Tag: agriculture

Area with high N2O emission has a relatively lower oxygen concentration due to the expansion of nutrients runoff from land. To diminish the negative environmental impacts, fertigation treatment could reduce the amount of nitrogen and nutrients input to the soil, prevent over fertilization, and excess nutrient runoff to the river. Forward osmosis has many advantages regard saving physical footprints. High waste water recovery rate, minimized resupply, and low energy cost can facilitate the sustainability of forward osmosis. However, forward osmosis has a lower membrane fouling propensity compared to other pressure-driven membrane processes. Forward osmosis is usually applied as pretreatment of reverse osmosis, the total energy consumption of a combination of FO and RO is lower than reverse osmosis alone. Moreover, osmotic backwashing can be compelling to restrict the membrane while reducing energy consumption at the same time. In the situation when Nanofiltration served as post-treatment combined with fertilizer draw forward osmosis can backwash the excess fertilizer replenishment and turn it into concentrated fertilizer draw solutions. The energy consumption of FDFO brackish water recovery using cellulose triacetate is affected by draw solution concentration , flow rates ,fodder systems for cattle and membrane selection. Membrane orientation and the flow rates have a minor effect on specific energy consumption compared to draw solution concentration. A diluted fertilizer draw solution can boost the system’s performance while a higher draw solution concentration can lower the specific energy consumption.

Moreover, a lower flow rate with a higher draw solution concentration can diminish the energy consumption of fertilizer draw forward osmosis to the lowest. This additional process would increase the energy consumption of the system. However, nanofiltration is necessary for desalination and direct fertigation treatment.The energy consumption of the nanofiltration process is determined by the environmental impacts, such as recovery rate, membrane lifetime, and membrane cleaning. Forward osmosis technology performs a 40-50% reduction in specific energy consumption compared to other alternatives. As a result, FO technology has the potential for wide adoption in drinking water treatment. Another area of application of FO usage is seawater desalination/brine removal, direct fertigation, wastewater reclamation, and wastewater minimization. Without the draw solution recovery step, forward osmosis could be applied as osmotic concentration. For example,fertilizer-draw forward osmosis is widely accepted for the freshwater supply and direct fertigation. However, in terms of the evaporative desalination process, it is more practical to treat the water with a lower total dissolved solid /salinity. Forward osmosis technology can be combined with other treatment methods such as reverse osmosis, nanofiltration, or ultrafiltration for different water treatment purposes. To be more specific, forward osmosis can be an alternative pre-treatment in conventional filtration/separation system ; an alternative process to conventional membrane treatment system ; a post-treatment process to recycle the volume of excess waste . The standalone forward osmosis process usually combines with additional post-treatment to meet the water quality standards for different purposes.

Forward osmosis has been researched in the past. In this review, we focused on fertilizer drawn forward osmosis, which can not only remove brine but also reduce multiple nutrient inputs such as nitrogen, phosphorous, potassium, and so on. Since a proper draw solution can reduce the concentration polarization, the draw solution selection becomes vital for both FO and FDFO processes. Moreover, different fertilizer draws solutions have various influences on energy consumption. The nutrient concentrations of treated water are controllable using the fertilizer-drawn forward osmosis treatment method. The composition of nutrients can be adjusted in the draw solution to produce water with different ratios of nutrients, which makes fertilizer draw forward osmosis a nearly perfect treatment method for direct fertigation. For the purpose of reducing N2O emissions, the removal rate of nitrogen in fertigation water is required to be improved using fertilizer drawn forward osmosis and nanofiltration. When nanofiltration is applied as post-treatment with fertilizer drawn forward osmosis, the nitrogen removal rate can reach up to 82.69% while using SOA as the draw solution. This number shows that treatment of fertigation can reach a higher standard of water quality attenuating nitrogen concentrations. As a result, lower nitrogen input in fertigation can significantly decrease the nitrous oxide emission from the soil for sustainable agricultural use. Forward osmosis can be also combined with other treatment methods to resolve the freshwater shortage problem. Despite the traditional seawater desalination treatment incorporating forward osmosis and reverse osmosis, the hybrid process of reverse osmosis and fertilizer drawn forward osmosis can remove the brine from water and lower the final nutrient concentration with a higher recovery rate. Lastly, the value of water flux, recirculation rate, draw solution concentration, membrane lifetime, and membrane cleaning can all be adjusted to minimize energy consumption as much as possible. In conclusion, FO and FDFO technologies are both environmentally friendly and economically for desalination and fertigation.

Evapotranspiration estimation is important for precision agriculture, especially precision water management. Mapping the ET temporally and spatially can identify variations in the field, which is useful for evaluating soil moisture and assessing crop water status. ET estimation can also benefit water resource management and weather forecast. ET is a combination of two separate processes, evaporation and transpiration . Evaporation is the process whereby liquid water is converted to water vapor through latent heat exchange. Transpiration is the process of the vaporization of liquid water contained in plant tissues,fodder sprouting system and the vapor removal to the atmosphere. The current theory for transpiration is constituted by the following three steps. First, the conversion of liquid-phase water to vapor water causes canopy cooling from latent heat exchange. Thus, canopy temperature can be used as an indicator of ET. Second, diffusion of water vapor from inside plant stomata on the leaves to the surrounding atmosphere. Third, atmospheric air mixing by convection or diffusion transports vapor near the plant surfaces to the upper atmosphere or off-site away from the plant canopy. Usually, evaporation and transpiration occur simultaneously.These direct ET methods, however, are usually point-specific or area-weighted measurements and cannot be extended to a large scale because of the heterogeneity of the land surface. The experimental equipment is also costly and requires substantial expense and effort, such as lysimeters, which are only available for a small group of researchers. For indirect methods, there are energy balance methods and remote sensing methods. For energy balance methods, Bowen ratio and eddy covariance have been widely used in ET estimation. However, they are also area-weighted measurements. Remote sensing techniques can detect variations in vegetation and soil conditions over space and time. Thus, they have been considered as some of the most powerful methods for mapping and estimating spatial ET over the past decades. Remote sensing models have been useful in accounting for the spatial variability of ET at regional scales when using satellite platforms such as Landsat and ASTER. Since the satellite started being applied, several remote sensing models have been developed to estimate ET, such as surface energy balance algorithm for land, mapping evapotranspiration with internalized calibration, the dual temperature difference, and the Priestley–Taylor TSEB. Remote sensing techniques can provide information such as normalized difference vegetation index , leaf area index , surface temperature, and surface albedo. Related research on these parameters has been discussed by different researchers. As a new remote sensing platform, researchers are very interested in the potential of small UAVs for precision agriculture, especially on heterogenous crops, such as vineyard and orchards.

