Dynamics of micro and macronutrients in a hydroponic nutrient film technique system under lettuce cultivation.

While hydroponics is considered an efficient vegetable production system, there is a compelling need to investigate the efficiency of the current generic nutrient dosing recommendation primarily based on electrical conductivity (EC) measurements. Such information is critical to fine-tune and optimize the current hydroponic management practices for improved nutrient uptake efficiency. This study investigated the dynamics of some micro and macronutrients (N, P, Ca, Mg, K, Fe, and Mn) in a recirculating nutrient film technique (NFT) hydroponic system under lettuce cultivation. The research was conducted in an indoor controlled environment growth chamber with lettuce grown in different EC levels (1.2 and 1.6 dS m-1). Each treatment had four hydroponic cultivation units, each one with 24 plants. Nutrient solution and tissue samples were collected two to three times per week. Nutrient dynamics, including nutrient uptake efficiencies and environmental losses, were calculated using a mass balance approach. The effects of EC level on fresh and dry lettuce biomass and nutrient uptake were insignificant. Observed variations in nutrient solution composition during lettuce cultivation included the almost complete removal of ammonia nitrogen, nitrate decreases towards the end of the experiment, consistent increases in aqueous Ca concentration, and corresponding decreases in K and Mn. Average N losses ranged between 27 and 40 %, presumably through denitrification, while 10-14 % of N was assimilated into the plant biomass. The remaining N in the recirculating nutrient solution was estimated to be between 50 and 59 %. The average P loss was 11-35 %, likely due to precipitation, while 52-77 % remained in the nutrient solution. Nutrient uptake efficiencies averaged 19-31 % K, 12-21 % P, 9-16 % Mn, 4-6 % Ca, 3-4 % Mg, and 2-4 % Fe. These results suggest that elevated nutrient concentrations in recirculating nutrient solutions led to losses and underutilization. Findings from this study provide a comprehensive dataset critical to improving hydroponic nutrient management beyond N and P. Hydroponic nutrient management should target providing essential nutrients needed by plants at the correct proportions considering the plant growth stage.

Seawater flooding of calcareous soils: Implications for trace and alkaline metals mobility.

Developing management strategies to safeguard public health and environmental sustainability requires a comprehensive understanding of the solubility and mobility of trace and alkaline metals in the event of seawater flooding. This study investigated the effects of seawater flooding, along the duration of flooding, on the release of trace and alkaline metals (Mn, Fe, Cu, Zn, Ca, K, and Mg) in two calcareous soils (Krome and Biscayne) located in southern Florida. Seawater flooding experiments involved two soil types and four flooding durations (1, 7, 14, and 28 days) replicated three times. Freshwater flooding experiments were also conducted for comparison. After each flooding experiment, soil samples were collected at three depths (15, 30, and 45 cm), and analyzed for selected elements. Comparative analysis revealed significant releases of Mn, Fe, and Zn in both soils flooded by seawater compared to freshwater. In most cases, significant increments were evident as early as 1-day exposure to seawater flooding, which further increased with flooding duration. However, the impacts of seawater flooding had notable differences between the two soils. Seawater flooding in Krome soil for 28 days, resulted in higher Mn, Fe, and Zn contents by 58, 340, and 510% compared with freshwater flooding, while corresponding increases in Biscayne soil were 3.3, 130, and 180%, respectively. Comparable marginal increases in Cu content were observed for both soils. Similarly, seawater flooding increased K, Mg, and Na contents from single-day flooding. The interplay between soil type, column depth, flooding duration, and their interactions proved influential factors in determining Mn, Fe, Cu, and Zn releases, with peak levels typically observed on the 28th day of flooding and at bottom depths. Overall, these findings highlight the release of these elements, raising concerns about potential plant toxicity and groundwater or surface water contamination due to leaching and runoff.

Integrating machine learning and empirical evapotranspiration modeling with DSSAT: Implications for agricultural water management.

