Reduce Water Usage Research Articles

Automated Plant Watering and Fertilizing with Soil Quality Testing

India is mostly a farming nation. For most Indian households, agriculture is the most important line of work. It is essential to the growth of an agricultural nation. In India, agriculture accounts for 10% of total exports and roughly 16% of GDP. The primary resource for agriculture is water. Water can be supplied by irrigation, although there can sometimes be significant water waste. Consequently, in order to conserve time and water. Agriculture uses the Internet of Things (IoT) technologies a lot these days. As a result, this article discusses a project that is built on the Internet of Things (IoT) and focuses on the agricultural sector with the aim of reducing water usage in the sector. As a result, this essay discusses a project that leverages the Internet of Things (IoT), where all information can be accessed and managed at the touch of a finger, to reduce water consumption in the agricultural sector. We have an idea for a project called an Automated Plant Watering and Fertilizing with Soil Quality Testing. The proposed method makes use of a variety of sensors that sense the different aspects of the soil, such as temperature, humidity, and soil moisture sensors, automatically irrigate the land by turning the motor on and off depending on the soil moisture value. Key Words: Sensors,PH Sensor,Arduino Board,Temp Humidity Sensor DHT-11,Soil Moisture Sensor,Water Motor, Internet of Things (IOT), Solenoid Valve

A pragmatic approach to polymer flooding to accelerate field implementation

Background: Polymer flooding is a well-known enhanced oil recovery technique which can increase recovery factors in mature oilfields above 10% of the oil originally in place. Despite a lengthy history and many published field cases, the speed of deployment is still rather slow. With the need to boost energy production while minimizing energy wastes and carbon emissions, considering this technique known to reduce water usage and accelerate oil recovery should be a must.
 Aim: This short publication aims at providing guidelines to accelerate deployment of polymer injection in various oilfields and a couple of pragmatic approaches recognizing the need for field data instead of poorly constrained simulations or incomplete laboratory studies.
 Materials and methods: After a brief review of the technique and current implementation workflows, we will discuss new approaches to foster the deployment of injection pilots by showing how polymer injection can reduce emissions and energy wastes while accelerating oil production.
 Results: We provide a different perspective on polymer injection with pragmatic tools and ideas showing that going to the field fast provides more information than any laboratory study.
 Conclusion: Given the current need for mitigating oil production declines, polymer flooding is a technique of choice which can be deployed fast if basic criteria explained in this paper are met.

Impacts of Deficit Irrigation on Photosynthetic Performance, Productivity and Nutritional Quality of Aeroponically Grown Tuscan Kale (Brassica oleracea L.) in a Tropical Greenhouse.

Tuscan kale was grown aeroponically with 5, 30 and 60 min nutrient spraying intervals (defined as 5 minNSIs, 30 minNSIs and 60 minNSIs). Four weeks after transplanting, some 5 minNSI plants were transferred to a 60 minNSI (5 minNSI → 60 minNSI) and 90 minNSI (5 minNSI → 90 minNSI) for one more week. Significantly lower light-saturated rates of photosynthesis and stomatal conductance were observed for plants grown with a 60 minNSI than with a 5 minNSI. However, all plants had similar internal CO2 concentrations and transpiration rates. Reduced light use efficiency but increased energy dissipation was observed in plants grown in a 60 minNSI. A higher nitrate concentration was observed in 60 minNSI plants compared to 5 minNSI and 30 minNSI plants, while all plants had similar concentrations of total reduced nitrogen, leaf soluble protein and Rubisco protein. Plants grown with prolonged NSIs (deficit irrigation) had lower biomass accumulation due to the inhibition of leaf initiation and expansion compared to 5 minNSIs. However, there was no substantial yield penalty in 5 minNSI → 60 minNSI plants. Enhancements in nutritional quality through deficit irrigation at pre-harvest were measured by proline and total soluble sugar. In conclusion, it is better to grow Tuscan kale with a 5 minNSI for four weeks followed by one week with a 60 minNSI before harvest to reduce water usage, yield penalty and enhance nutritional quality.