UAVs overcome some of the remote sensing limitations faced by satellite. For example, satellite remote sensing is prone to cloud cover; UAVs are below the clouds. Unlike satellites, UAVs can be operated at any time if the weather is within operating limitations. The satellite has a fixed flight path; UAVs are more mobile and adaptive for site selection. Mounted on the UAVs, lightweight sensors, such as RGB cameras, multispectral cameras, and thermal infrared cameras, can be used to collect high-resolution images. The higher temporal and spatial resolution images, relatively low operational costs, and the nearly real-time image acquisition, make the UAVs an ideal platform for mapping and monitoring ET. Many researchers have already used UAVs for ET estimation, as shown in Table 1. For example, in Ortega-Farías et al. implemented a remote sensing energy balance algorithm for estimating energy components in an olive orchard, such as incoming solar radiation, sensible heat flux, soil heat flux, and latent heat flux. Optical sensors were mounted on a UAV to provide high spatial resolution images. By using the UAV platform, experiment results show that the RSEB algorithm can estimate latent heat flux and sensible heat flux with errors of 7% and 5%, respectively. It demonstrated that UAV could be used as an excellent platform to evaluate the spatial variability of ET in the olive orchard.There are two objectives for this paper. First, to examine current applications of UAVs for ET estimation. Second, to explore the current uses and limitations of UAVs, such as UAVs’ technical and regulatory restrictions, camera calibrations, and data processing issues. There are many other ET estimation methods, such as surface energy balance index, crop water stress index , simplified surface energy balance index, and surface energy balance system, which have not been applied with UAVs. Therefore, they are out of the scope of this article. This study is not intended to provide an exhaustive review of all direct or indirect methods that have been developed for ET estimation. The rest of the paper is organized as follows: Section 2 introduces different UAV types being used for ET estimation. Several commonly used lightweight sensors are also compared in Section 2. The ET estimation methods being used with UAV platforms, as shown in Table 1, are discussed. In Section 3, different results of ET estimation methods and models are compared and discussed. Challenges and opportunities, such as thermal camera calibration, UAV path planning, and image processing, are discussed in Section 4. Lastly, the authors share views regarding ET estimation with UAVs in future research and draw conclusive remarks. Many kinds of UAVs are used for different research purposes, including ET estimation. Some popular UAV platforms are shown in Figure 1. Typically, there are two types of UAV platforms, fixed-wings and multirotors. Fixed-wings can usually fly longer with a larger payload. They can usually fly for about 2 h, which is suitable for a large field. Multirotors can fly about 30 min, which is suitable for short flight missions. Both of them have been used in agricultural research, such as, which promises great potential in ET estimation.Mounted on UAVs, many sensors can be used for collecting UAV imagery, such as multispectral and thermal images, for ET estimation. For example, the Survey 3 camera has four bands, blue, green, red, and near-infrared , with a spectral resolution of 4608 × 3456 pixels, and a spatial resolution of 1.01 cm/pixel. The Survey 3 camera has a fast interval timer, 2 s for JPG mode, and 3 s for RAW + JPG mode. Faster interval timer would benefit the overlap design for UAV flight missions, such as reducing the flight time, and enabling higher overlapping. Another multi-spectral camera being commonly used is the Rededge M. The Rededge M has five bands, which are blue, green, red, near-infrared, and red edge. It has a spectral resolution of 1280 × 960 pixel, with a 46◦ field of view. With a Downwelling Light Sensor , which is a 5-band light sensor that connects to the camera, the Rededge M can measure the ambient light during a flight mission for each of the five bands. Then, it can record the light information in the metadata of the images captured by the camera. After the camera calibration, the information detected by the DLS can be used to correct lighting changes during a flight, such as changes in cloud cover during a UAV flight. The thermal camera ICI 9640 P has been used for collecting thermal images as reported in. The thermal camera has a resolution of 640 × 480 pixels. The spectral band is from 7 to 14 µm. The dimensions of the thermal camera are 34 × 30 × 34 mm. The accuracy is designed to be ±2 ◦C. A Raspberry Pi Model B computer can be used to trigger the thermal camera during flight missions. The SWIR 640 P-Series , which is a shortwave infrared camera, can also be used for ET estimation. The spectral band is from 0.9 µm to 1.7 µm. The accuracy for the SWIR camera is ±1 ◦C. It has a resolution of 640 × 512 pixels.

Typically, they allow for endogenous structural adjustments in land use, management, commodity production, and consumption in response to exogenous scenario drivers . However, with several components of productivity parameters endogenously determined, it can be difficult to isolate the potential role of livestock efficiency changes due to technological breakthroughs or policy incentives. For example, as production decreases due to decreasing demand, so could productivity. In this case, a design feature can be a design faw for sensitivity analysis and policy assessment focused on individual key system parameters, even if model results can be further decomposed to disentangle endogenous and exogenous productivity contributions . Accounting-based land sector models, such as the FABLE Calculator, which we also employ in this current study, can offer similarly detailed sector representation, without the governing market mechanisms, thus allowing fully tunable parameters for exploring policy impacts . This feature facilitates quantifying uncertainty and bounding estimates through sensitivity analyses. The FABLE Calculator is a sophisticated land use accounting model that can capture several of the key determinants of agricultural land use change and GHG emissions without the complexity of an optimization based economic model. Its high degree of transparency and accessibility also make it an appealing tool to facilitate stakeholder engagement.This paper explores the impacts of healthier diets and increased crop yields on U.S. GHG emissions and land use,dutch buckets as well as how these impacts vary across assumptions of future livestock productivity and ruminant density in the U.S. We employ two complementary land use modeling approaches.

The first is the FABLE Calculator , a land use and GHG accounting model based on biophysical characteristics of the agricultural and land use sectors with high agricultural commodity representation. The second is a spatially-explicit partial equilibrium optimization model for global land use systems . The combination of these modeling approaches allows us to provide both detailed representation of agricultural commodities with high flexibility in scenario design and a dynamic representation of land use in response to known economic forces , qualities that are difficult to achieve in a single model. Both modeling frameworks allow us to project to 2050 U.S. national scale agricultural production, diets, land-use, and carbon emissions and sequestration under varying policy and productivity assumptions. Our work makes several advances to sustainability research. First, using agricultural and forestry models that capture market and intersectoral dynamics, this is the first non-LCA study to examine the sustainability of a healthier average U.S. diet . Second, using two complementary modeling approaches, this is the first study to explore the GHG and land use effects of the interaction of healthy diets and agricultural productivity. Specifically, we examined key assumptions about diet, livestock productivity, ruminant density, and crop productivity. Two of the key production parameters we consider—livestock productivity and stocking density—are affected by a transition to healthier diets but have not been extensively discussed in the agricultural economic modeling literature. Third, we isolate the effects of healthier diets in the U.S. alone, in the rest of the world, and globally, which is especially important given the comparative advantage of U.S. agriculture in global trade.To model multiple policy assumptions across dimensions of food and land use and have full flexibility in terms of parameter assumptions and choice of underlying data sets, we customized a land use accounting model built in Excel, the FABLE Calculator , for the U.S. Below we describe the design of the Calculator, but for more details we direct the reader to the complete model documentation .

