Evaluating the Effect of Combined Water and Salinity Stresses in Estimating the Fodder Maize Biological Yield Through Periodic Evaporation and Transpiration

IntroductionThe rise in water demand and reduction of water quality and soil in irrigating areas, especially in dry and semi-arid areas of the world, have turned into one of the most crucial challenges for water and soil engineering in recent years. This issue leads us toward optimal quantitative and qualitative management of these valuable resources aimed at achieving economic performance and water productivity. The periodic evaporation and transpiration of the plant in the conditions of simultaneous water and salinity stress are known as one of the most important factors in the qualitative and quantitative growth of the plant yield. Applying mathematical models that simulate the relationship between field variables and yield can be seen as a useful tool in water and soil management issues in such a situation, which has the potential to ensure optimal use of the water and soil resources of any country by providing the plant's water needs and preventing its further loss.Materials and MethodsA factorial experiment was performed in 2019 based on completely randomized blocks design with three replications in plots with an area of 9 square meters at the agricultural and animal husbandry farm of Aliabad Fashafuyeh, located in Qom province to examine the simultaneous effect of different levels of water stress and salinity on the periodic evaporation-transpiration and fresh yield of the single cross 704 forage corn cultivar. The applied treatments included the irrigation water salinity at three electrical conductivity levels of 1.8 (S0), 5.2 (S1), and 8.6 (S2) deci Siemens/meter (dS/m), which were prepared by mixing saline well water of the region with fresh (drinking) water and three water stress levels of 100% (W0), 75% (W1), and 50% (W2) of the plant's water requirement. The depth of soil moisture in the corn plant root zone was measured by the TDR device at five depths of 7.5, 12, 20, 40, and 60 cm during different growth stages of the plant using pairs of 7.5, 12, and 20 cm stainless steel electrodes.Results and DiscussionThe simultaneous water and salinity stresses, which led to the reduced amount of periodic evaporation-transpiration of the yield compared to ideal conditions (without stress), were simulated by additive and multiplicative models. The results suggested a decrease in the evaporation and transpiration with the increased simultaneous water and salinity stresses so that the amount of total evaporation-transpiration in different treatments was measured to be between 692.7 and 344.9 mm and the fresh yield was estimated between 50.4 and 3.2 tons per hectare. Also, the highest amount of periodic evaporation and transpiration in all treatments was found to occur in the development and intermediate stages, and the relative fresh yield in the W0S0 to W2S2 treatments was calculated between 66% and 100%. The results of modeling the relative yield of the crop based on the amounts of relative evaporation and transpiration of corn in different growth stages and under the different treatments of water stress and salinity, indicated that Singh's additive model and Rao's multiplicative model were appropriate, while the Minhas model was recognized to be inappropriate in this estimation.ConclusionThe research results suggested the significant impact of water stress and salinity at least at the 95% level on evaporation and transpiration and the corn yield. Moreover, the effect of the sensitivity of different growth stages of the plant on the reduction of evaporation and transpiration of corn varies so that in the three treatment groups W0, W1, and W2, the highest average decrease in slope was related to the final stage (13.6%) followed by the middle stage with an average decrease of 8.4% compared to the control treatment. Therefore, the highest decrease rate in evaporation-transpiration slope has been observed in these two growth stages due to the beginning of flowering, fruit formation, and physiological ripening of seeds. These results come from the lack of sufficient water storage and increased salinity of irrigation water in the soil. Water stresses and salinity will reduce water absorption and evaporation-transpiration, and ultimately, reduce crop production due to the decreased amount and potential of water in the soil. Another finding to be mentioned is the priority of water stress compared to salinity stress in reducing evaporation and transpiration and production yield. Also, by managing water and salinity stresses in the critical stages of plant growth (especially the middle stage), which is the time of flowering and the beginning and completion of the maize production process, a significant reduction in the crop can be somewhat prevented

Evaluación de modelos para estimar la infiltración y rugosidad del riego por surcos