The availability of accurate reference evapotranspiration (ETo) data is crucial for developing decision support systems for optimal water resource management. This study aimed to evaluate the accuracy of three empirical models (Hargreaves-Samani (HS), Priestly-Taylor (PT), and Turc (TU)) and three machine learning models (Multiple linear regression (LR), Random Forest (RF), and Artificial Neural Network (NN)) in estimating daily ETo compared to the Penman-Monteith FAO-56 (PM) model. Long-term data from 42 weather stations in Florida were used. Moreover, the effect of ETo model selection on sweet corn irrigation water use was investigated by integrating simulated ETo data from empirical and ML models using the Decision Support System for Agrotechnology Transfer (DSSAT) model at two locations (Citra and Homestead) in Florida. Furthermore, a linear bias correction calibration technique was employed to improve the performance of empirical models. Results were consistent in that the NN and RF models outperformed the empirical models. The empirical models tended to underestimate and overestimate small and high daily ETo values, respectively, with the HS model exhibiting the least accuracy. However, calibrated PT and TU models performed comparably to the ML models. Results also revealed that using an inappropriate ETo model could lead to over-irrigation by up to 54 mm during a single crop season. Overall, ML models have proven reliable alternatives to the PM model, especially in regions with access to long-term data due to their site-independent performance. In areas without long-term data for ML model training and testing, calibrating empirical models is viable, but site-specific calibration is needed. It is important to highlight that distinct plant species exhibit varying transpiration characteristics and, consequently, have different water requirements. These differences play a pivotal role in shaping the overall impact of ETo models on crop water use.

Evaluating the effects of DEM and soil data resolution on streamflow and sediment yield simulations in the Upper Blue Nile basin.

While the availability of "big data" on biophysical parameters through citizen science and/or from public/private sources is expected to help in addressing data scarcity issues, there is little understanding of whether and/or how such data will improve watershed simulations. This research aimed to evaluate whether improvements in resolutions of Digital Elevation Model (DEM) and soil data will enhance streamflow and sediment yield simulations and thereby improve soil and water management decisions. The study was conducted in two different-sized watersheds (Anjeni and Gilgel Abay with ~ 1 km2 and ~ 1655 km2 area, respectively) in the Upper Blue Nile basin in Ethiopia. Effects of DEM and soil data resolutions on streamflow and sediment yield were evaluated using the Soil and Water Assessment Tool (SWAT). The results showed that the effect of DEM and soil data resolution on streamflow and sediment yield simulation was scale dependent finer resolution DEM and soil datasets improved streamflow and sediment yield simulations in the smaller Anjeni watershed, whereas DEM resolution had no effect in the bigger Gilgel Abay watershed. Small watersheds are often used to understand watershed processes, and thus the use of finer-resolution spatial data for watershed simulations could result in better results. Findings from the smaller Anjeni watershed suggested that the combined use of finer resolution DEM and soil data could potentially improve sediment yield simulations although the lack of observed sediment yield data did not allow verification of this at the larger Gilgel Abay watershed.

Soil erosion estimation and erosion risk area prioritization using GIS-based RUSLE model and identification of conservation strategies in Jejebe watershed, Southwestern Ethiopia.