The FABLE Calculator represents 76 crop and livestock products using data from the FAOSTAT database. The model first specifies demand for these commodities under selected scenarios , the Calculator computes agricultural production and other metrics, land use change, food consumption, trade, GHG emissions, water use, and land for biodiversity. The key advantages of the Calculator include its speed, the number and diversity of scenario design elements , simplicity, and its transparency. However, unlike economic models using optimization techniques, the Calculator does not consider commodity prices in generating the results, does not have any spatial representation, and does not represent different production practices. The following assumptions can be adjusted in the Calculator to create scenarios: GDP, population, diet composition, population activity level, food waste, imports, exports, livestock productivity, crop productivity, agricultural land expansion or contraction, reforestation, climate impacts on crop production, protected areas, post-harvest losses, bio-fuels. Scenario assumptions in the Calculator rely on “shifters” or time-step-specific relative changes that are applied to an initial historic value using a user-specified implementation rate. The Calculator performs a model run through a sequence of steps or calculations, as follows: calculate human demand for each commodity; calculate livestock production; calculate crop production; calculate pasture and cropland requirements; compare the land use requirements with the available land accounting for restrictions imposed and reforestation targets; calculate the amount of feasible pasture and cropland; and calculate the feasible crop and livestock production; calculate feasible human demand; calculate indicators . See Figure S1 in the Supplementary Materials for a diagram of these steps. Using U.S. national data sources, we modified or replaced the US FABLE Calculator’s default data inputs and growth assumptions based on Food and Agriculture Organization data.

Specifically, we used crop and livestock productivity assumptions from the U.S. Department of Agriculture , grazing/stock intensity using literature from U.S. studies, miscanthus and switch grass bio-energy feed stock productivity assumptions from the Billion Ton study , updated beef and other commodity exports using USDA data, and created a “Healthy Style Diet for Americans” diet using the 2015–2020 USDA Dietary Guidelines for Americans . See SM Table S6 for all other US Calculator data and assumptions. We used these U.S.-specific data updates to construct U.S. diet, yield, and livestock scenarios and sensitivities . See for a full description of the other assumptions and data sources used in the default version of the FABLE Calculator.As a complement to the FABLE Calculator’s exogenously determined trade flows, we used GLOBIOM [a widely used and well-documented global spatially explicit partial equilibrium model of the forestry and agricultural sectors. Documentation can be found at the GLOBIOM github development site to capture the dynamics of endogenously determined international trade. Unlike the FABLE Calculator, GLOBIOM is a spatial equilibrium economic optimization model based on calibrated demand and supply curves as typically employed in economic models. GLOBIOM represents 37 economic production regions, with regional consumers optimizing consumption based on relative output prices, income, and preferences. The model maximizes the sum of consumer and producer surplus by solving for market equilibrium and using the spatial equilibrium modeling approach described in McCarl and Spreen and Takayama and Judge . Product-specific demand curves and growth rates over time allow for selective analysis of preference or dietary change through augmenting demand shift parameters over time to reflect differences in relative demand for specific commodities . Production possibilities in GLOBIOM apply spatially explicit information aggregated to Simulation Units, which are aggregates of 5 pixels of the same altitude, slope, and soil class, within the same 30 arcmin pixel, and within the same country. Land use, production and prices are calibrated to FAOSTAT from the 2000 historic period. Production systems parameters and emissions coefficients for specific crop and livestock technologies are based on detailed biophysical process models,grow bucket including EPIC for crops and RUMINANT for livestock . Livestock and crop productivity changes are reflected by both endogenous and exogenous components. For crop production, GLOBIOM yields can be shifted exogenously to reflect technological or environmental change assumptions and their associated impact on yields. Exogenous yield changes are accompanied by changes in input use intensity and costs .A similar approach has been applied in other U.S.-centric land sector models, including the intertemporal approach outlined in Wade et al. . Furthermore, reflecting potential yield growth with input intensification per unit area is consistent with observed intensification of some inputs in the U.S. agricultural system. This includes nitrogen fertilizer intensity , which grew approximately 0.4% per year from 1988 to 2018 .

Higher prices can induce production system intensification or crop mix shifts across regions to exploit regional comparative advantages. GLOBIOM accounts for several different crop management techniques, including subsistence-level , low input, high input, and high input irrigated systems. The model simulates spatiotemporal allocation of production patterns and bilateral trade fows for key agriculture and forest commodities. Regional trade patterns can shift depending on changes in market or policy factors that Baker et al. and Janssens et al. explore in greater detail in addition to providing a more comprehensive documentation of the GLOBIOM approach to international trade dynamics, including cost structures and drivers of trade expansion or contraction, or establishing new bilateral trade flows. This approach allows for flexibility in trade adjustments at both the intensive and extensive margins given a policy or productivity change in a given region. GLOBIOM has been applied extensively to a wide range of relevant topics, including climate impacts assessment , mitigation policy analysis , diet transitions , and sustainable development goals . We designed new U.S. and rest-of-the world diet and yield scenarios , and ran all scenarios at medium resolution for the U.S. and coarse resolution for ROW. We chose Shared Socioeconomic Pathway 2 macroeconomic and population growth assumptions for all parameters across all scenarios when not specified or overridden by scenario assumptions .We aligned multiple assumptions in the FABLE Calculator with GLOBIOM inputs and/or outputs to isolate the impacts of specific parameter changes in livestock productivity and ruminant density. Specifically, we used the same set of U.S. healthy diet shifters in both models, but aligned the US FABLE Calculator’s crop yields and trade assumptions with GLOBIOM outputs to isolate the effects of increasing the ruminant livestock productivity growth rate and reducing the ruminant grazing density using the Calculator . While we developed high and baseline crop yield inputs for GLOBIOM, actual yields are reported because of the endogenous nature of yields in GLOBIOM. This two model approach allows us to explore the impact of exogenous changes to the livestock sector that cannot be fully exogenous in GLOBIOM. Subsequent methods sections describe each of these scenarios and sensitivity inputs in greater detail.We constructed a “Healthy U.S. diet” using the “Healthy U.S.-style Eating Pattern” from the USDA and US Department of Health and Human Services’ 2015–2020 Dietary Guidelines for Americans . We use a 2600 kcal average diet. This is a reduction of about 300 kcal from the current average U.S. diet given that the current diet is well over the Minimum Dietary Energy Recommendations of 2075 kcal, computed as a weighted average of energy requirement per sex, age, and activity level and the population projections by sex and age class following the FAO methodology . The DGA recommends quantities of aggregate and specific food groups in units of ounces and cup-equivalents on a daily or weekly basis. We chose representative foods in each grouping to convert volume or mass recommendations into kcal/day equivalents and assigned groupings and foods to their closest equivalent US Calculator product grouping . For DGA food groups that consist of more than one US Calculator product group, e.g., “Meats, poultry, eggs”, we used the proportion of each product group in the baseline American diet expressed in kcal/day and applied it to the aggregated kcal from the DGA to get the recommended DGA kcal for each product group . We made one manual modification to this process by increasing the DGA recommendation for beef from a calculated value of 36 kcal/day to 50 kcal/day, since trends in the last decade have shown per capita beef consumption exceeding that of pork . This process led to a total daily intake of 2576 kcal for the healthy U.S. diet . The Baseline, average U.S. diet is modeled in the US FABLE Calculator using FAO reported values on livestock and crop production by commodity in weight for use as food in the U.S., applying the share of each commodity that is wasted, then allocating weight of each commodity to specific food product groups , converting weight to kcal, and finally dividing by the total population and days in a year to get per capita kcal/day. See the Calculator for more details and commodity specific assumptions . This healthy U.S. diet expressed in kcal was used directly in the Calculator as a basis for human consumption demand calculations for specific crop and livestock commodities.