Several methods have been proposed for estimating infiltration and roughness parameters in surface irrigation using mathematical models. The EVALUE, SIPAR_ID, and INFILT models were used in this work. The EVALUE modeluses a direct solution procedure, whereas the other two models are based on the inverse solution approach. The objective of this study is to evaluate the capacity of these models to estimate the Kostiakov infiltration parameters and the Manning roughness coefficient in furrow irrigation. Twelve data sets corresponding to blocked-end and free drainingfurrows were used in this work. Using the estimated  parameters and the SIRMOD irrigation simulation software, the total infiltrated volume and recession time were predicted to evaluate the accuracy of the mathematical models. TheEVALUE and SIPAR_ID models provided the best performance, with EVALUE performing better than SIPAR_ID for estimating the Manning roughness coefficient. The INFILT model provided lower accuracy in cut-back irrigation than in standard irrigation. The performance of SIPAR_ID and INFILT in blocked-end and free draining furrows was similar.En el riego por superficie se han propuesto varios métodos basados en modelos matemáticos para estimar los  parámetros de infiltración y rugosidad. En este trabajo se han utilizado los modelos EVALUE, SIPAR_ID e INFILT. El modelo EVALUE utiliza un procedimiento de solución directa, mientras que los otros dos se basan en un enfoque de solución inversa. El objetivo de este estudio fue evaluar la capacidad de estos modelos para estimar los parámetros deinfiltración de Kostiakov y el coeficiente de rugosidad de Manning en el riego por surcos. Se utilizaron en doce evaluaciones de riego por surcos, bien bloqueados en el extremo o bien con desagüe libre. Utilizando los parámetros estimados y el software de simulación de riego por gravedad SIRMOD, se predijeron el volumen total infiltrado y el tiempo de receso para evaluar la precisión de los modelos  matemáticos. Los modelos EVALUE y SIPAR_ID proporcionaronel mejor rendimiento, dando mejores resultados EVALUE que SIPAR_ID para estimar el coeficiente de rugosidad de Manning. El modelo INFILT fue menos preciso en el riego con recorte de caudal que en el riego estándar. El rendimiento de SIPAR_ID e INFILT fue similar en los surcos bloqueados en el extremo y con desagüe libre

Evaluation of the Influence of Different ETO Estimation Methods in Simulation of Wheat Actual Evapotranspiration and Biomass by AquaCrop Model

IntroductionEvaluation of plant models in agriculture has been done by many researchers. The purpose of this work is to determine the appropriate plant model for planning and predicting the response of crops in different regions. This action is made it possible to study the effect of various factors on the performance and efficiency of plant water consumption by spending less time and money. Since the most important agricultural product in Iran is wheat, so proper management of wheat fields has an important role in food security and sustainable agriculture in the country. The main source of food for the people in Iran is wheat and its products, and any action to increase the yield of wheat is necessary due to limited water and soil resources. Evapotranspiration is a complex and non-linear process and depends on various climatic factors such as temperature, humidity, wind speed, radiation, type and stage of plant growth. Therefore, in the present study, by using daily meteorological data of Urmia, Rasht, Qazvin, Mashhad and Yazd stations, the average daily evapotranspiration values based on the results of the FAO-Penman-Monteith method are modeled and the accuracy of the two methods temperature method (Hargreaves-Samani and Blaney-Criddle) and three radiation methods (Priestley-Taylor, Turc and Makkink) were compared with FAO-56 for wheat.Materials and MethodsThe present study was conducted to evaluate the accuracy and efficiency of the AquaCrop model in simulation of evapotranspiration and biomass, using different methods for estimation reference evapotranspiration in five stations (Urmia, Qazvin, Rasht, Yazd and Mashhad). Four different climates (arid, semi-arid, humid and semi-humid) were considered in Iran for wheat production. The equations used to estimate the reference evapotranspiration in this study are: Hargreaves-Samani (H.S), Blaney-Criddle (B.C), Priestley-Taylor (P.T), Turc (T) and Makkink (Mak). Then, the results were compared with the data of the mentioned stations for wheat by error statistical criteria including: explanation coefficient (R2), normal root mean square error (NRMSE) and Nash-Sutcliffe index (N.S).Results and DiscussionThe value of the explanation coefficient (R2) of simulation ET and biomass in the Blaney-Criddle method is close to one, which shows a good correlation between the data. The NRMSE and Nash-Sutcliffe values for both parameters and the five stations are in the range of 0-20 and close to one, respectively, which indicates the AquaCrop model's ability to simulate ET and biomass. On the other hand, the value of R2 in the Hargreaves-Samani method for biomass close to one, NRMSE in the range of 0-10 and Nash-Sutcliffe index is more than 0.5, which indicates a good simulation. The NRMSE index in the evaluation of ET and biomass wheat is excellent for the Blaney-Criddle method and about Hargreaves-Samani for ET is poor and for the biomass is excellent.The Turc method with NRMSE in the range of 0-30, explanation coefficient close to or equal to one and a Nash-Sutcliffe index of one or close to one can be used to simulate ET and biomass at all five stations. Also, for biomass simulation, Priestley-Taylor and Makkink methods have acceptable statistical values in all five stations.Based on the value of explanation coefficient (R2) of estimation ET and biomass wheat for radiation methods, the correlation between the data in all three radiation methods is high. Percentage of NRMSE index of Makkink method for wheat in ET evaluation in Qazvin station is poor category and in Urmia and Rasht is good and in Mashhad and Yazd is moderate and about biomass in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd) is excellent category, the error percentage of Priestley-Taylor method for wheat in ET evaluation in Yazd station is good and the rest of the stations is poor, about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd). The error rate of Turc method for wheat in ET evaluation in Urmia, Rasht and Mashhad stations is good and in Qazvin and Yazd is poor and about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd).ConclusionAccording to the results obtained using Blaney-Criddle method with R2 value close to one, NRMSE in the range of 0-20% (excellent to good) and Nash-Sutcliffe index close to one and Turc method with R2 value close to one, NRMSE in the range of 0-10% (excellent) and Nash-Sutcliffe index close to one was showed a good accuracy of AquaCrop model in simulation of evapotranspiration and biomass with these methods of estimation of evapotranspiration compared to other methods