Development of a Digital Twin for smart farming: Irrigation management system for water saving

World agriculture faces the challenge of increasing its agricultural production by 50 % from 2012 to 2050, while reducing water consumption, as agriculture accounts for 69 % of all fresh water used on the planet. The use of technologies such as the internet of things, artificial intelligence, digital twins, among others, in the agricultural environment is increasing. Digital twin applied to agriculture is in its early stages of development. A digital twin is one in which data flows automatically and in both directions between a physical object and a virtual object. Withing this context, this paper presents a digital twin of a smart irrigation system in an application scenario. A digital twin for an irrigation system is one in which the physical components of the system, such as its sensors and actuators, are connected with their virtual representations. The system is composed of a FIWARE-based internet of things platform and a discrete event simulation model in Siemens Plant Simulation software. The internet of things platform is used to collect, aggregate and process soil, weather and crop data to calculate daily irrigation prescriptions. The simulation model is used to simulate the behavior of an irrigation system defined in an application scenario. The communication between the platform and the simulation model happens in real-time and is intermediate by an OPC UA server. A application scenario is considered to evaluate the behavior of the system and to evaluate, in future research, different irrigation strategies. The benefits of the systems proposed are twofold. First, evaluate the behavior of the Internet of Things (IoT) platform and an irrigation system before implementing both in the field. Second, enable the evaluation of different irrigation strategies in parallel with current farm practices. Within the system proposed, farmers can evaluate the behavior of the system before implementing in their farms and allowing the system to operate automatically. It is possible to infer that the system can improve farm operations and reduce water usage by allowing farmers to gather soil, weather and crop information and evaluate multiple irrigation strategies.

AI Based Solar Panel Cleaning Robot

Among the various renewable energies, Solar energy is one of the most important sources. Solar panel is used to collect the solar energy and convert it into useful electrical energy. The dust accumulated on the solar panel reduce its efficiency to a certain degree. To overcome this problem, efficient techniques to clean the solar panel must be implemented. The proposed model is to clean the dust and bird droppings that has accumulated on the solar panel. An AI-based solar panel cleaning robot is designed which performs dry or wet cleaning based on the dirt or bird droppings, thus reducing water usage. The robot utilizes a Convolutional Neural Network model based on the Visual Geometry Group 16 architecture to detect dirt and bird droppings on solar panels. The robot is designed to perform dry cleaning using a brush and wet cleaning using a water pump, depending on the type of dirt detected. The experimental readings show that the power output of the solar panel increases significantly after cleaning, and the prototype model demonstrates the effectiveness of the robot in detecting and cleaning dirt and bird droppings. The development of such a robot has the potential to improve the efficiency of solar panels and reduce water usage in the cleaning process, making it a more sustainable and eco-friendly solution for maintaining solar panels.

Enhancing Disaster Resilience and Long-Term Sustainability: Adaptive and Cultural Architectural Designs of Saudi Arabia

In the heart of Saudi Arabia, a nation grappling with multifaceted climate change challenges, a transformative architectural paradigm has emerged. The region contends with rising temperatures, prolonged heatwaves, water scarcity, and the looming specter of sea-level rise. In response, Saudi Arabia is undergoing an architectural revolution—a fusion of adaptive designs with a profound respect for cultural heritage. This research explores the profound implications of integrating adaptive and culturally nuanced architectural designs into Saudi Arabia\'s unique socio-ecological fabric. A comprehensive methodology, combining a meticulous literature review, in-depth case studies, insightful expert interviews, and data analysis, provides a multifaceted exploration into the realms of energy efficiency, water usage, disaster resilience, cultural preservation, and community acceptance. The findings underscore the marked improvement in energy efficiency achieved through innovative cooling techniques, passive solar design, and energy-efficient materials. This contributes substantially to long-term sustainability. Additionally, sustainable architectural features, such as water-efficient fixtures and innovative landscaping approaches, have led to a significant reduction in water usage, preserving scarce water resources. These designs effectively preserve the rich cultural heritage of Saudi Arabia, ensuring the continuity of cultural identity. The amalgamation of cultural elements and adaptive features in architectural designs stands as a testament to long-term sustainability, reducing resource consumption, energy usage, and environmental impact. Furthermore, adaptive designs have notably elevated disaster resilience, fortifying structures against extreme heat, sandstorms, and heavy rainfall. The confluence of traditional and adaptive architectural elements has resulted in robust structures that can withstand environmental challenges, minimizing infrastructure damage, and safeguarding cultural assets. Lastly, the incorporation of cultural elements in architectural designs has garnered high levels of community acceptance and appreciation, fostering a sense of connection and belonging.

