 1985 CANALE10 ha contribuito in modo determinante alla...
亞美尼亞 - 一般
ARTN, established in 1985 has earned a well-deserved popularity...


Get safe, instant infrared heat for the outdoors when you use the Mr. Heater SRC15T SunRite outdoor tank top propane heater. It's great for camping, hiking, fishing, sporting events, construction sites and more!
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The HTC U12 Plus was released back in May, it was made available by Amazon a couple of days ago, and now JerryRigEverything released the HTC U12 Plus durability test. As per usual, the durability test video got released via YouTube, and it has a duration of about six minutes. The HTC U12 Plus comes with a see-through back, and it's made out of metal and glass, in case you've been wondering. The HTC U11 did not do all that well in JerryRigEverything's durability test last year, as the phone shattered during the bend test, let's see if the same applies to the HTC U12 Plus, or did HTC learn its lesson.
The HTC U12 Plus uses a Gorilla Glass 5 protection on the front, and the display got scratched at a usual level, with a level 6 pick, while deeper scratches were visible with a level seven pick. The phone's front-facing cameras are covered with that very same Gorilla Glass 5 protection, while some cloth is applied on top of an earpiece, and it's rather easy to remove the cloth from there, which is not the case with most modern smartphones. Rear-facing cameras are protected with Gorilla Glass 5 as well, same goes with a rear-facing fingerprint scanner it seems, or at least some sort of glass. The sides of the phone are made out of metal, and as most of you know, the HTC U12 Plus does not come with regular physical keys, it has button on the sides, but those are pressure-sensitive buttons (they can't be clicked), and they can be removed with a razor blade rather easily it seems, which is kind of strange.
Once those capacitive keys get removed, they don't work any longer. The SIM card slot is also made out of metal, while the phone uses a Super LCD display which lasted for about 10 seconds under the lighter flame before pixels died, but they recovered soon after. The phone did not shatter after Jerry applied pressure on the back and on the front, but it did flex quite a bit, and the back side could be removed afterwards, which brings the phone's IP rating into question if the phone flexed strongly enough.


text:
Richard Wadholm
Asimov's Science Fiction Magazine, April 2002
Feb 14, 2010 Mark WatsonComment on Asimov's Science Fiction Magazine, April 2002
Richard Wadholm. At the Money. I was looking forward to this hugely. A 'companion piece'
Reviews Silverberg Haber Year's Best
Science Fiction The Best of 2001, edited by Robert Silverberg and Karen Haber. ibooks, 2002
Feb 25, 2004 Mark WatsonComment on Science Fiction The Best of 2001, edited by Robert Silverberg and Karen Haber. ibooks, 2002
Stories by : Dan Simmons, Gregory Benford, Ian Watson, James Patrick Kelly, Jim Grimsley, Michael Blumlein, Michael Swanwick, Nancy Kress, Richard Wadholm, Robin Wayne Bailey, Stephen Baxter.
Year's Best Science Fiction, 20th Annual Collection. Gardner Dozois. St. Martins Griffin, 2003
Feb 25, 2004 Mark WatsonComment on Year's Best Science Fiction, 20th Annual Collection. Gardner Dozois. St. Martins Griffin, 2003
Stories by : Alastair Reynolds, Alex Irvine, Bruce Sterling, Charles Coleman Finlay, Charles Stross, Chris Beckett, Eleanor Arnason, Geoff Ryman, Greg Egan, Gregory Benford, Ian McDonald, Ian R. Macleod, James Van Pelt, John Kessel, John Meaney, Kage Baker, Maureen F. McHugh, Michael Swanwick, Molly Gloss, Nancy Kress, Paul McAuley, Richard Wadholm, Robert Reed, Steven Popkes, Walter Jon Williams