Erosion of soil refers to the process of detaching and transporting topsoil from the land surface by natural forces such as water, wind, and other factors. As a result of this process, soil fertility is lost, water bodies' depth is reduced, water turbidity rises, and flood hazard problems, etc. Using a numerical model of erosion rates and erosion risks in the Jejebe watershed of the Baro Akobo basin in western Ethiopia, this study mapped erosion risks to prioritize conservation measures. In this study, the Revised Universal Soil Loss Equation (RUSLE) model was used, which was adapted to Ethiopian conditions. To estimate soil loss with RUSLE, the rainfall erosivity (R) factor was generated by interpolating rainfall data, the soil erodibility (K) factor was derived from the soil map, the topography (LS) factor was determined from the digital elevation model (DEM), cover and management (C) factor derived from the land use/cover data, and conservation practices (P) factor generated from digital elevation model (DEM) and land use/cover data were integrated with remote sensing data and the GIS 10.5 environment. The findings indicated that the watershed annual soil loss varies from nearly 0 on a gentle slope of forest lands to 265.8 t ha-1 year-1 in the very steep slope upper part of the watershed, with a mean annual soil loss of 36.2 t ha-1 year-1. The total annual soil loss in the watershed is estimated to be around 919,886.5 tons per year. To minimize the amount of soil erosion in the watershed that had been most severely affected, we identified eight conservation strategies that could be implemented. These strategies were based on the participatory watershed development (PWD) principles established by the Ethiopian government and the severity of the erosion in the watershed. The study's findings showed that a GIS-based RUSLE soil erosion assessment model can provide a realistic prediction of the amount of soil loss that will occur in the watershed. This tool can also help identify the priority areas for implementing effective erosion control measures.

Predicting runoff and sediment responses to climate-resilient land use and management scenarios.

Soil erosion is the predominant agent affecting ecosystem services in the Ethiopian highlands. However, land management interventions aimed at controlling erosion in the region are hampered, mainly by a lack of watershed-based appropriate management practices and anticipated climate changes. This study examined the effectiveness of different land use changes and management scenarios in decreasing runoff and sediment loss under current and future climates in the drought-prone humid watershed of the Ethiopian highlands. We employed a modeling approach integrating observed data at watershed and plot scales with Soil and Water Assessment Tool. In the first step, we evaluated the impact of land use changes between 2006 and 2017 on runoff and sediment loss. Then, we developed five land use and management scenarios based on watershed land capabilities and selected land management practices. Model parameters were modified based on runoff and sediment loss results obtained from experimental plots of biophysical and agronomical land management practices in the watershed. The runoff and sediment loss were simulated under current (2014-2019) and future climates (the 2050s) for each land use and management scenario. Results revealed that land use changes (mainly an increase in Acacia decurrens plantations by 206%) alone between 2006 and 2017 reduced runoff by 31% and sediment loss by 45%. Under the current climate, the five land use and management scenarios reduced runoff by 71-95% and sediment loss by 75-96% compared to the baseline scenario. Under the future climate (2050s), these scenarios decreased runoff by 48-90% and sediment loss by 54-91%. However, their effectiveness was slightly decreased (5-23%) as a result of increases in rainfall (10-46%) and mean temperature (1.7-1.9 °C) in the 2050s. The scenario of improving vegetation cover through forage production and plantations in appropriate areas plus best land management practices was the most effective and climate-resilient of the five scenarios. This study suggests that evaluating the impact of land use and management practices under future climate change shows promise for guiding effective and sustainable interventions to adapt to climate change.

Impacts of soil and water conservation measures on soil physicochemical properties in the Jibgedel Watershed, Ethiopia.

Soil erosion significantly affects agricultural production. Soil and Water Conservation (SWC) measures have been constructed to reduce soil loss. However, the impact of SWC measures on physicochemical soil properties has rarely been investigated in most parts of Ethiopia. Therefore, this study was designed to evaluate the effects of SWC measures on selected soil physicochemical properties in the Jibgedel watershed, West Gojjam zone, Ethiopia. The study also assessed the farmers' perception of the benefits and impacts of SWC measures. Composite and core soil samples were taken at a depth of 0 to 20 cm from four farmlands with SWC measures (soil bund, stone bund, and soil bund with sesbania tree) and without SWC measures in three replications. Results have shown that employing SWC measures in the farmland significantly improved most of the physicochemical properties of the soil compared to farmland without SWC measures. Bulk density from soil bund with and without sesbania trees was significantly lower than stone bund and untreated farmland. Soil organic carbon, total nitrogen, electrical conductivity, and available phosphorus from soil bund with sesbania tree were significantly higher than other treatments. The result also revealed that most farmers perceived that the implemented SWC measures improved soil fertility and crop yield. SWC measures are easier to adopt for integrated watershed management when farmers are well-versed in them.