Previous studies have shown that SL promotes photomorphogenesis by increasing HY5 level . However, the molecular links from SL signaling to HY5 regulation have remained unclear. Our results show that BZS1 mediates SL regulation of HY5 level and photomorphogenesis. Similar to hy5-215, BZS1-SRDX seedlings are partially insensitive to GR24 treatment under light , which indicates that BZS1 plays a positive role in SL regulation of seedling morphogenesis. Actually, BZS1 is the only member in the subfamily IV of B-box protein family that is regulated by SL , suggesting that BZS1 plays a unique role in SL regulation of photomorphogenesis. As BZS1 increases HY5 level, SL activation of BZS1 expression would contribute, together with inactivation of COP1 , to the SL-induced HY5 accumulation. On the other hand, the BZS1-SRDX plants showed normal branching phenotypes , which suggests that BZS1 is only involved in SL regulation of HY5 activity and seedling photomorphogenesis but not shoot branching. Our finding of BZS1 function in SL response further supports a key role for BZS1 in integration of light, BR and SL signals to control seedling photomorphogenesis . To generate 15N-labeled seeds, Arabidopsis plants were grown hydroponically in diluted Hoagland solution containing 10 mM K15NO3 . One eighth diluted Hoagland medium was used at seedling stage and 1/4 Hoagland medium was used when plant started to bolt. After the siliques were fully developed, 1/8 Hoagland medium was used till seeds were fully mature. For SILIA-IP-MS assay,strawberry gutter system the 14N- or 15N-labeled seeds were grown on Hoagland medium containing 10 mM K14NO3 or K15NO3, respectively, for 5 days under constant white light.

The seedlings were harvested and ground to fine powder in liquid nitrogen. Five grams each of 14N-labeled BZS1-YFP or YFP and 15N-labeled wild-type tissue power were mixed and total proteins were extracted using extraction buffer . After removing the cell debris by centrifugation, 20 μL GFP-Trap®_MA Beads were added to the supernatant and then incubated in the cold room for 2 h with constant rotating. The beads were washed three times with IP wash buffer . The proteins were eluted twice using 50 μL 2 × SDS sample loading buffer by incubating at 95°C for 10 min. The isotope labels were switched in repeat experiments. The eluted proteins were separated by NuPAGE® Novex 4–12% Bis-Tris Gel . After Colloidal Blue staining , the gel was cut into five fractions for trypsin digestion. In-gel digestion procedure was performed according to Tang et al. . Extracted peptides were analyzed by liquid chromatographytandem mass spectrometry . The LC separation was performed using an Eksigent 425 NanoLC system on a C18 trap column and a C18 analytical column . Solvent A was 0.1% formic acid in water, and solvent B was 0.1% formic acid in acetonitrile. The flow rate was 300 nL/min. The MS/MS analysis was conducted with a Thermo Scientific Q Exactive mass spectrometer in positive ion mode and data dependent acquisition mode to automatically switch between MS and MS/MS acquisition. The identification and quantification were done by pFind and pQuant softwares in an open search mode. The parameters of software were set as follows: parent mass tolerance, 15 ppm; fragment mass tolerance, 0.6 Da. The FDR of the pFind analysis was 1% for peptides. Arabidopsis TAIR10 database was used for data search. Three-day-old Arabidopsis seedlings expressing BZS1-YFP or YFP alone were grown under constant light and used for BZS1-COP1 co-immunoprecipitation assay. For the BZS1, HY5 and STH2 co-immunoprecipitation assay, about one-month-old healthy Nicotiana benthamiana leaves were infiltrated with Agrobacterium tumefaciens GV3101 harboring corresponding plasmids.

The plants were then grown under constant light for 48 h and infiltrated leaves were collected. Total proteins from 0.3 g tissue powder were extracted with 0.6 mL extraction buffer . The lysate was pre-cleared by centrifugation twice at 20,000 g for 10 min at 4°C, and then diluted with equal volume of extraction buffer without Triton X-100. Twenty microliter of Pierce Protein A Magnetic Beads coupled with 10 μg anti-GFP polyclonal antibody were added to each protein extract and incubated at 4°C for 1 h with rotation. The beads were then collected by DynaMag™-2 Magnet and washed three times with wash buffer . The bonded proteins were eluted with 50 μL 2 × SDS loading buffer by incubating at 95°C for 10 min. For western blot analysis, proteins were separated by SDS-PAGE electrophoresis and transferred onto a nitrocellulose membrane by semi-dry transfer cell . The membrane was blocked with 5% none-fat milk followed by primary and secondary antibodies. Chemiluminescence signal was detected using SuperSignal™ West Dura Extended Duration Substrate and FluorChem™ Q System . Monoclonal GFP antibody was purchased from Clontech, USA. Myc antibody and ubiquitin antibody were from Cell Signaling Technology, USA.HY5 and COP1 antibodies were from Dr. Hongquan Yang’s lab. Secondary antibodies goat anti-mouse-HRP or goat anti-rabbitHRP were from Bio-Rad Laboratories. Arundo donax is a tall grass that is native from the lower Himalayas and invaded the Mediterranean region, prior to its introduction in the America’s . It is suspected to first have been introduced to the United States in the 1700’s, and in the Los Angeles area in the 1820’s by Spanish settlers . Its primary use was for erosion control in drainage canals.