Identification of Sustainability factors of Self-Compacting Geopolymer Concrete for precast construction using SEM

Today's cement concrete industry is a major polluter. Cement, used as a binder in cement concrete, is made by high-temperature combustion, which raises atmospheric CO2 levels and contributes to climate change and natural resource depletion. As raw supplies diminish, several governments begin to levy carbon taxes. Numerous research have been undertaken to produce an innovative and ecologically advantageous construction material known as Geopolymer concrete (GC) in order to minimise and eliminate greenhouse gas emissions. In order to connect coarse aggregates (CA), fine aggregates (FA), and other materials in GC and improve concrete quality while using fewer natural resources, it is essential to replace cement with a byproduct substance rich in silicon and aluminium, such as red mud, fly ash (FA), rice husk ash (RHA), silica fume (SF), ground granulated blast furnace slag (GGBS), and others, activated by a high alkaline solution (AS). In this study were surveyed online and precast self-compacting geopolymer concrete's sustainability was examined. The data underwent factor analysis. Principal component analysis is used to extract factors. According to the research, there are 9 key variables to consider: Reduction in Carbon Footprint, Utilization of Waste Materials, Environmentally Friendly, Reduce Water usage during production, Low Maintenance, Augmentation of Mechanical Properties of Concrete, Natural Materials, Cost Effective, Reduction in Energy consumption during production. These are the nine primary sustainability criteria of Self-Compacting Geopolymer Concrete for Precast Construction.

Technology Focus: EOR Modeling (January 2023)

The oil and gas industry is facing unprecedented responsibility and expectations to keep fueling the world’s economies and social developments with reliable, accessible, safe, and affordable energy sources while responding to the global urgency to safeguard natural resources and protect the environment. Most major oil and gas companies have announced decarbonization strategies for low-carbon or net-zero emissions associated with their business operations. Consequently, reducing the carbon intensity of oil production [kilograms of carbon dioxide (CO2) equivalent emitted per produced barrel of oil] will be pivotal to meeting the environmental mandate. On the other hand, approximately 70% of the world’s counties have set targets to reach net zero within the next 3–5 decades, including emissions from burned hydrocarbon, which is a major challenge. Within this exigent mission to transition the industry, a major question arises about the merit and the role of enhanced oil recovery (EOR). With a share below 3% of the global oil production, field-scale EOR deployment and contribution have been modest despite substantial investments made in research and development and piloting in the last 4 decades. This underperformance of EOR has been attributed mostly to competitive alternatives (waterflooding), high cost, complex infrastructure and supply chains, fluctuating oil prices, and others. In the era of thirst for sustainability in our industry, there are reviving opportunities for selective EOR methods that can achieve efficient oil production with low carbon intensity. For instance, CO2 EOR is intuitively a win/win technology. This method may not be feasible everywhere for various reasons, however, including the availability and proximity of CO2 sources and the suitability of reservoir conditions. Chemical EOR methods, such as low-salinity, polymer-, and surfactant-based methods with low chemical usages have the potential to reduce water usage and enhance recovery factors, particularly from tight oil reservoirs. In contrast, EOR methods that are inherently associated with high carbon intensity, such as thermal EOR, will face stricter constraints to perform, including prohibitive costs for carbon offsetting. Advanced modeling and optimization, including guided machine learning and data analytics, will be crucial to maximizing recovery, quantifying uncertainties, and managing risk while preserving resources and reducing costs. The selected papers in this feature include examples of innovative approaches for developing efficient EOR schemes and advanced modeling and optimization. In one inclusion, optimized water chemistry is engineered for various EOR schemes (e.g., polymer, surfactant, CO2) to improve efficiency while reducing chemical usage. The second inclusion demonstrates an integrated core-to-field work flow to design surfactant-based EOR for a tight formation at the laboratory scale and demonstrate its performance using field-scale simulations. An integrated optimization approach for a Permian CO2-EOR field is demonstrated in the third paper, where an advanced Bayesian framework is used to capture uncertainties. Our industry has consistently demonstrated resilience, adaptivity, and creativity. In the era of industry transition to low-carbon operations, opportunities exist for selective EOR methods to revive and contribute. Recommended additional reading at OnePetro: www.onepetro.org. SPE 208121 Polymer Injection To Unlock Bypassed Oil in a Giant Carbonate Reservoir: Bridging the Gap Between Laboratory and Large-Scale Polymer Project by Clement Fabbri, ADNOC, et al. SPE 208127 The World’s First Offshore Gravity-Assisted Simultaneous Water-Alternating-Gas EOR Full-Field Implementation by Ahmad Khanifar, Petronas, et al. SPE 207449 Numerical Optimization of Water-Alternating-Gas Injection in a Sandstone Field Using a Coupled Surface and Subsurface Model by Thaer I. Ismail, Khalifa University of Science and Technology, et al.

