Search

This paper highlights the evolution and impact of the SWAP model (Soil – Water – Atmosphere – Plant), which was initiated by R.A. Feddes and colleagues fifty years ago, in 1974. Since then, the SWAP model has played a crucial role in the advancement of agrohydrology. This paper highlights some major advances that have been made, especially focussing on the last fifteen years. The domain of the SWAP model deals with the simulation of the soil water balance in both unsaturated and saturated conditions. The model solves the Richards equation using the water retention and hydraulic conductivity functions as described by the Van Genuchten – Mualem equations. Bimodal extensions of the Van Genuchten - Mualem relationships have been implemented, as well as modifications near saturation and addressing hysteresis. An important sink term in the Richards equation is root water uptake. Crop development plays an important role in a robust simulation of root water uptake. That is why a link has been made with the dynamic crop growth model WOFOST. Instead of using a prescribed crop development, a distinction between potential and actual crop development is calculated by reducing the potential photosynthesis as a result of water or oxygen stress. Since the early days of SWAP, empirical and macroscopic concepts have been used to simulate root water uptake. Recently two process-based concepts of root water uptake and oxygen stress have also been implemented. Another important sink-source term in the Richards equation is the interaction with artificial drains. In SWAP, drainage can be simulated by either using prescribed or simulated drain heads and simulation of controlled drainage with subirrigation is possible. Finally, we briefly elaborate on three studies using SWAP: water stresses in agriculture in the Netherlands, regional water productivity in China, and controlled drainage with subirrigation. We finish discussing promising developments for the near future.

This thesis examined the potential for lignite, an acidic organic amendment, to improve the environmental credentials of intensive vegetable production systems in soil and organic growth media. Through a series of laboratory and glasshouse trials it was identified that lignite effectively reduced the environmental impact of nitrogen fertiliser, and pH treatment was required to ensure good crop production. A combination of changes in cation exchange capacity, acidity and porosity were identified as the mechanisms leading to effective treatment with lignite.

Machine learning algorithms are able to capture complex, nonlinear interacting relationships and are increasingly used to predict yield variability at regional and national scales. Using explainable artificial intelligence (XAI) methods applied to such algorithms may enable better scientific understanding of drivers of yield variability. However, XAI methods may provide misleading results when applied to spatiotemporal correlated datasets. In this study, machine learning models are trained to predict simulated crop yield from climate indices, and the impact of model evaluation strategy on the interpretation and performance of the resulting models is assessed. Using data from a process-based crop model allows us to then comment on the plausibility of the ‘explanations’ provided by XAI methods. Our results show that the choice of evaluation strategy has an impact on (i) interpretations of the model and (ii) model skill on heldout years and regions, after the evaluation strategy is used for hyperparameter-tuning and feature-selection. We find that use of a cross-validation strategy based on clustering in feature-space achieves the most plausible interpretations as well as the best model performance on heldout years and regions. Our results provide first steps towards identifying domain-specific ‘best practices’ for the use of XAI tools on spatiotemporal agricultural or climatic data.

Agrobased industries are contributing socio-economic development of the country, distillery industries are using sugarcane molasses as a raw material for alcohol production. Every litre of alcohol production ten to fifteen litres of waste water generated named as spentwash. The disposal of spentwash is a seroious issue and looking for recycling option to enhance soil health.r Distillery Spentwashis important organic liquid manure contain high amount of nutrients like nitrogen, phosphorus, potassium, calcium and sulfur and also it contains high amount of micronutrients such as iron, zinc, copper, manganese, boron and molybdenum. Field experiment was conducted to study the efficiency of Biomethanated distillery spentwash, on improving the yield and quality of Yam at Research and Development farm of Bannari Amman Sugars Ltd., Modur, Sathyamangalamtaluk, Erode district. Distillery Spentwashwas applied in a field with the treatments from 10 to 60 KL/ha and soil samples are collected at initial, vegetative and harvesting stage of Elephant foot yam. The application of spent wash as manure was improved soil health and resulted in increasedroot and shoot length quality and yield of Elephant foot Yam. There was enhanced available N andK status of soil with the application of spent wash, particularly for K.The increase in yield and quality parameters was observed at harvest stage of Elephant foot Yam.Application of Biomethanated Distillery Spentwashat 50 KL/ha recorded higher yield of 38.20 t /ha. Elephant foot yam quality parameters like Carbohydrate, Vitamin C, Beta carotene were significantly increased when compared to control field.