Evaluating models for the estimation of furrow irrigation infiltration and roughness

Several methods have been proposed for estimating infiltration and roughness parameters in surface irrigation using mathematical models. The EVALUE, SIPAR_ID, and INFILT models were used in this work. The EVALUE model uses a direct solution procedure, whereas the other two models are based on the inverse solution approach. The objective of this study is to evaluate the capacity of these models to estimate the Kostiakov infiltration parameters and the Manning roughness coefficient in furrow irrigation. Twelve data sets corresponding to blocked-end and free draining furrows were used in this work. Using the estimated parameters and the SIRMOD irrigation simulation software, the total infiltrated volume and recession time were predicted to evaluate the accuracy of the mathematical models. The EVALUE and SIPAR_ID models provided the best performance, with EVALUE performing better than SIPAR_ID for estimating the Manning roughness coefficient. The INFILT model provided lower accuracy in cut-back irrigation than in standard irrigation. The performance of SIPAR_ID and INFILT in blocked-end and free draining furrows was similar.En el riego por superficie se han propuesto varios métodos basados en modelos matemáticos para estimar los parámetros de infiltración y rugosidad. En este trabajo se han utilizado los modelos EVALUE, SIPAR_ID e INFILT. El modelo EVALUE utiliza un procedimiento de solución directa, mientras que los otros dos se basan en un enfoque de solución inversa. El objetivo de este estudio fue evaluar la capacidad de estos modelos para estimar los parámetros de infiltración de Kostiakov y el coeficiente de rugosidad de Manning en el riego por surcos. Se utilizaron en doce evaluaciones de riego por surcos, bien bloqueados en el extremo o bien con desagüe libre. Utilizando los parámetros estimados y el software de simulación de riego por gravedad SIRMOD, se predijeron el volumen total infiltrado y el tiempo de receso para evaluar la precisión de los modelos matemáticos. Los modelos EVALUE y SIPAR_ID proporcionaron el mejor rendimiento, dando mejores resultados EVALUE que SIPAR_ID para estimar el coeficiente de rugosidad de Manning. El modelo INFILT fue menos preciso en el riego con recorte de caudal que en el riego estándar. El rendimiento de SIPAR_ID e INFILT fue similar en los surcos bloqueados en el extremo y con desagüe libre

Evaluation of ERA5 Reanalysis Dataset for Simulation of Climatic Variables and Water Harvesting from Humidity (Case Study: Qazvin Province)

Water supply remains a significant challenge in arid and semi-arid regions, and in addressing this concern, unconventional water sources have gained prominence. Notably, the extraction of water from air humidity, classified as an unconventional water source has seen increased adoption. Diverse techniques have been developed to achieve this goal, with the utilization of mesh networks being particularly prevalent. Consequently, this study assesses the evaluation of the performance of the ERA5 dataset in the simulation of atmospheric variables that influence the ability to assess water harvesting from air humidity (including temperature, wind speed, and water vapor pressure). Also, the possibility of water harvesting from air humidity was investigated in Qazvin Province. The outcomes demonstrated the benefit of incorporating adjustment coefficients in estimating temperature and wind speed using the ERA5 dataset. Based on these findings, the northwestern and southern regions of the province (Kuhin and Takestan) exhibit notable potential during spring and summer for water harvesting from the atmosphere. The peak water harvesting for these stations in the summer is estimated at 10.2 and 9.7 l/day.m2, respectively. Using the ERA5 reanalysis dataset, the annual average potential for water harvesting in the stations was evaluated at 7.9 and 4.6 l/day.m2, respectively. Notably, the minimum water harvesting capacity during the summer season recorded in Qazvin is equal to 3.39 l/day.m2, which can be planned for use in irrigation requirements of green spaces, fields, or gardens

Recent developments in enzyme immobilization technology for high-throughput processing in food industries.

The demand for food and beverage markets has increased as a result of population increase and in view of health awareness. The quality of products from food processing industry has to be improved economically by incorporating greener methodologies that enhances the safety and shelf life via the enzymes application while maintaining the essential nutritional qualities. The utilization of enzymes is rendered more favorable in industrial practices via the modification of their characteristics as attested by studies on enzyme immobilization pertaining to different stages of food and beverage processing; these studies have enhanced the catalytic activity, stability of enzymes and lowered the overall cost. However, the harsh conditions of industrial processes continue to increase the propensity of enzyme destabilization thus shortening their industrial lifespan namely enzyme leaching, recoverability, uncontrollable orientation and the lack of a general procedure. Innovative studies have strived to provide new tools and materials for the development of systems offering new possibilities for industrial applications of enzymes. Herein, an effort has been made to present up-to-date developments on enzyme immobilization and current challenges in the food and beverage industries in terms of enhancing the enzyme stability