A number of other uses for Arundo have been identified. It is the source of reeds for single reed wind instruments such as clarinet and the saxophone . In Europe and Morocco Arundo is used for waste water treatment , such as nutrient and heavy metal removal, and water volume evapotranspiration. The high rate of evapotranspiration by stands of this species, used as a benefit in these countries, is one of the characteristics that is detrimental in the California ecosystems invaded by Arundo. By the 1990’s Arundo has infested tens of thousands of acres in California riparian ecosystems, and these populations affect the functioning of these systems in different ways. It increases the fire hazard in the dry season . The regular fires promoted by the dense Arundo vegetation, are changing the nature of the ecosystem from a flood-defined to a fire-defined system . During floods, Arundo plant material can accumulate in large debris dams against flood control structures and bridges, and interfere with flood water control management , and bridges across Southern California rivers. It can grow up to 8-9 m tall, and its large leaf surface area can cause the evapotranspiration of up to 3 x the amount of water that would be lost from the water table by the native, riparian vegetation . Displacement of the native vegetation results in habitat loss for desired bird species, such as the federally endangered Least Bell’s Vireo and the threatened Willow Flycatcher . Due to the problems listed above, removal of Arundo from California ecosystems has been one of the priorities of a variety of organizations and agencies involved in the management of the state’s natural resources, such as the California Department of Fish & Game, a number of resource conservation districts. In the practice of Arundo control,grow strawberry in containers both mechanical and chemical methods of Arundo control are applied, sometimes in combination , the choice of their use depending on timing, terrain, vegetation, and funding. The risks, costs, and effects of the different control methods were listed in the most recent Arundo and saltcedar workshop by . The timing of the eradication effort can be affected by a number of factors other than the biology of the target species, such as limitations due to bird nesting season, and funding availability. Ideally, the timing of any eradication effort, chemical or mechanical should be determined by the ecophysiology of the target species, in this case Arundo donax, rather than the calendar year. For chemical eradication, this has been recognized for a while, as stated by Nelroy Jackson of Monsanto, at the first Arundo workshop: “Timing of application for optimal control is important. Best results from foliar applications of Rodeo© or Roundup© are obtained when the herbicides are applied in late summer to early fall, when the rate of downward translocation of glyphosate would be greatest.” A similar statement has not yet been made for the timing of mechanical eradication methods, nor had the effect of timing on the effectiveness of mechanical eradication been identified. Mechanical eradication of Arundo can be attempted in many different manners. The most frequently used method is the cutting of the above ground material, the plant’s tall stems. Another method of mechanical eradication is digging out the underground biomass, the rhizomes. The cutting of stems can occur before and after herbicide applications.

The large amount of standing above ground biomass, up to 45 kg/m2 impedes the removal of the cut material, because the costs will be too high. The costs associated with the removal of the large biomass of the stems, has led to the use of “chippers” that will cut the stems into pieces of approximately 5 – 10 cm in situ. After these efforts, the chipped fragments are left in place. A small fraction of the fragments left behind after chipping will contain a meristem. The stem pieces of these fragments may have been left intact, or split lengthwise. In the second case the node at which the meristem at located will have been split as well. On many pieces with a meristem, the meristem itself may still be intact. These stem fragments might sprout and regenerate into new Arundo plants . If stems are not cut into small pieces, or removed after cutting, the tall, cut stems can be washed into the watershed during a flood event. This material can accumulate behind bridges and water control structures with possible consequences as described in the introduction. Meristems on the stems can also sprout, and lead to the establishment of new stands of Arundo at the eradication project site, or down river . A. donax stands have a high stem density. The outer stalks of dense stands will start to lean to the outside because the leaves produced during the growing season push the stems in the stand apart. After the initial leaning due to crowding, gravity will pull the tall outside stems almost horizontal . Throughout this report these outside hanging stems will be referred to as “hanging stems”. The horizontal orientation causes hormonal asymmetry in these stems. The main hormones involved are IAA , GA and ethylene . The unusual IAA and GA distributions cause the side shoots developing on these hanging stems, to grow vertically. IAA also plays an important role in plant root development , and may therefore have a stimulative effect on root emergence from the adventious shoot meristem on fragments that originated from hanging stems, that would be absent in stem fragments from upright stems. In a preliminary experiment comparing root emergence between stem fragments from hanging and upright stems, 38% of the hanging stemstem fragments developed roots, while none of the upright stem-stem fragments showed root emergence . These results indicated the need for further study into the possibility that new A. donax plants can regenerate from the stem fragments with shoot meristems that might be dispersed during mechanical Arundo removal efforts. In order to apply herbicides at that time that the rate of downward translocation of photosynthates and herbicide would be greatest, this time period has to be established. Carbohydrate distribution and translocation within indeterminate plants, such as Arundo, results from the balance between the supply of carbon compounds to and the nitrogen concentration in the different plant tissues. Carbon and nitrogen are the most important elements in plant tissues. Due to different diffusion rates of NO3 – and NH4 + in soil water versus that of CO2 in air, and differences in plant N and C uptake rates, plant growth will earlier become nitrogen limited than carbon limited. During plant development tissue nitrogen concentrations are diluted by plant growth , which is mainly based on the addition of carbohydrates to the tissues. When plant growth becomes nitrogen limited, the tissue will maintain the minimum nitrogen content needed for the nucleic acids and proteins that maintain metabolic function. At this low tissue nitrogen content, there is not enough nitrogen in an individual cell to provide the nucleic acids and proteins to support the metabolism of two cells, therefore the cells cannot divide. This means that the tissue cannot grow anymore , until it receives a new supply of nitrogen.

The results suggest that SA responses in tomato play a less important role in defense against Phytophthora capsici than to Pst. The impact of SA and plant activators on ABA accumulation was measured in tomato roots and shoots.However, ABA accumulation in non-stressed TDL and BTH treatments trended higher than those observed in salt-stressed plants that did not receive a plant activator treatment . Protection by TDL against Pst is likely the result of a triggered SAR response and not the result of an antagonistic effect on ABA levels. The efficacy of plant activators depends on the specific diseases targeted and the environmental context, which may present additional stressors to confound defense network signaling in the plant. A challenge for successful deployment of plant activators in the field is to manage the allocation, ecological and fitness costs that are associated with induced defenses . These costs can be manifested by reduced growth and reproduction, vulnerability to other forms of attack, and potential interference with beneficial associations . It would seem that the severity of these costs is conditioned in part by the milieu of abiotic stressors operative at any given time. Reactive oxygen species contribute to the initiation of SAR , are induced by SA and BTH , and are essential co-substrates for induced defense responses such as lignin synthesis . ROS also are important in modulating abiotic stress networks, for example in ABA signaling and response . The potential compounding effect of ROS generated from multiple stressors presents a dilemma in that the plant must reconcile these to adapt or else suffer the negative consequences of oxidative damage for failure to do so . Paradoxically, SA and BTH also are reported to protect plants against paraquat toxicity, blueberry grow pot which involves ROS generation for its herbicidal action . How plants balance ROS’s signaling roles and destructive effects within multiple stress contexts is unresolved and a critically important area of plant biology with relevance for optimizing induced resistance strategies in crop protection .