Modeling impacts of projected land use and climate changes on the water balance in the Baro basin, Ethiopia.

In terms of land use and climate, the world is changing at an unprecedented rate and these changes have a significant influence on our water resources. This study was conducted to examine the individual and combined potential impacts of land use and climate change on the water balance of the Baro basin in Ethiopia for the baseline period (1985-2002) and near-future period (2023-2040) using the Soil and Water Assessment Tool (SWAT). The plausible land use scenarios considering current (CUR), business as usual (BAU), and further expansion of altitudinal forest and watershed management practices (CON), as well as climate change scenarios from regional climate model outputs (RCMs) under two representative concentration pathways (RCP4.5 and RCP8.5) for the 2023-2040 time frame, were used as inputs to the models. The monthly calibrated and validated SWAT model produced an acceptable result, which was then used for water balance simulations. Findings show that forest decreased from 54.5% to 48.9% and 41.2% while agricultural land increased from 21.8% to 29.7% and 39.8% under the CUR and BAU land use change scenarios, respectively. The results from the ensemble mean showed an increase in maximum and minimum temperatures and a decrease in rainfall under the RCP4.5 and RCP8.5 climate change scenarios, which in turn resulted in an increase in evapotranspiration (ET) and a decrease in water availability. Climate change outweighed the impact of land-use change, thus indicating an increase in annual ET by up to 12% and a decrease of 42% in surface runoff (SURQ) under the RCP8.5 scenario. The BAU land use scenario projection triggers a respective increase of 18% in annual SURQ and reduction of ET by 2%. However, under the CON land use scenario, SURQ decreased by 24%. The study concluded that future land use and climate change will further challenge the basin's water supply capacity to meet the increased water demand. Understanding the changes in the basin's water balance is critical for mitigation and adaptation options. As a result, this study proposes restoration efforts and climate-resilient water management strategies that can increase the resilience of the river basin.

Using liquefied biomass hydrogel to mitigate salinity in salt-affected soils.

Salinity affects over 33% of irrigated farmland globally. Developing a low-cost, safe, and effective material as a soil salinity mitigation option would be of significant importance. This study proposed to synthesize a hydrogel using liquefied biomass from sugarcane bagasse, polyvinyl alcohol, and sodium tetraborate decahydrate. The effectiveness of the produced hydrogel in mitigating soil salinity was evaluated based on an incubation experiment at two salinity levels (5 and 10 dS m-1). The experiment was conducted by mixing liquefied hydrogel with soil at four application rates (0, 1, 2, and 3% w/w) with three replications. Porewater and soil samples were tested for pH and electrical conductivity (EC). Soil samples were also analyzed for selected cations and anions. The results demonstrated that hydrogel significantly reduced porewater EC at both 5 and 10 dS m-1 salt solutions. In addition, hydrogel reduced Cl-, P, Ca2+, and Al3+ concentrations in soil samples with maximum reductions observed from 3% hydrogel treatment. However, pH of porewater showed a consistent increase with hydrogel application. The application of hydrogel also increased NH4-N at high salt level. Overall, hydrogel has shown promising results in reducing soil salinity and could potentially be used as a soil amendment for saline soils.

Characterization of residues from non-woody pulping process and its function as fertilizer.

Pulping and paper industries using non-woody feedstocks face the challenge of its notorious waste disposal problem. To resolve this problem, in this study, we evaluated a variety of properties of solid residues reclaimed from the effluents of both wheat straw ammonium sulfate and Kraft pulping processes as organic fertilizers. The results show that both residues from the ammonium sulfate (RAS) and Kraft pulping (RKP) processes possess desirable C/N ratios, appropriate nutritional compositions, and low levels of harmful heavy metals. The high solubilities (>35 g/L) of both residues allow their use for fertigation or foliar applications. The salt index (30-50) is within the range of commercial chemical fertilizers such as potassium sulfate (42.6) and magnum sulfate (44). The E3/E5 ratios of residues suggest that the residues have small molecular sizes, which are similar to fulvic acids. Overall, wheat straw pulping residues demonstrate the potential as the sustainable organic fertilizers and the beneficial soil amendments. This work has the potential to resolve the severer effluent disposal problem faced by the non-woody pulping and papermaking industries, open a door to effectively utilize residues as value-added byproducts, and lead to both environmental sustainability and economic benefits.