An intelligent IOT sensor coupled precision irrigation model for agriculture

Sustainable agricultural practices are required, especially for irrigation, to provide for a growing population. About 85% of the freshwater resources in the world are used for irrigation. "Us," current irrigation procedures must be either updated or replaced with cutting-edge, intelligent systems that utilize the ML, IoT (Internet of Things), and sensor networks which are wireless. In the proposed paper, a brainy system for tracking and scheduling accuracy irrigation using IoT, a LoRa-based machine learning (ML) is being introduced. We developed an independent irrigation technique that would provide the tomato and eggplant with the precise amount of water they required was set up using the information obtained from the soil moisture sensors. In comparison to traditional watering, which required 7541 mL for the banana plant and 8755 mL for the rice plant, the irrigation system irrigated the plants with an overall quantity of 5010.745 mL & 4421.09 mL in one month. Overall, this led to a 46% reduction in water usage, and the plants looked better than they would have with conventional watering. The simulation results clearly show that the suggested approach uses water more sensibly than cutting-edge models in the experiment farming region.

Sustainability in interventional radiology: are we doing enough to save the environment?

BackgroundHealthcare waste contributes substantially to the world’s carbon footprint. Our aims are to review the current knowledge of Interventional Radiology (IR) waste generation and ways of reducing waste in practice, to quantify the environmental and financial impact of waste generated and address green initiatives to improve IR waste management.MethodsA systematic literature search was conducted in July 2022 using the Medline and Embase literature databases. The scope of the search included the field of IR as well as operating theatre literature, where relevant to IR practice.ResultsOne-hundred articles were reviewed and 68 studies met the inclusion criteria. Greening initiatives include reducing, reusing and recycling waste, as well as strict waste segregation. Interventional radiologists can engage with suppliers to reformulate procedure packs to minimize unnecessary items and packaging. Opened but unused equipment can be prevented if there is better communication within the team and increased staff awareness of wasted equipment cost. Incentives to use soon-to-expire equipment can be offered. Power consumption can be reduced by powering down operating room lights and workstations when not in use, changing to Light Emitting Diode (LED) and motion sensor lightings. Surgical hand wash can be replaced with alcohol-based hand rubs to reduce water usage. Common barriers to improving waste management include the lack of leadership, misconceptions regarding infectious risk, lack of data, concerns about increased workload, negative staff attitudes and resistance to change. Education remains a top priority to engage all staff in sustainable healthcare practices.ConclusionInterventional radiologists have a crucial role to play in improving healthcare sustainability. By implementing small, iterative changes to our practice, financial savings, greater efficiency and improved environmental sustainability can be achieved.