Agrobased industries are contributing socio-economic development of the country, distillery industries are using sugarcane molasses as a raw material for alcohol production. Every litre of alcohol production ten to fifteen litres of waste water generated named as spentwash. The disposal of spentwash is a seroious issue and looking for recycling option to enhance soil health.r Distillery Spentwashis important organic liquid manure contain high amount of nutrients like nitrogen, phosphorus, potassium, calcium and sulfur and also it contains high amount of micronutrients such as iron, zinc, copper, manganese, boron and molybdenum. Field experiment was conducted to study the efficiency of Biomethanated distillery spentwash, on improving the yield and quality of Yam at Research and Development farm of Bannari Amman Sugars Ltd., Modur, Sathyamangalamtaluk, Erode district. Distillery Spentwashwas applied in a field with the treatments from 10 to 60 KL/ha and soil samples are collected at initial, vegetative and harvesting stage of Elephant foot yam. The application of spent wash as manure was improved soil health and resulted in increasedroot and shoot length quality and yield of Elephant foot Yam. There was enhanced available N andK status of soil with the application of spent wash, particularly for K.The increase in yield and quality parameters was observed at harvest stage of Elephant foot Yam.Application of Biomethanated Distillery Spentwashat 50 KL/ha recorded higher yield of 38.20 t /ha. Elephant foot yam quality parameters like Carbohydrate, Vitamin C, Beta carotene were significantly increased when compared to control field.

Agrobased industries are contributing socio-economic development of the country, distillery industries are using sugarcane molasses as a raw material for alcohol production. Every litre of alcohol production ten to fifteen litres of waste water generated named as spentwash. The disposal of spentwash is a seroious issue and looking for recycling option to enhance soil health.r Distillery Spentwashis important organic liquid manure contain high amount of nutrients like nitrogen, phosphorus, potassium, calcium and sulfur and also it contains high amount of micronutrients such as iron, zinc, copper, manganese, boron and molybdenum. Field experiment was conducted to study the efficiency of Biomethanated distillery spentwash, on improving the yield and quality of Yam at Research and Development farm of Bannari Amman Sugars Ltd., Modur, Sathyamangalamtaluk, Erode district. Distillery Spentwashwas applied in a field with the treatments from 10 to 60 KL/ha and soil samples are collected at initial, vegetative and harvesting stage of Elephant foot yam. The application of spent wash as manure was improved soil health and resulted in increasedroot and shoot length quality and yield of Elephant foot Yam. There was enhanced available N andK status of soil with the application of spent wash, particularly for K.The increase in yield and quality parameters was observed at harvest stage of Elephant foot Yam.Application of Biomethanated Distillery Spentwashat 50 KL/ha recorded higher yield of 38.20 t /ha. Elephant foot yam quality parameters like Carbohydrate, Vitamin C, Beta carotene were significantly increased when compared to control field.

Crop growth is one of the most important parameters of a crop and its knowledge before harvest is essential to help farmers, scientists, governments and agribusiness. This paper provides a novel demonstration of the use of freely available Sentinel-2 data to estimate rice crop growth in a single year. Sentinel 2 data provides frequent and consistent information to facilitate coastal monitoring from field scales. The aims of this study were to modify the rice growth vegetation index to improve rice growth phenology in the coastal areas. The rice growth vegetation index 2 is the best vegetation index, compared with 11 vegetation indices, plant height and biomass. The results demonstrate that the coefficient of rice growth vegetation index 2 was 0.83, has the highest correlation with plant height. Rice growth vegetation index 2 is more appropriate for enhancing and obtaining rice phenology information. This study analyses the best spectral vegetation indices for estimating rice growth.

The current research work was conducted to understand the dynamics of nutrients from the organic-inorganic (algae, agri-mat, grass and lime ammonium nitrate) amendments into soil through mineralization, their movement thereafter from the soil to the crop. In addition, the effect of organic materials on some soil physical and chemical properties and crop productivity was investigated through a series of different but interconnected laboratory, glasshouse and field experiments. The first experiment was carried out through a 2-month incubation study to investigate nutrient release (mineralization) capacity of inorganic-organic treatment combinations and organic amendments alone on sandy loam and loam soil. The objective of the incubation study was to determine the nitrogen-mineralization rate of different organic mulching materials singularly and when combined with lime-ammonium nitrate under two soil types. The incubation study was conducted in the laboratory at Agricultural Research Council – Soil, Climate and Water in Arcadia, Pretoria. The experiment consisted of sandy loam and loam soil, each treated with the following seven treatments T1 = control, T2 = 5g of dry algae per 100g of soil, T3 = 5g of ground agri-mat per 100g of soil, T4 = 5g of ground grass per 100g of soil, T5 = 75kgN.ha-1 using Lime Ammonium Nitrate (LAN) + 2.5g of dry algae per 100g of soil (50%NF + 50%DA), T6 = 75kgN.ha-1 using LAN + 2.5g of ground agri-mat per 100g of soil (50%NF + 50%GA), T7 = 50%NF + 50%GG. Each treatment was replicated three times and the experiment was laid out in a completely randomized design. Three experimental units per treatment were drawn at 0, 3, 7, 15, 30, 45, and 60 days for mineral-N (NH4 + -N and NO3 - -N) content determination. The results from the incubation study indicates that all the treatments where organic amendments were added had higher mineralization rates compared to the treatments where organic amendments were applied singularly. The highest amounts o