Polyethyleneimine-modified biochar for enhanced phosphate adsorption.

Biochar, a low-cost porous carbonaceous adsorbent, has low adsorption capacity for anion contaminants. The objective of this study was to improve biochar's ability to adsorb phosphorus (P) through polyethyleneimine (PEI) modification to form an amine-functionalized biochar. Biochars prepared by pyrolysis of bamboo biomass, before and after PEI modification, were characterized using the Fourier transformed infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscope (SEM), elemental analysis, and batch sorption experiments. The effects of pH, coexisting anions, and ionic strength on P adsorption by PEI-modified biochar were also investigated. Results indicated that PEI was successfully grafted onto biochar which resulted an increase in surface amine group and in P adsorption. The peak of P adsorption occurred at pH of three and adsorption of P was decreased with increasing of ionic strength and when coexisting ions, such as HCO3-, SO42-, NO3-, and Cl-, were coexisted. The electrostatic interaction between P and surface functional groups of PEI-modified biochar served as the primary mechanism controlling the adsorption process. These results indicate that chemically functionalized biochar with amine groups can enhance P adsorption.

Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia.

The Weather Research and Forecasting (WRF) model is one of the regional climate models for dynamically downscaling climate variables at finer spatial and temporal scales. The objective of this study was to evaluate the performance of WRF model for simulating temperature and rainfall over Lake Tana basin in Ethiopia. The WRF model was configured for six experimental setups using three land surface models (LSMs): Noah, RUC and TD; and two land use datasets: USGS and updated New Land Use (NLU). The performances of WRF configurations were assessed by comparing simulated and observed data from March to August 2015. The result showed that temperature and rainfall simulations were sensitive to LSM and land use data choice. The combination of NLU with RUC and TD produced very small cold bias (0.27 °C) and warm bias (0.20 °C) for 2m maximum temperature (Tmax) and 2m minimum temperature (Tmin), respectively. WRF model with RUC and NLU captured well the observed spatial and temporal variability of Tmax, while TD and NLU for Tmin. Moreover, rainfall simulation was better with NLU; especially NLU and Noah configuration produced the smallest mean bias (2.39 mm/day) and root mean square error (6.6 mm/day). All the WRF experiments overestimated light and heavy rainfall events. Overall, findings showed that the application of updated land use data substantially improved the WRF model performance in simulating temperature and rainfall. The study would provide valuable support for identifying suitable LSM and land use data that can accurately predict the climate variables in the Blue Nile basin.

Evaluation of phytotoxicity of three organic amendments to collard greens using the seed germination bioassay.

Small-scale vegetable and fruit crop producers in the USA use locally available commercial organic fertilizers and soil amendments recycled from municipal and agricultural wastes. Organic soil amendments provide crops with their nutrient needs and maintain soil health by modifying its physical, chemical, and biological properties. However, organic soil amendments might add unwanted elements such as toxic heavy metals or salts, which might inhibit crop growth and reduce yield. Therefore, the objective of this study was to evaluate phytotoxicity of three commercial organic amendments, chicken manure, milorganite, and dairy manure, to collard greens using the seed germination bioassay and chemical analysis of the organic amendments. The seed germination bioassay was conducted by incubating collard greens seeds to germinate in 1:10 (w/v) organic amendment aqueous extracts. Results of this work identified phytotoxic effects of chicken manure and milorganite, but not dairy manure, to collard greens. Potentially phytotoxic chemicals such as copper, zinc, nickel, and salts were also higher in chicken manure and milorganite compared to dairy manure. In particular, nickel in chicken manure and milorganite aqueous extracts was 28-fold and 21-fold, respectively, higher than previously reported toxic levels to wheat seedlings. The results demonstrate the need for more research on phytotoxicity of commercial organic soil amendments to ensure their safe use in vegetable and fruit crop production systems.