From a Single-Stage to a Two-Stage Countercurrent Extraction of Lipids and Proteins from Full-Fat Chickpea Flour: Maximizing Process Extractability and Economic Feasibility

The mainstream adoption of chickpea proteins and lipids requires a thorough understanding of the impact of critical extraction parameters (enzyme use, reaction time, and solids-to-liquid ratio—SLR) and modes of extraction (single-stage extraction—SSE and countercurrent extraction—CCE) on the simultaneous extraction of lipids and proteins from full-fat chickpea flour and economic process feasibility. A kinetics study revealed that 68.5% oil and 87% protein extraction yields can be achieved using 0.5% protease at pH 9.0, 50 °C, 60 min, and 1:10 SLR, highlighting the role of proteolysis and an adequate incubation time on overall extractability. An increased gradient concentration between the matrix and aqueous media solutes at a lower SLR (1:15), and reduced slurry viscosity increased oil and protein extractability to 80 and 91%, respectively. The high-water usage in the SSE was addressed by the development of a two-stage CCE that reduced water usage by 47% while increasing oil and protein extractability to ~96%. Higher extractability and reduced water usage in the two-stage CCE resulted in a higher net gross profit, thus outweighing its higher operating costs. The results presented herein further widen the scope of bioprocessing standards for full-fat chickpea flour and add to the elucidation of the impact of key processing conditions on the extractability and economic feasibility of the production of chickpea ingredients for subsequent food/nutraceutical applications.

Rediscovering wild food to diversify production across Australia's agricultural landscapes

Conventional agriculture currently relies on the intensive and expansive growth of a small number of monocultures, this is both risky for food security and is causing substantial environmental degradation. Crops are typically grown far from their native origins, enduring climates, pests, and diseases that they have little evolutionary adaptation to. As a result, farming practices involve modifying the environment to suit the crop, often via practices including vegetation clearing, drainage, irrigation, tilling, and the application of fertilizers, pesticides, and herbicides. One avenue for improvement, however, is the diversification of monoculture agricultural systems with traditional foods native to the area. Native foods benefit from evolutionary history, enabling adaptation to local environmental conditions, reducing the need for environmental modifications and external inputs. Traditional use of native foods in Australia has a rich history, yet the commercial production of native foods remains small compared with conventional crops, such as wheat, barley and sugarcane. Identifying what native crops can grow where would be a first step in scoping potential native food industries and supporting farmers seeking to diversify their cropping. In this study, I modeled the potentially suitable distributions of 177 native food and forage species across Australia, given their climate and soil preferences. The coastal areas of Queensland's wet tropics, south-east Queensland, New South Wales, and Victoria were predicted to support the greatest diversity of native food and forage species (as high 80–120 species). These areas also correspond to the nation's most agriculturally intensive areas, including much of the Murray-Darling Basin, suggesting high potential for the diversification of existing intensive monocultures. Native crops with the most expansive potential distribution include Acacia trees, Maloga bean, bush plum, Emu apple, native millet, and bush tomatoes, with these crops largely being tolerant of vast areas of semi-arid conditions. In addition to greater food security, if diverse native cropping results in greater ecosystem service provisioning, through carbon storage, reduced water usage, reduced nutrient runoff, or greater habitat provision, then payment for ecosystem service schemes could also provide supplemental farm income.

Water usage reduction and CSR committees: Taiwan evidence

AbstractAlthough board‐level corporate social responsibility (CSR) committees have been discussed extensively, we know relatively little about how CSR committees affect companies' water conservation and the contingencies that influence this relationship, specifically in emerging markets. In Taiwan, industrial water conservation is an imperative climate change adaptation given the elevating incidence of floods and droughts brought on by climate change. This study extensively hand‐collects data on water usage, the existence of CSR committees from CSR reports, and the annual reports of companies listed on the Taiwan Stock Exchange and Taipei Exchange companies during 2017–2020. Our findings support the stakeholder theory that the existence of CSR committees likely set water use reduction targets and facilitated water usage reduction. Moreover, this relationship is stronger in water consumption industries. In summary, the memberships in water consumption industries and CSR committees are complements rather than substitutes.