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Why So Many Subs? Investigating the WCPSS Teacher Shortage
Lucas Moore and Lorelei Zagacki
Up to 3 classes are sometimes held in the Media Center under the supervision of one substitute (Ellie Hamashima)
As of February 4th, 2022, there are a total of 119 job openings in Wake County high schools. Driven by teachers retiring, leaving the profession, transferring to other schools, and entering the private sector, this is an unprecedented statistic that frequently leaves many classes with substitute teachers.
This has had a profound impact on students such as sophomore Izzy Fron. Fron had a teacher leave midway through the year, and she believes that the classroom environment has suffered because of this upheaval. Izzy states, "when there is an active teacher, students can learn more and complete their work, but without one, there is slacking off on busy work." This situation has been seen in classrooms across the school, resulting in students such as Izzy feeling like their learning experience has been affected in a negative way.
These effects extend beyond the classes directly experiencing teacher turnover; they impact the entire Green Hope community. One such example is Green Hope Teacher of the Year Ms. Caroline Moakley, who described her experience this year as "spinning 100 plates all at once."
It does feel quite a bit like spinning 100 plates all at once."
— Ms. Caroline Moakley
With average class sizes hovering in the high 30s, creating lesson plans and grading work for around 100 students takes hours upon hours of time. To further exacerbate the issue, when there aren't enough substitutes in the building teachers must cover classes during their planning periods. Moakley discussed the importance of having that planning period, saying, "We try to avoid having situations where teachers have to use their planning periods to cover classes because then that teacher is not able to plan and grade, and that just snowballs the effect of having large classes and not being able to catch up on your work."
Moakley said that the increased workload this year has impacted the feedback she is able to give to her students, resulting in less time for specific commentary and advice.
Students from multiple classes work in the Media Center, supervised by Mr. Manuel Jurado. (Ellie Hamashima)
In order to preserve teacher's planning periods, several classes end up in the Media Center every period under the supervision of school substitute Mr. Manuel Jurado. "With 3 classes, it can be a little overwhelming," Jurado said. He expressed his gratitude for the Media Center Specialists, Ms. Emily Yates and Ms. Jennifer Dry, who help him manage sometimes close to 100 students in a single period.
But luckily, the situation may be improving soon. Green Hope has had 16 positions open up midway through the 2021-22 school year, ranging from teachers to counselors to administrators. More staff have been hired mid-year than in the entire summer. And to further complicate the situation, the school only had between the start of December and final exams week in early January to fill those positions. One of the key figures in this hiring process is principal Dr. Camille Hedrick, whose focus this year is building a strong, supportive school community.
The most valuable resource on your campus is your people."
— Dr. Camille Hedrick, Principal
"The most valuable resource on your campus is your people," Hedrick said. She repeatedly praised her department chairs, teachers, and support staff for their hard work during this difficult time. Hedrick and her department chairs spent winter break interviewing and giving school tours to prospective faculty.
"We had a lot of people to bring in…and we had to do it in such a way that they are set up for success. And that, in a positive way, takes a toll on the other staff," she said.
In the end, Green Hope successfully filled all 16 open positions with people who are, in Hedrick's eyes, "home run hitters." She stressed the importance of building a supportive, welcoming community, saying that good teachers "only work where they are welcome and they feel effective and they can do their job well," and that, "if they don't feel good, they'll go work somewhere else." But, if they're set up for success and given the resources they need, Hedrick believes they'll stay.
Every student deserves a good teacher"
The number of position openings in Wake County schools is still quite high, most individual high schools have more than ten, and some more than 20. At the time of writing, Green Hope only lists six job openings, which speaks to the amazing community that Hedrick attributes to teachers, staff, students, and their families.
Hedrick summed up her approach to building Green Hope's staff by saying, "it matters to me that we have good teachers and that we have good staff members." The teacher turnover present this year has certainly been difficult for students, teachers, and administrators, but the influx of new faces into the building will, Hedrick hopes, mitigate these issues and influence the Green Hope community for the better.
Lucas Moore, Editor-in-Chief
Lucas is Editor-in-Chief at The GH Falcon, and a senior at Green Hope. This is his third year on the staff of The Falcon, and his main responsibilities include building this website, editing articles,...
Lorelei Zagacki, Student Life Editor
Lorelei Zagacki is a proud senior who's excited to film more podcasts and graduate this year!
Hailing from North Carolina, Lorelei loves herself a good southern meal of chicken and waffles. If you were...
Ellie Hamashima, Staff Writer / Social Media Editor
Ellie Hamashima is a fun, charismatic senior and the Social Media Manager of the Falcon. She is the youngest of two siblings and enjoys making new friends, which is something she is excited to do next...
All The Green Hope Falcon Picks Reader Picks Sort: Newest


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On Oct. 26, artists and musicians will pack the Isle of Hope Marina and Paxton Park for the Isle of Hope Art and Music Festival.
What started as a small event in Ruth Wright's front yard to showcase members of the Isle of Hope Artisans' League quickly turned into a bustling event.
"We have one of the most beautiful places on Isle of Hope to live in, and we would like to celebrate that ... by having a fun day that is enriching for the mind, body and soul through art and music, but the bottom line is about just having a great time with old and new friends for the day," said event organizer Brigitte Szychowski-VanBaelen.
This year, more than 60 Savannah-based artists will present their photographs, paintings and original jewelry, alongside musical acts Velvet Caravan, Lauren Lapointe and The Train Wrecks, just to name a few.
A little something extra for the kids has been added to the 2013 festival at Paxton Park, where a Kids' Zone will include a chance to create projects from Savannah's Clay Spot and Scribble Art Studio. Wormsloe Historic Site will also host period-style games at the marina.
And best of all, aside from refreshments and art purchases, the festival is free.
"We like to introduce something new every year, and this year we focused on kids and family," said Szychowski-VanBaelen. "The support of our community has been overwhelming, which is noticeable through sponsorships, both monetarily and in kind, and it is what is making this event happen every year."
What: Isle of Hope Art and Music Festival
When: 10 a.m. to 10 p.m. Oct. 26
Where: Art show from 10 a.m. to 5 p.m. on the Marina Pavilion, Bluff Drive and Paxton Park; music fest from 1-10 p.m. in marina parking lot; free kids activities from 11 a.m. to 3 p.m. in Paxton Park and 10 a.m. to 5 p.m. at the marina.
Info: www.facebook.com/IsleOfHopeArtMusicFest


text:
from django.core.management.base import AppCommand

class Command(AppCommand):
    help = "Prints the CREATE INDEX SQL statements for the given model module name(s)."

    output_transaction = True

    def handle_app(self, app, **options):
        from django.core.management.sql import sql_indexes
        return u'\n'.join(sql_indexes(app, self.style)).encode('utf-8')

redpajama_set_name: RedPajamaGithub