Although our experiments were conducted under highly controlled conditions, the results with TDL are encouraging and show that chemically induced resistance to bacterial speck disease occurs in both salt-stressed and non-stressed plants and in plants severely compromised in SA accumulation. Future research with plant activators should consider their use within different abiotic stress contexts to fully assess outcomes in disease and pest protection.These syntenies of wheat and rye chromosomes permit the formation of compensating translocations of wheat and rye chromosomes. A compensating translocation is genetically equivalent to either of the two parental chromosomes; that is, it carries all relevant genes, but not necessarily in the same order. On the other hand, homoeology between wheat group 1S and rye 1S arms permitted induction of homoeologous genetic recombination, thus the development of recombinants of much smaller segments of rye 1RS to wheat than the entire arm. Many of the present wheat cultivars developed by breeding for disease resistance carry a spontaneous centric rye-wheat translocation 1RS.1BL that has been very popular in wheat breeding programs . This translocation contains a short arm of rye chromosome 1, and the long arm of wheat chromosome 1BL . It must have occurred by misdivision of centromeres of the two group 1 chromosomes, and fusion of released arms and first appeared in two cultivars from the former Soviet Union, Aurora and Kavkaz. Rye chromosome arm 1RS in the translocation contains genes for resistance to insect pest and fungal disease but as it spread throughout wheat breeding programs it became apparent that the translocation was also responsible for a yield boost in the absence of pests and disease . Besides the presence of genes for resistance and yield advantage on 1RS, there is a disadvantage of 1RS in wheat due to the presence of the rye seed storage protein secalin, controlled by the Sec-1 locus on 1RS, and the absence of the wheat loci, Gli-B1 and Glu-B3, on the 1RS arm. Lukaszewski modified the 1RS.1BL translocation by removing the Sec-1 locus and adding Gli-B1 and Glu-B3 on the 1RS arm. Lukaszewski developed a set of wheat−rye translocations, derived from ‘Kavkaz’ winter wheat that added 1RS to wheat arms 1AL, 1BL, and 1DL in spring bread wheat ‘Pavon 76’, a high yielding spring wheat from CIMMYT.

Studies showed that the chromosomal position of 1RS in the wheat genome affected agronomic performance as well as bread-making quality . Using the 1RS translocation, Lukaszewski developed a total of 183 wheatrye short arm recombinant lines for group 1 chromosomes in a near-isogenic background of cv. Pavon 76 bread wheat. Out of 183 recombinant chromosomes, 110 were from 1RS- 1BS combinations, 26 from 1RS-1AS and 47 from1RS-1DS combinations. Mago et al. used some of these lines to link molecular markers with rust resistance genes on 1RS. These recombinant brea kpoint populations provide a powerful platform to locate region specific genes. Wheat roots have two main classes, seminal roots and nodal roots . Seminal roots originate from the scutellar and epiblast nodes of the germinating embryonic hypocotyls, and nodal roots, emerge from the coleoptiler nodes at the base of the apical culm . The subsequent tillers produce their own nodal roots, two to four per node and thus contribute towards correlation of root and shoot development . The seminal roots constitute from 1-14% of the entire root system and the nodal roots constitute the rest . Genetic variation for root characteristics was reported in wheat and other crop species . Genetic variability for seedling root number was studied among different Triticum species at diploid, tetraploid, and hexaploid level and it was found to be positively correlated with seed weight . In a hydroponic culture study in winter wheat, Mian et al. found significant genotypic differences in root and shoot fresh weights, number of roots longer than 40 cm, longest root length and total root length. Wheat genotypes with larger root systems in hydroponic culture were higher yielding in field conditions than those with smaller root systems . Also, wheat yield stability across variable moisture regimes was associated with greater root biomass production under drought stress . Studies in other cereal crops associated quantitative trait loci for root traits with the QTL for grain yield under field conditions. Champoux et al. provided the first report of specific chromosomal regions in any cereal likely to contain genes affecting root morphology. They reported that QTL associated with root traits such as root thickness, root dry weight per tiller, root dry weight per tiller below 30 cm,hydroponic bucket and root to shoot ratio shared common chromosomal regions with putative QTL associated with field drought avoidance/tolerance in rice. Price and Tomos also mapped QTL for root growth using a different population than that used by Champoux et al. in rice.

In a field study of maize recombinant lines, QTL for root architecture and above ground biomass production shared the same location . Tuberosa et al. reported the overlap of QTL for root characteristics in maize grown in hydroponic culture with QTL for grain yield in the field under well-watered and droughted regimes occurred in 8 different regions. They observed that QTL for weight of nodal and seminal roots were most frequently and consistently overlapped with QTL for grain yield in drought and well watered field conditions. Also, at four QTL regions, increase in weight of the nodal and seminal roots was positively associated with grain yield under both irrigation regimes in the field. There are a few reports on QTL studies for root traits in durum wheat but none has been reported in bread wheat. Kubo et al. studied root penetration ability in durum wheat. They used discs of paraffin and Vaseline mixtures as substitute for compact soil. Later, a QTL analysis was done for the number of roots penetrating the poly vinyl disc, total number of seminal and crown roots, root penetration index and root dry weight . The QTL for number of roots penetrating the poly vinyl disc and root penetration index was located on chromosome 6A and a QTL for root dry weight was located on 1B. Wang et al. demonstrated significant positive heterosis for root traits among wheat F1 hybrids. They showed that 27% of the genes were differentially expressed between hybrids and their parents. They suggested the possible role of differential gene expression in root heterosis of wheat, and possible other cereal crops. In a recent molecular study of heterosis, Yao et al. speculated that up-regulation of TaARF, an open reading frame encoding a putative wheat ARF protein, might contribute to heterosis observed in wheat root and leaf growth. Rye, wheat and barley develop 4-6 seminal roots which show a high degree of vascular segmentation . Feldman traced files of metaxylem to their levels of origin in maize root apex and showed their differentiation behind the root apex in three-dimensional model. In drier environments, Richards and Passioura demonstrated that genotypes, when selected for narrow root xylem vessels as against unselected controls, yielded up to 3%-11% more than the unselected controls depending upon their genetic background. This yield increase in the selections with narrow root vessel was correlated with a significantly higher harvest index, also higher biomass at maturity and kernel number. Huang et al. indicated the decrease in diameter of metaxylem vessel and stele with increase in temperature which resulted in decreased axial water flow in wheat roots. The decrease in axial water flow is very critical in conserving water during vegetative growth and making it available during reproductive phase of the plant. In a recent study on root anatomy, QTL for metaxylem were identified on the distal end of the long arm of chromosome 10 of rice . In another comparative study of rye DNA sequences with rice genome, the distal end of the long arm of chromosome 10 of rice showed synteny to the 1RS chromosome arm . The 1RS.1BL chromosome is now being used in many wheat breeding programs. Rye has the most highly developed root system among the temperate cereals and it is more tolerant to abiotic stresses such as drought, heat, and cold than bread wheat .