Carbon dioxide emission in relation with irrigation and organic amendments from a sweet corn field.

Soil moisture and organic matter level affects soil respiration and microbial activities, which in turn impact greenhouse gas (GHG) emissions. This study was conducted to evaluate the effect of irrigation levels (75% [deficit], 100% [full], and 125% [excess] of reference crop evapotranspiration requirements), and organic amendments (OA) type (chicken manure [CM] and bone meal [BM]) and OA application rates (0,168, 336 and 672 kg total N ha-1) on (i) soil physical properties (bulk density, organic matter content and soil moisture content) and (ii) soil carbon dioxide (CO2) emissions from a highly weathered tropical Hawai'ian soil. Carbon dioxide readings were consistently taken once or twice a week for the duration of the cropping season. A drip irrigation system was used to apply the appropriate amount of irrigation water to the treatment plots. Treatments were randomly selected and corresponding organic amendments were manually incorporated into the soil. Plots were cultivated with sweet corn (Zea mays 'SS-16'). Soil moisture content within and below the rootzone was monitored using a TDR 300 soil moisture sensor (Spectrum Technologies, Inc., Plainfield, IL, USA) connected with 12 cm long prongs. Soil bulk density and organic matter content were determined at the end of the cropping season. Analysis of variance results revealed that OA type, rate, and their interaction had significant effect on soil CO2 flux (P < 0.05). Among the OA rates, all CM mostly resulted in significantly higher soil CO2 fluxes compared to BM and control treatment (p < 0.05). The two highest rates of BM treatment were not significantly different from the control with regard to soil CO2 flux. In addition, organic amendments affected soil moisture dynamics during the crop growing season and organic matter content measured after the crop harvest. While additional studies are needed to further investigate the effect of irrigation levels on soil CO2 flux, it is recommended that in order to minimize soil CO2 emissions, BM soil amendments could be a potential option to reduce soil CO2 fluxes from agricultural fields similar to the one used in this study.

Soil Water Content Sensor Response to Organic Matter Content under Laboratory Conditions.

Studies show that the performance of soil water content monitoring (SWCM) sensors is affected by soil physical and chemical properties. However, the effect of organic matter on SWCM sensor responses remains less understood. Therefore, the objectives of this study are to (i) assess the effect of organic matter on the accuracy and precision of SWCM sensors using a commercially available soil water content monitoring sensor; and (ii) account for the organic matter effect on the sensor's accuracy. Sand columns with seven rates of oven-dried sawdust (2%, 4%, 6%, 8%, 10%, 12% and 18% v/v, used as an organic matter amendment), thoroughly mixed with quartz sand, and a control without sawdust were prepared by packing quartz sand in two-liter glass containers. Sand was purposely chosen because of the absence of any organic matter or salinity, and also because sand has a relatively low cation exchange capacity that will not interfere with the treatment effect of the current work. Sensor readings (raw counts) were monitored at seven water content levels (0, 0.02, 0.04, 0.08, 0.12, 0.18, 0.24, and 0.30 cm³ cm(-3)) by uniformly adding the corresponding volumes of deionized water in addition to the oven-dry one. Sensor readings were significantly (p < 0.05) affected by the organic matter level and water content. Sensor readings were strongly correlated with the organic matter level (R² = 0.92). In addition, the default calibration equation underestimated the water content readings at the lower water content range (<0.05 cm³ cm(-3)), while it overestimated the water content at the higher water content range (>0.05 cm³ cm(-3)). A new polynomial calibration equation that uses raw count and organic matter content as covariates improved the accuracy of the sensor (RMSE = 0.01 cm³ cm(-3)). Overall, findings of this study highlight the need to account for the effect of soil organic matter content to improve the accuracy and precision of the tested sensor under different soils and environmental conditions.