The current research work was conducted to understand the dynamics of nutrients from the organic-inorganic (algae, agri-mat, grass and lime ammonium nitrate) amendments into soil through mineralization, their movement thereafter from the soil to the crop. In addition, the effect of organic materials on some soil physical and chemical properties and crop productivity was investigated through a series of different but interconnected laboratory, glasshouse and field experiments. The first experiment was carried out through a 2-month incubation study to investigate nutrient release (mineralization) capacity of inorganic-organic treatment combinations and organic amendments alone on sandy loam and loam soil. The objective of the incubation study was to determine the nitrogen-mineralization rate of different organic mulching materials singularly and when combined with lime-ammonium nitrate under two soil types. The incubation study was conducted in the laboratory at Agricultural Research Council – Soil, Climate and Water in Arcadia, Pretoria. The experiment consisted of sandy loam and loam soil, each treated with the following seven treatments T1 = control, T2 = 5g of dry algae per 100g of soil, T3 = 5g of ground agri-mat per 100g of soil, T4 = 5g of ground grass per 100g of soil, T5 = 75kgN.ha-1 using Lime Ammonium Nitrate (LAN) + 2.5g of dry algae per 100g of soil (50%NF + 50%DA), T6 = 75kgN.ha-1 using LAN + 2.5g of ground agri-mat per 100g of soil (50%NF + 50%GA), T7 = 50%NF + 50%GG. Each treatment was replicated three times and the experiment was laid out in a completely randomized design. Three experimental units per treatment were drawn at 0, 3, 7, 15, 30, 45, and 60 days for mineral-N (NH4 + -N and NO3 - -N) content determination. The results from the incubation study indicates that all the treatments where organic amendments were added had higher mineralization rates compared to the treatments where organic amendments were applied singularly. The highest amounts o

Knowledge-driven "smart" irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations.

Successful growth, both vegetative and reproductive, are the final goals for plants. In the case of erops, knowing how plants make use of the available resourees to convert them into biomass, and espeeially, what is the main limiting factor for growth, is of paramount importanee. Although much effort has been dedieated to study how different agronomieal practices affect crop water relations and leaf gas exchange, we still lack the knowledge on the precise conditions that favour or limit plant growth. The classieal view, shared among most seientists, is that earbon limit plant growth. This coneeption makes sense sinee photoassimilates are the brieks to build the biomass. However, other proeesses are as important as C02 uptake. In particular, the maintenance of turgor is as critical for growing as photosynthesis. This misconception on the key limiting factor for growth, giving a major role to the souree aetivity instead of the sink aetivity, has emerged from the limitation and availability ofteehnical methods to evaluate both. In our researeh group we have developed novel methods to overcome these limitations, and we have made them suitable for their use under fieId conditions and long period of time during the growing season. Our results confirrn some opinions found in the literature and support, now with empirical evidence, that photosynlhesis, in most cases, is not lhe main limiting factor for growth but turgor. The new coneept "hours of turgor" emerges and will help us understand the perfonnanee of a speeies under a given environment and the funetional physiological traits thal make the difference in growth among species.

Drought is the most serious environmental challenge that limits plant growth and causes more severe yield losses than other abiotic stress factors resulting in a serious food shortage. Nanomaterials (NMs) are considered as vital tools to overcome contemporary and future challenges in agricultural production. Recently, NMs have been applied for enhancing seed germination, growth, physiology, productivity and quality attributes of various crops under normal or stress conditions. Up to date, there is no a comprehensive review about the potential role of NMs in attenuating the drought-induced adverse effects in crop plants. Thus, this review will highlight this issue. Generally, NMs minimize drought-induced osmotic stress by accumulation of osmolytes that result in osmotic adjustment and improved plant water status. In addition, NMs play a key role to improve root growth, conductive tissue elements and aquaporin proteins facilitating uptake and translocation of water and nutrients. Furthermore, NMs reduce water loss by stomatal closure due to abscisic acid signaling. However, this leads to reduced photosynthesis and oxidative stress damage. At the same time, NMs increase the content of light-harvesting pigments, enzymatic and non-enzymatic antioxidants leading to enhancing photosynthesis with reducing oxidative stress damage. Overall, NMs can ameliorate the deleterious effects of drought stress in crop plants by regulation of gene expression and alternation of various physiological and biochemical processes.