Introgression of rye chromatin into wheat may enlarge the wheat root system. Manske and Vlek reported thinner roots and higher relative root density for 1RS.1BL translocations compared with their non-translocated bread wheat checks in an acid soil, but not under better soil conditions. Repeated studies with the 1RS translocation lines of Pavon 76 have demonstrated a consistent and reproducible association between root biomass and the presence and position, of the rye 1RS arm . The increased grain yield of 1RS translocations under field conditions observed and reported earlier may be due to the consistent tendency of 1RS to produce more root biomass and also to the higher transpiration rate measured .Those authors have shown a significant increase of root biomass in wheat lines with 1RS translocations, and a positive correlation between root biomass and grain yield. All translocations of 1RS: with 1A, 1B, and 1D chromosomes have shown increased root biomass and branching as compared to Pavon 76 and there was differential expression for root biomass among these translocation lines with ranking 1RS.1AL > 1RS.1DL > 1RS.1BL > Pavon 76. In Colorado, the 1RS.1AL translocation with 1RS from Amigo showed 23% yield increase under field conditions over its winter wheat check, Karl 92 . Many present day bread wheat cultivars carry a centric rye-wheat translocation 1RS.1BL in place of chromosome 1B . Originally the translocation was thought to have been fixed because the 1RS arm of rye carries genes for resistance to various leaf and stem fungal diseases and insects . However, the translocation increased grain yield even in the absence of pathogens . It has been shown recently that this yield increase may be a direct consequence of a substantially increased root biomass . Studies by Ehdaie et al. 2003 showed a significant increase of root biomass in wheat lines with 1RS translocations and a positive correlation between root biomass and grain yield. In sand cultures, all three 1RS translocations on 1AL, 1BL, and 1DL in ‘Pavon 76’ genetic background showed clear position effects with more root biomass and root branching over Pavon 76 .

A previous study about the response of different Andean and Mesoamerican common-bean cultivars to AlT showed that Andean genotypes are more tolerant to this abiotic stress, as compared to Mesoamerican genotypes . Our phylogenetic analysis revealed that all the Andean genotypes present a deleted version of the MIR1511 that would result in the absence of functional mature miR1511 . Previous work from our group showed that common-bean miR1511 expression responds to AlT stress . Here we analyzed the regulation of miR1511 and ALS3, as well as the early effects of AlT in roots of common-bean plants from the Mesoamerican BAT93 genotype vs. Andean G19833 genotype, with a deleted MIR1511 . Common-bean plantlets from BAT93 and G19833 genotypes were grown in hydroponic conditions either in control or AlT treatments, for up to 48 hrs. First, we performed the expression analysis of miR1511 and ALS3 target gene, using qRT-PCR . In AlT-stressed BAT93 plants, the transcript accumulation level of mature miR1511 gradually decreased, reaching more than half at 24 hours post-treatment , while at 48 hpt it returned to values close to those of time 0 . As expected, G19833 plants did not express mature miR1511 .The ALS3 transcript accumulation was significantly higher in G19833 roots, which lack miR1511, compared to BAT93 roots . At 6 hpt, ALS3 expression in G19833 roots almost doubled and remained unchanged up to 48 hpt, when transcript accumulation in BAT93 and G1988 roots reached similar levels . To further study the role of miR1511/ALS3 in the physiological reaction of common-bean plants to high Al levels, nft hydroponic system we aimed to over express the miR1511 precursor in transgenic roots.

As long as stable transformation of Phaseolus vulgaris plants is, to date, nearly impossible, we chose to use BAT93 and G19833 composite plants -with untransformed aerial organs and transgenic roots . As long as common bean is recalcitrant to stable transformation, this method is an alternative to demonstrate miRNA functionality . The miR1511-overexpressing composite plants as well as control plants, transformed with empty vector , were grown in AlT and control treatments. The expression level of miR1511 and ALS3 were determined by qRT-PCR in roots from composite plants harvested at 48 hpt . A two-fold accumulation of miR1511 transcript was observed in BAT93 OE1511 roots from plants grown in either treatment, compared to EV . In G19833 EV roots, the absence of miR1511 was confirmed, however a significant accumulation of miR1511 mature transcript was observed in OE1511 roots, albeit at lower levels than the level from BAT93 OEmiR1511 roots . In control treatment, both genotypes showed lower expression level of ALS3 in OEmiR1511 vs. EV roots. In addition, increased ALS3 transcript levels were observed in AlT stressed roots from both genotypes, as compared to control treatment . The primary and earliest symptoms of plants subjected to AlT stress is an inhibition of lateral root formation and root growth due to the alteration of root cell expansion and elongation, inhibiting cell division . On this basis, we analyzed the root architecture phenotype of BAT93 and G19833 OEmiR1511 and EV plants, grown under AlT or control treatments for 48 h . The growth rate of root length, width and area as well as the number of lateral roots, was calculated from the difference of each value at 48 hpt vs. time 0. The BAT93 EV plants under AlT showed decreased rates of each root parameter , thus indicating the drastic effect of high Al on root development. In contrast, G19833 EV plants showed higher tolerance to AlT evidenced by similar rate of the root length, area, width and lateral root number in stress vs control treatments .

These results are in agreement with those previously reported indicating a higher tolerance to AlT of Andean common-bean genotypes compared to Mesoamerican genotypes . Surprisingly, in G19833 plants genetically engineered for the expression of mature miR1511, the effect of root phenotype was evident. The rate of root length, area, width and lateral root number of G19833 OEmiR1511 AlT-stressed plants significantly decreased ascompared to EV plants, showing reduced levels similar to those from BAT93 stressed plants . In A. thaliana, primary root growth inhibition under phosphate limitation or AlT is mediated by ALS3 and LPR1, a ferroxidase . LPR1 acts downstream of ALS3 and its expression is epistatic to ALS3 expression . To determine if LPR1 could be involved in the different response to AlT of BAT93 vs. G19833 plants, we measured the accumulation of LPR1 transcripts in similar AlT conditions as those from Figure 4. The transcript level of LPR1 gene decreased in AlT treatment. In AlT BAT93 roots, the transcript level of LPR1 gradually decreased reaching half of the initial expression at 48 hpt. In AlT G19833 roots, the LPR1 expression was significantly lower compared to BAT93 roots from 6 hpt to 24 hpt . At 48 hpt, LPR1 transcript reached similar levels in roots from both genotypes . The LPR1 expression pattern was opposite to the ALS3 expression profile in AlT-stressed roots , indicating an epistatic relation between these two genes and the possible participation of LPR1 together with ALS3 in the control of common-bean root growth under AlT. In order to determine if miR1511 indirectly controls LPR1 expression via the regulation of ALS3 transcript, we evaluated the LPR1 transcripts accumulation in transgenic roots from OEmiR1511 and EV composite plants, growing in Alt vs control conditions. In both BAT93 and G19833 roots, a significant increase of LPR1 transcript accumulation was observed in OEmiR1511 roots from plants grown in either treatment, compared to EV roots . In AlT treatment, roots from both genotypes showed significant lower LPR1 transcript level compared to roots from control condition.