Comparative economic and environmental assessments of furrow- and flood-irrigated rice production systems

Rice producers in the Mid-South of the United States face decreasing groundwater availability and increasing pumping depths which may jeopardize sustainable rice production. Recently, producers have started adopting furrow irrigated rice (FIR) which reduces irrigation requirements by approximately 17 % compared to conventionally flooded rice (CIR). Although driven by water savings and ease of planting and harvesting, as FIR does not require levies to be built, there are both yield (quantity) and milling (quality) concerns with FIR production. While some view FIR as a more sustainable production practice because of its reduced water usage, a comprehensive Life Cycle Analysis (LCA) has not been conducted to compare the two production systems. This study compares the economic (yield differences, NPV of water conserved and milling discounts/premiums) and environmental (a stepwise LCA which monetizes the holistic environmental of CIR and FIR on a per kg of rice basis) differences between CIR and FIR. Profitability results indicate that CIR more profitable and LCA results show that CIR is more environmentally sustainable. These results present a Gordian knot for policy makers and rice stakeholders alike as they struggle between a production practice that has a lower environmental impact (CIR) versus one that conserves water, reduces soil disturbance, and offers more flexibility to respond to market and weather conditions (FIR). Water savings has historically been a key focus of rice production from an environmental sustainability standpoint. Our research indicates that failure to both recognize and quantify holistic environmental metrics besides water savings may provide misleading recommendations.

Multispectral image analysis detects differences in drought responses in novel seeded Miscanthus sinensis hybrids

AbstractDrought tolerance in Miscanthus sinensis is a desirable trait because of its potential use to develop new varieties, namely intra‐specific hybrids, adapted to drought‐prone marginal lands. In this study, drought tolerance was evaluated on 8 M. sinensis intra‐specific hybrids (GRC1–GRC8). Plants were grown in the growth chamber (14/10 h, 25/20°C, 70% relative air humidity and 300 μmol m−2 s−1 irradiance). Drought was induced by withholding irrigation for 21 days (stress phase) and after re‐watering (recovery phase) for 7 days. Nondestructive multispectral 3D images for plant morphology, color, and chlorophyll fluorescence imaging were used to quantify drought‐induced changes on a weekly basis for the entire duration of the experiment. Total leaf area (TLA) and digital biomass (DB) responded most rapidly to water deficits (7–14 days), followed by leaf senescence (14–21 days), and finally, a drop in the maximum efficiency of PSII (Fv/Fm; 21 days). Traits measured on the last day of the drought treatment were used to calculate the phenotypic plasticity. Significant differences in drought susceptibility and phenotypic plasticity were found among the studied hybrids. Drought treatment (21 days) reduced DB and TLA on average by 50%, normalized difference vegetation index (NDVI) by 20% and Fv/Fm from 0.79 (in control) to 0.69 in the less drought‐susceptible hybrids (GRC4 and GRC5), whereas in drought‐sensitive hybrids (GRC2 and GRC3), 21 days of drought reduced DB and TLA on average by 80%, NDVI by 45% and Fv/Fm dropped from 0.79 (in control) to 0.35. The more drought‐resilient hybrids showed lower phenotypic plasticity than their more sensitive counterparts, a stay‐green strategy enabled through lower biomass accumulation and by extension, reduced water usage. Multispectral imaging and image analysis enabled fast and nondestructive quantification of plant morphological and physiological responses under drought conditions and could be used as an effective screening tool for drought susceptibility.

Evaluation of water consumption in rapid sand filters backwashed under varied physical conditions

Egypt suffers from water scarcity. In water treatment plants using sand filters, a significant amount of treated water is consumed, estimated at 10%–15% of the filtered water during backwashing. The objective of this study is to determine the most effective way to reduce the amount of treated water used for backwashing. The methodology of this study was to evaluate the effects of air and water rates, treated water turbidity of 1.6 NTU or slightly higher synthetic turbidity of 4.0 NTU, and media type with single or dual media on reducing treated water consumption during rapid sand filter backwashing procedures. The experimental set up was a bench-scale filter operated at a filtration rate of 189 m3/m2/day. Backwashing with the right water and air rates reduce water usage by 18%, enhanced process performance, and reduced the ripening period. Backwashing using synthetic turbid water recovered 100% of the treated water and improved the ripening duration without affecting backwashing efficiency. This study concluded that backwashing the dual media filter with silica sand and activated carbon achieved the highest treated backwash water consumption by approximately 60%. While anthracite coal was utilized as a dual-media filter, the least reduction in treated water consumption was discovered.