Chickpea is a legume, which is grown in two regions of Mexico mainly, Northwest (Sonora, Sinaloa and Baja California) and El Bajío region (Guanajuato, Michoacán and Jalisco); however, each year the production of the culture is compromised with vascular fusariosis, one of the main diseases that affect the culture and that is associated with the fungal complex Fusarium oxysporum,Fusarium solani, Rhizoctonia solani,Macrophomina phaseolinaand Sclerotium rolfsii.An alternative of biological control is the application of Trichoderma, which also has an indirect effect on the nutrition of the plant. The objective of this study was to determine the in vitroantagonism of two strains of Trichoderma harzianum(T1 and T2) and its effect as a biofertilizer. In vitroconfrontations were carried out against strains of the Fusarium oxysporumf. sp. ciceris(Foc 0, 1B/C, 5 and 6), Fusariumsolani, Macrophomina phaseolina(M-Sonora and M-GTO) and Sclerotium rolfsii. The effectof T2 as a biofertilizer (TB) was evaluated by measuring the variables: number of flowers, pods, plant height, stem diameter, root length and grain yield. The two strains of T. harzianumshowed antagonism on different scales against pathogens. Additionally, with the treatment where T. harzianum(TB) was applied, there were increases in the number of flowers (30%), pods (24%), height (3%), plant diameter (3.5%), as well as root length (13%) and grain yield (23%)., El garbanzo es una leguminosa, que se cultiva en dos regiones de México principalmente, noroeste (Sonora, Sinaloa y Baja california) y la región de El Bajío (Guanajuato, Michoacán y Jalisco); sin embargo, cada año la producción del cultivo está comprometida con la fusariosis vascular, una de las principales enfermedades que afectan al cultivo y que está asociada al complejo fúngico Fusarium oxysporum, Fusarium solani, Rhizoctonia solani, Macrophomina phaseolina y Sclerotium rolfsii. Una alternativa de control biológico es la aplicación de Trichoderma, la que además tiene un efecto indirecto en la nutrición de la planta. El objetivo de este estudio fue determinar el antagonismo in vitro de dos cepas de Trichoderma harzianum (T1 y T2) y su efecto como biofertilizante. Se realizaron confrontaciones in vitro contra cepas de las razas de Fusarium oxysporum f. sp. ciceris (Foc 0, 1B/C, 5 y 6), Fusarium solani, Macrophomina phaseolina (MSonora y M-GTO) y Sclerotium rolfsii. Se evaluó el efecto de T2 como biofertilizante (TB) midiendo las variables: número de flores, vainas, altura de la planta, diámetro del tallo, longitud de la raíz y rendimiento de grano. Las dos cepas de T. harzianum mostraron antagonismo en diferente escala contra los patógenos. Adicionalmente, con el tratamiento donde se aplicó T. harzianum (TB) se presentaron incrementos en el número de flores (30%), vainas (24%), altura (3%), diámetro de las plantas (3.5%), así como la longitud de la raíz (13%) y rendimiento del grano (23%).

Drought is the most serious environmental challenge that limits plant growth and causes more severe yield losses than other abiotic stress factors resulting in a serious food shortage. Nanomaterials (NMs) are considered as vital tools to overcome contemporary and future challenges in agricultural production. Recently, NMs have been applied for enhancing seed germination, growth, physiology, productivity and quality attributes of various crops under normal or stress conditions. Up to date, there is no a comprehensive review about the potential role of NMs in attenuating the drought-induced adverse effects in crop plants. Thus, this review will highlight this issue. Generally, NMs minimize drought-induced osmotic stress by accumulation of osmolytes that result in osmotic adjustment and improved plant water status. In addition, NMs play a key role to improve root growth, conductive tissue elements and aquaporin proteins facilitating uptake and translocation of water and nutrients. Furthermore, NMs reduce water loss by stomatal closure due to abscisic acid signaling. However, this leads to reduced photosynthesis and oxidative stress damage. At the same time, NMs increase the content of light-harvesting pigments, enzymatic and non-enzymatic antioxidants leading to enhancing photosynthesis with reducing oxidative stress damage. Overall, NMs can ameliorate the deleterious effects of drought stress in crop plants by regulation of gene expression and alternation of various physiological and biochemical processes.