Again, LPR1 expression pattern was the opposite compared to that of ALS3 in the same transgenic root samples , thus indicating the probable epistatic relationship between these two genes and the indirect regulation of miR1511 on LPR1 expression. In plants, microRNA genes have a higher birth and death rates than protein-coding genes . For various authors, the miRNAs’ evolution rate generates a reservoir of adaptability for gene regulation . Due to this high evolutionary turnover rate, new miRNA families and members emerge, while others lose their regulatory role and disappear from genomes of phenotypically close species or genotypes. In soybean, MIR1511 is subjected to this mechanism. Htwe et al.,reported two altered versions of MIR1511 alleles in some annual wild soybean genotypes,hydroponic nft system whereas no deletion was found in G. max and perennial wild soybean MIR1511. Here, we report a similar phenomenon for P. vulgaris MIR1511 genotypic variations. Only part of the MW1 subgroup of P. vulgaris Mesoamerican genotypes and all the Andean genotypes analyzed displayed a 58 bp-deletion in the miR1511 precursor gene compared to the corresponding sequence of P. dumosus, P. coccineus, the PhI gene pool and the rest of P. vulgaris Mesoamerican genotypes . As MIR1511 is present in non-legume species, the most parsimonious hypothesis to explain the evolution process associated with this event is to consider a deletion of part of miR1511 precursor sequence. In contrast to soybean, where probably two deletion events were required for the generation of two alternative MIR1511 alleles, our results suggest a single deletion event in the common ancestor of a part of MW1 Mesoamerican subgroup and the Andean genotypes for the generation of a different allele of miR1511 precursor gene. This single MIR1511 deletion event hypothesis supports the Mesoamerican model proposed by Ariani and colleagues where the Mesoamerican gene pool is the ancestral population from which the other gene pools have derived. The fact that the PhI gene pool contains an untruncated version, as do the other closely-related Phaseolus species included in this analysis, further confirms the sister-species status of the PhI gene pool, now known as P. debouckii . P. debouckii also contains ancestral, i.e., non-derived, sequences for phaseolin seed protein and chloroplast DNA . Based on the MIR1511 phylogenetic history presented here , we propose an addendum to this model where AW gene pool genotypes derived from one, or more, member of the MW1 Mesoamerican subgroup. A clear distinct geographical distribution pattern was observed among the P. vulgaris genotypes featuring the MIR1511 deletion and the ones with an unaltered allele . MIR1511 deletion occurred in genotypes originating from the northern and southern extreme limits of the common-bean distribution in Latin American area. Such distribution pattern correlates with the annual precipitation pattern reported for the American continent , indicating that genotypes with MIR1511 deletion originated from areas with significantly less precipitation as compared to areas where genotypes with unaltered MIR1511 originated . Drought makes soil not suitable for agriculture; it tends to increase soil concentration of different compounds that would result in plant toxicity, including aluminum toxicity, which is an important plant growth-limiting factor . The harsh soil conditions of areas where P. vulgaris genotypes lacking of MIR1511 originated probably forced these common-bean populations to adapt and favored selection of genotypes with higher AlT tolerance. In this work, we showed the experimental validation of a target gene for P. vulgaris miR1511. We validated the miR1511-induce cleavage of ALS3 transcript, an ABC transporter participating in Al detoxification in plants . However, additional action of miR1511 by translation repression of ALS3 cannot be excluded. Other proposed target genes for P. vulgaris miR1511 are not related to plants AlT response and show high binding-site penalty score, thus improbable to be considered as functional in the AlT response. Here we provided evidence of the role of the miR1511/ALS3 node in the common-bean response to AlT .

We interpret that the MIR1511 deletion resulting in lack of mature miR1511 allowed common-bean adaptation to high Al in the soils by eliminating the negative regulation of ALS3 transcript and the accumulation of LPR1, in the first 48 hpt, thus increasing its tolerance to AlT and favoring plant growth. Interestingly, similar characteristics hold for the soybean MIR1511-deletion case where the origin of soybean genotypes featuring a MIR1511-altered allele is geographically correlated with areas susceptible to high Al concentration in soil due to presence of drought in these regions .High aluminum levels in soil mainly affect plant roots; aluminum can be allocated to different subcellular structures thus altering the growth of the principal root and the number of lateral roots . In this sense, it has been observed that AlT-stressed plants favor the transport of chelated Al to vacuoles and from roots, through the vasculature, to aerial tissues that are less sensitive to Al accumulation . In Arabidopsis and other plants, ALS1 and ALS3, from the ATP-binding cassette transporter family, are involved in Al detoxification and enhance tolerance to AlT . ALS3 is located in the tonoplast, the plasma membrane of root cortex epidermal cells, and in phloem cells throughout the plant . It has been shown that Arabidopsis als3 mutants are more sensitive to AlT exhibiting extreme root growth inhibition, compared to wild type plants . Recent studies on the role of Arabidopsis ALS3 in root growth inhibition revealed its regulation via the inhibition of the STOP1-ALMT1 and LPR1 pathways, which indirectly control ROS accumulation in roots via the modulation of Fe accumulation . Furthermore, Arabidopsis ALS3 expression is induced by excess Al , a phenomenon we observed in common-bean plants as well . Common-bean ALS3 expression doubled after 6 hours under AlT in roots from G19833 plants, while in stressed roots from BAT93 plants a similar level was reached only after 48 h of treatment . The opposite expression profile was found for the ALS3-epistatic gene LPR1, in the same samples . Our data on the different ALS3 and LPR1 expression level from both genotypes indicate that the absence of the negative regulator miR1511 in G19833 plants allows a faster response to AlT. Although the level of mature miR1511 decreased in BAT93 roots up to 24 h of after exposure to high Al, this level seems sufficient to induce degradation of ALS3 transcript, which showed reduced levels compared to G19833 roots, and an increase of LPR1 expression . Our analysis of root architecture in common-bean plants showed that G19833 Andean genotype plants are more tolerant to AlT as compared to Mesoamerican BAT93 plants . These data agree with those reported by Blair et al. .