Blue revolution for food security under carbon neutrality: A case from the water-saving and drought-resistance rice

Blue revolution for food security under carbon neutrality: A case from the water-saving and drought-resistance rice

High impact water conservation: factors explaining residents’ intent to reduce irrigated area in the yard

ABSTRACT As water scarcity worsens, social scientists seek strategies that facilitate water conservation behaviours. This study analyses the factors driving engagement in a high-impact behaviour in residential landscapes, eliminating irrigated areas in one’s yard, to guide future social marketing efforts to reduce water usage. Feelings of internal commitment (i.e., personal norms) had the strongest relationship with this behaviour followed by social pressure (i.e., subjective norms), demonstrating the influence perceived personal and societal obligations have on water conservation. Practitioners, policymakers and scientists working on urban water issues should focus on these normative influences to ensure proliferation of the identified practice.

Economic penalties associated with irrigation during high rainfall years in the southeastern United States

Although cotton is a drought-tolerant crop, irrigation is still needed to ensure productivity, even in the humid Southeastern United States. Irrigation must be carefully managed to limit unnecessary water use while ensuring maximum economic productivity. To better understand the costs and net returns of irrigation and cultivar selection, field experiments were conducted in 2016 and 2017 to compare cotton lint yield and fiber quality in dryland plots and plots irrigated using the University of Georgia checkbook method (UGA Checkbook) at a field site near Camilla, Georgia. Results showed cultivar differences in fiber quality parameters of micronaire and uniformity in 2016, but there was no cultivar difference in fiber quality in 2017. Cultivar differences were not observed in yield or net returns for both years. However, stoplight chart analysis of net returns indicated differences in cultivar selection for irrigated or dryland production. ST 6182 GLB2 would be a better option for a producer to minimize downside risk under dryland conditions, and PHY 333 WRF would be a better option under irrigated production. Results also indicated that broadly applying simplistic water balance approaches could decrease yield, water productivity, and net returns, especially in environments where rainfall is sufficient yet unpredictable. Overirrigation affected some fiber quality parameters but did not impact the overall market price for cotton. In 2016, irrigating according to the UGA Checkbook method negatively impacted yield and net returns. In 2017, irrigation did not affect yield but negatively impacted net returns. Average losses in net returns associated with excessive irrigation in these two wet years were $336 per hectare for net return over irrigation variable costs, and $645 per hectare for net return over irrigation total costs. Implementing robust, efficient irrigation strategies is necessary to achieve high cotton yields, reduce water usage, and improve economic returns.

Effect of modified washing process on water usage, composition and gelling properties of grass carp surimi.

Washing is an essential process in surimi production, from which a large amount of wastewater is generated. Due to the increasing pressure of environmental protection, it is an urgent technical requirement for surimi manufacturers to reduce water usage while maintaining the quality of surimi. In this study, composition, structure and gelling properties of grass carp surimi prepared with a modified washing process (MWP) were investigated. Intermediate dehydration with various compression ratios were utilized between two washing cycles. Water usage and wastewater discharge were reduced significantly by 33% and 38%, respectively, when MWP was applied. As the compression ratio increased, composition of fat, cathepsins, transglutaminase and heme proteins in surimi decreased gradually. Yield, protein content and the major protein pattern of surimi were not changed, but surface hydrophobicity gradually decreased. As the compression rate increased to 1:2.0, textural values and water holding capacity of the corresponding surimi gel decreased gradually, while whiteness increased and then remained unchanged. At a higher compression ratio (>1:1.5), aggregated network and excessive free water were observed in the surimi gel. Composition and gelling properties of the MWP surimi with a compression ratio of 1:1.2-1:1.5 were equal to those of the surimi prepared under conventional three-cycle washing. Results indicated that MWP demonstrated its great potential in surimi production by dramatically reducing the usage of cold water and discharge of wastewater without scarifying surimi quality. © 2022 Society of Chemical Industry.