Chickpea is a legume, which is grown in two regions of Mexico mainly, Northwest (Sonora, Sinaloa and Baja California) and El Bajío region (Guanajuato, Michoacán and Jalisco); however, each year the production of the culture is compromised with vascular fusariosis, one of the main diseases that affect the culture and that is associated with the fungal complex Fusarium oxysporum,Fusarium solani, Rhizoctonia solani,Macrophomina phaseolinaand Sclerotium rolfsii.An alternative of biological control is the application of Trichoderma, which also has an indirect effect on the nutrition of the plant. The objective of this study was to determine the in vitroantagonism of two strains of Trichoderma harzianum(T1 and T2) and its effect as a biofertilizer. In vitroconfrontations were carried out against strains of the Fusarium oxysporumf. sp. ciceris(Foc 0, 1B/C, 5 and 6), Fusariumsolani, Macrophomina phaseolina(M-Sonora and M-GTO) and Sclerotium rolfsii. The effectof T2 as a biofertilizer (TB) was evaluated by measuring the variables: number of flowers, pods, plant height, stem diameter, root length and grain yield. The two strains of T. harzianumshowed antagonism on different scales against pathogens. Additionally, with the treatment where T. harzianum(TB) was applied, there were increases in the number of flowers (30%), pods (24%), height (3%), plant diameter (3.5%), as well as root length (13%) and grain yield (23%)., El garbanzo es una leguminosa, que se cultiva en dos regiones de México principalmente, noroeste (Sonora, Sinaloa y Baja california) y la región de El Bajío (Guanajuato, Michoacán y Jalisco); sin embargo, cada año la producción del cultivo está comprometida con la fusariosis vascular, una de las principales enfermedades que afectan al cultivo y que está asociada al complejo fúngico Fusarium oxysporum, Fusarium solani, Rhizoctonia solani, Macrophomina phaseolina y Sclerotium rolfsii. Una alternativa de control biológico es la aplicación de Trichoderma, la que además tiene un efecto indirecto en la nutrición de la planta. El objetivo de este estudio fue determinar el antagonismo in vitro de dos cepas de Trichoderma harzianum (T1 y T2) y su efecto como biofertilizante. Se realizaron confrontaciones in vitro contra cepas de las razas de Fusarium oxysporum f. sp. ciceris (Foc 0, 1B/C, 5 y 6), Fusarium solani, Macrophomina phaseolina (MSonora y M-GTO) y Sclerotium rolfsii. Se evaluó el efecto de T2 como biofertilizante (TB) midiendo las variables: número de flores, vainas, altura de la planta, diámetro del tallo, longitud de la raíz y rendimiento de grano. Las dos cepas de T. harzianum mostraron antagonismo en diferente escala contra los patógenos. Adicionalmente, con el tratamiento donde se aplicó T. harzianum (TB) se presentaron incrementos en el número de flores (30%), vainas (24%), altura (3%), diámetro de las plantas (3.5%), así como la longitud de la raíz (13%) y rendimiento del grano (23%).

In this comparative research, we applied the HYDRUS (2D/3D) and SALTMED models to investigate the influence of various water-saving irrigation strategies on maize water footprints (WFs). The models were first calibrated and validated based on data collected in a two-year field investigation under five water-saving irrigation treatments: full irrigation (FI), partial root-zone drying at water deficit levels of 55% (PRD55) and 75% (PRD75), and deficit irrigation at the same levels (DI55 and DI75). While the SALTMED model performed well when simulating crop growth parameters, with absolute relative error (RE) of 3.5–12%, the HYDRUS (2D/3D) model was more accurate when simulating soil water and solute transport, with the normalized values of the root mean square error (nRMSEs, 6.7–31.8%) and the mean bias error (nMBEs, 7.7–34.3%) lower than by SALTMED. This better performance of HYDRUS (2D/3D) resulted in 0.6–3.0% and 5.3–30.2% lower values of estimated consumptive and degradative WFs, respectively, compared to values estimated by SALTMED. While no considerable differences were observed among various irrigation treatments regarding their consumptive WFs for the maize production, PRD75 may represent a safer option under the water crisis, since its grey WF was 17.1–77.2% lower than those estimated for the other water-saving irrigation treatments. This WF reduction was accompanied by an insignificant reduction in crop yield and improved N uptake. Based on our results, while HYDRUS (2D/3D) provides more reliable results, both the HYDRUS (2D/3D) and SALTMED models may be applied for the evaluation of new targets implemented for achieving sustainable agriculture in water-scarce regions.

In this comparative research, we applied the HYDRUS (2D/3D) and SALTMED models to investigate the influence of various water-saving irrigation strategies on maize water footprints (WFs). The models were first calibrated and validated based on data collected in a two-year field investigation under five water-saving irrigation treatments: full irrigation (FI), partial root-zone drying at water deficit levels of 55% (PRD55) and 75% (PRD75), and deficit irrigation at the same levels (DI55 and DI75). While the SALTMED model performed well when simulating crop growth parameters, with absolute relative error (RE) of 3.5–12%, the HYDRUS (2D/3D) model was more accurate when simulating soil water and solute transport, with the normalized values of the root mean square error (nRMSEs, 6.7–31.8%) and the mean bias error (nMBEs, 7.7–34.3%) lower than by SALTMED. This better performance of HYDRUS (2D/3D) resulted in 0.6–3.0% and 5.3–30.2% lower values of estimated consumptive and degradative WFs, respectively, compared to values estimated by SALTMED. While no considerable differences were observed among various irrigation treatments regarding their consumptive WFs for the maize production, PRD75 may represent a safer option under the water crisis, since its grey WF was 17.1–77.2% lower than those estimated for the other water-saving irrigation treatments. This WF reduction was accompanied by an insignificant reduction in crop yield and improved N uptake. Based on our results, while HYDRUS (2D/3D) provides more reliable results, both the HYDRUS (2D/3D) and SALTMED models may be applied for the evaluation of new targets implemented for achieving sustainable agriculture in water-scarce regions.

The growth of Eucalyptus pellita in forestry plantations requires attention to water requirements, especially in the initial growth phase from seedling to field-ready plant. In this study, actual evapotranspiration (ETa), crop coefficient (Kc), and the irrigation requirement of E. pellita were assessed during the nursery growth phase (day 40–142). The experimental set-up included lysimeters with different treatments in terms of plants, drainage, and soil conditions. Plant growth and water balance were monitored during June September 2018 in an open nursery area in Riau, Indonesia. ETa was determined by the water balance lysimeter method and potential (reference) evapotranspiration (ETo) was extracted based on the Penman-Monteith method (FAO/56). The results showed that the average Kc value for E. pellita at age 40–142 days is 0.79, which exceeds that reported for E. grandis. The recommended irrigation requirement varies depending on precipitation, from 70 mL/plant/day with no rainfall to zero at precipitation of >30 mm/day. This is the first study to assess water use in E. pellita growing in pots during the nursery phase, which provides guidance on irrigation requirements during their initial growth phase.

Accurate estimation of the soil water balance of the soil-plant-atmosphere system is key to determining the availability of water resources and their optimal management. Evapotranspiration and leaching are the main sinks of water from the system affecting soil water status and hence crop yield. The accuracy of soil water content and evapotranspiration simulations affects crop yield simulations as well. DSSAT is a suite of field-scale, process-based crop models to simulate crop growth and development. A “tipping bucket” water balance approach is currently used in DSSAT for soil hydrologic and water redistribution processes. By comparison, HYDRUS-1D is a hydrological model to simulate water flow in soils using numerical solutions of the Richards equation, but its approach to crop-related process modeling is rather limited. Both DSSAT and HYDRUS-1D have been widely used and tested in their separate areas of use. The objectives of our study were: (1) to couple HYDRUS-1D with DSSAT to simulate soil water dynamics, crop growth and yield, (2) to evaluate the coupled model using field experimental datasets distributed with DSSAT for different environments, and (3) to compare HYDRUS-1D simulations with those of the tipping bucket approach using the same datasets. Modularity in the software design of both DSSAT and HYDRUS-1D made it easy to couple the two models. The pairing provided the DSSAT interface an ability to use both the tipping bucket and HYDRUS-1D simulation approaches. The two approaches were evaluated in terms of their ability to estimate the soil water balance, especially soil water contents and evapotranspiration rates. Values of the d index for volumetric water contents were 0.9 and 0.8 for the original and coupled models, respectively. Comparisons of simulations for the pod mass for four soybean and four peanut treatments showed relatively high d index values for both models (0.94–0.99).

Modern problems in agricultural seek methods to increase the convenience, reliability accuracy and at the same time, cost efficacy in precision farming. To exploit the global research gaps in sustainable agriculture, this thesis organizes three different works committed to provide solutions to three modern agricultural problems: reliable crop modeling, accurate crop counting and cost-effective crop health monitoring. As strategic solutions, this study proposes the use of emerging advancements on recent artificial intelligence technologies, weather forecasting, web-services, aerial imagery and digital image processing to connect the crucial cores of sustainable agriculture visions. The outputs of this work is targeted help decision makers, and specially the farmers themselves, to increase the productivity of farms for better yield, and to draw young people to the farms to meet the global hunger of 21st century with sustainability in life support and food security. The unavailability of seasonal weather data at the simulation time (often beginning of a growth season) forces decision makers in crop growth assessment to consider multiple weather scenarios, which are often generated from longtime observed data. Ironically these scenario immediately become "outdated" as soon as the season begins, because they are always different from newly observed data. In the first research of this thesis, we investigate this dilemma and in particular address three questions: determination of most successful scenario, classification of scenarios into fresh and stale, and generation of a new scenario from fresh scenarios. Algorithms to solve these questions are given as strategies for prediction games of weather generators. We also elaborate on the applications of our results in networking existing weather generation web services. The production of banana - one of the highly consumed fruits - is highly affected due to loss of certain number of banana plants in an early phase of vegetati

Accurate estimation of the soil water balance of the soil-plant-atmosphere system is key to determining the availability of water resources and their optimal management. Evapotranspiration and leaching are the main sinks of water from the system affecting soil water status and hence crop yield. The accuracy of soil water content and evapotranspiration simulations affects crop yield simulations as well. DSSAT is a suite of field-scale, process-based crop models to simulate crop growth and development. A "tipping bucket" water balance approach is currently used in DSSAT for soil hydrologic and water redistribution processes. By comparison, HYDRUS-1D is a hydrological model to simulate water flow in soils using numerical solutions of the Richards equation, but its approach to crop-related process modeling is rather limited. Both DSSAT and HYDRUS-1D have been widely used and tested in their separate areas of use. The objectives of our study were: (1) to couple HYDRUS-1D with DSSAT to simulate soil water dynamics, crop growth and yield, (2) to evaluate the coupled model using field experimental datasets distributed with DSSAT for different environments, and (3) to compare HYDRUS-1D simulations with those of the tipping bucket approach using the same datasets. Modularity in the software design of both DSSAT and HYDRUS-1D made it easy to couple the two models. The pairing provided the DSSAT interface an ability to use both the tipping bucket and HYDRUS-1D simulation approaches. The two approaches were evaluated in terms of their ability to estimate the soil water balance, especially soil water contents and evapotranspiration rates. Values of the d index for volumetric water contents were 0.9 and 0.8 for the original and coupled models, respectively. Comparisons of simulations for the pod mass for four soybean and four peanut treatments showed relatively high d index values for both models (0.94-0.99).

Modern problems in agricultural seek methods to increase the convenience, reliability accuracy and at the same time, cost efficacy in precision farming. To exploit the global research gaps in sustainable agriculture, this thesis organizes three different works committed to provide solutions to three modern agricultural problems: reliable crop modeling, accurate crop counting and cost-effective crop health monitoring. As strategic solutions, this study proposes the use of emerging advancements on recent artificial intelligence technologies, weather forecasting, web-services, aerial imagery and digital image processing to connect the crucial cores of sustainable agriculture visions. The outputs of this work is targeted help decision makers, and specially the farmers themselves, to increase the productivity of farms for better yield, and to draw young people to the farms to meet the global hunger of 21st century with sustainability in life support and food security. The unavailability of seasonal weather data at the simulation time (often beginning of a growth season) forces decision makers in crop growth assessment to consider multiple weather scenarios, which are often generated from longtime observed data. Ironically these scenario immediately become "outdated" as soon as the season begins, because they are always different from newly observed data. In the first research of this thesis, we investigate this dilemma and in particular address three questions: determination of most successful scenario, classification of scenarios into fresh and stale, and generation of a new scenario from fresh scenarios. Algorithms to solve these questions are given as strategies for prediction games of weather generators. We also elaborate on the applications of our results in networking existing weather generation web services. The production of banana - one of the highly consumed fruits - is highly affected due to loss of certain number of banana plants in an early phase of vegetati

Modern problems in agricultural seek methods to increase the convenience, reliability accuracy and at the same time, cost efficacy in precision farming. To exploit the global research gaps in sustainable agriculture, this thesis organizes three different works committed to provide solutions to three modern agricultural problems: reliable crop modeling, accurate crop counting and cost-effective crop health monitoring. As strategic solutions, this study proposes the use of emerging advancements on recent artificial intelligence technologies, weather forecasting, web-services, aerial imagery and digital image processing to connect the crucial cores of sustainable agriculture visions. The outputs of this work is targeted help decision makers, and specially the farmers themselves, to increase the productivity of farms for better yield, and to draw young people to the farms to meet the global hunger of 21st century with sustainability in life support and food security. The unavailability of seasonal weather data at the simulation time (often beginning of a growth season) forces decision makers in crop growth assessment to consider multiple weather scenarios, which are often generated from longtime observed data. Ironically these scenario immediately become "outdated" as soon as the season begins, because they are always different from newly observed data. In the first research of this thesis, we investigate this dilemma and in particular address three questions: determination of most successful scenario, classification of scenarios into fresh and stale, and generation of a new scenario from fresh scenarios. Algorithms to solve these questions are given as strategies for prediction games of weather generators. We also elaborate on the applications of our results in networking existing weather generation web services. The production of banana - one of the highly consumed fruits - is highly affected due to loss of certain number of banana plants in an early phase of vegetati

Modern problems in agricultural seek methods to increase the convenience, reliability accuracy and at the same time, cost efficacy in precision farming. To exploit the global research gaps in sustainable agriculture, this thesis organizes three different works committed to provide solutions to three modern agricultural problems: reliable crop modeling, accurate crop counting and cost-effective crop health monitoring. As strategic solutions, this study proposes the use of emerging advancements on recent artificial intelligence technologies, weather forecasting, web-services, aerial imagery and digital image processing to connect the crucial cores of sustainable agriculture visions. The outputs of this work is targeted help decision makers, and specially the farmers themselves, to increase the productivity of farms for better yield, and to draw young people to the farms to meet the global hunger of 21st century with sustainability in life support and food security. The unavailability of seasonal weather data at the simulation time (often beginning of a growth season) forces decision makers in crop growth assessment to consider multiple weather scenarios, which are often generated from longtime observed data. Ironically these scenario immediately become "outdated" as soon as the season begins, because they are always different from newly observed data. In the first research of this thesis, we investigate this dilemma and in particular address three questions: determination of most successful scenario, classification of scenarios into fresh and stale, and generation of a new scenario from fresh scenarios. Algorithms to solve these questions are given as strategies for prediction games of weather generators. We also elaborate on the applications of our results in networking existing weather generation web services. The production of banana - one of the highly consumed fruits - is highly affected due to loss of certain number of banana plants in an early phase of vegetati

Modern problems in agricultural seek methods to increase the convenience, reliability accuracy and at the same time, cost efficacy in precision farming. To exploit the global research gaps in sustainable agriculture, this thesis organizes three different works committed to provide solutions to three modern agricultural problems: reliable crop modeling, accurate crop counting and cost-effective crop health monitoring. As strategic solutions, this study proposes the use of emerging advancements on recent artificial intelligence technologies, weather forecasting, web-services, aerial imagery and digital image processing to connect the crucial cores of sustainable agriculture visions. The outputs of this work is targeted help decision makers, and specially the farmers themselves, to increase the productivity of farms for better yield, and to draw young people to the farms to meet the global hunger of 21st century with sustainability in life support and food security. The unavailability of seasonal weather data at the simulation time (often beginning of a growth season) forces decision makers in crop growth assessment to consider multiple weather scenarios, which are often generated from longtime observed data. Ironically these scenario immediately become "outdated" as soon as the season begins, because they are always different from newly observed data. In the first research of this thesis, we investigate this dilemma and in particular address three questions: determination of most successful scenario, classification of scenarios into fresh and stale, and generation of a new scenario from fresh scenarios. Algorithms to solve these questions are given as strategies for prediction games of weather generators. We also elaborate on the applications of our results in networking existing weather generation web services. The production of banana - one of the highly consumed fruits - is highly affected due to loss of certain number of banana plants in an early phase of vegetati

Groundwater is an important factor that needs to be considered when evaluating the water balance of the soil-plant-atmosphere system and the sustainable development of arid oases. However, the impact of shallow groundwater on the root zone water balance and cotton growth is not fully understood. In this study, we have first analyzed the influence of the groundwater table depth on the seasonal maximum leaf area index of cotton, the average seasonal water stress, cotton yield, actual transpiration, actual evaporation, and capillary rise using experimental data collected at the Aksu water balance station, in Xinjiang, northwest of China and the Hydrus-1D variably-saturated soil water flow model coupled with a simplified crop growth model from SWAT. The coupled model has been first calibrated and validated using field observations of soil water content, leaf area index, cotton height, the above ground biomass, and cotton yield comparisons between measured and modeled variables have shown a reasonable agreement for all variables. Additionally, with a validated model, we have carried out numerical experiments from which we have concluded that groundwater is a major water resource for cotton growth in this region. The capillary rise from groundwater contributes almost 23% of crop transpiration when the average groundwater depth is 1.84. m, which is the most suitable groundwater depth for this experimental site. We have concluded that cotton growth and various components of the soil water balance are highly sensitive to the groundwater table level. Different positions of the groundwater table showed both positive and negative effects on cotton growth. Likewise, cotton growth has a significant impact on the capillary rise from groundwater. As a result, groundwater is a crucial factor that needs to be considered when evaluating agricultural land management in this arid region. The updated Hydrus-1D model developed in this study provides a powerful modeling tool for evaluating

Groundwater is an important factor that needs to be considered when evaluating the water balance of the soil-plant-atmosphere system and the sustainable development of arid oases. However, the impact of shallow groundwater on the root zone water balance and cotton growth is not fully understood. In this study, we have first analyzed the influence of the groundwater table depth on the seasonal maximum leaf area index of cotton, the average seasonal water stress, cotton yield, actual transpiration, actual evaporation, and capillary rise using experimental data collected at the Aksu water balance station, in Xinjiang, northwest of China and the Hydrus-1D variably-saturated soil water flow model coupled with a simplified crop growth model from SWAT. The coupled model has been first calibrated and validated using field observations of soil water content, leaf area index, cotton height, the above ground biomass, and cotton yield comparisons between measured and modeled variables have shown a reasonable agreement for all variables. Additionally, with a validated model, we have carried out numerical experiments from which we have concluded that groundwater is a major water resource for cotton growth in this region. The capillary rise from groundwater contributes almost 23% of crop transpiration when the average groundwater depth is 1.84. m, which is the most suitable groundwater depth for this experimental site. We have concluded that cotton growth and various components of the soil water balance are highly sensitive to the groundwater table level. Different positions of the groundwater table showed both positive and negative effects on cotton growth. Likewise, cotton growth has a significant impact on the capillary rise from groundwater. As a result, groundwater is a crucial factor that needs to be considered when evaluating agricultural land management in this arid region. The updated Hydrus-1D model developed in this study provides a powerful modeling tool for evaluating

Due to climate changes and increasing food needs, it is important to develop simple models of wide application to determine the irrigation needs. The aim of this study was to calibrate and validate the AquaCrop model in maize crop of the variety ICA V156 in different locations of Colombia, such as Chinchina (Caldas), Palmira (Valle del Cauca) and Cerete (Cordoba), situated at altitudes of 20, 900, and 1,340 m a.s.l., respectively. As part of the model calibration, the biomass, harvest index, and grain yield were recorded. After the calibration, the Pearson correlation coefficient and the respective analysis of variance were calculated for each variable. The biomass, harvest index and grain yield were different in each study site, with the highest grain obtained in Cerete, followed by Chinchina and, finally, Palmira. The modeling in each of the locations showed similarity between the field data and the simulated data in each of the sites. In the calibration, Palmira had the highest grain yield (4.9 t ha-1), followed by Chinchina (4.83 t ha-1) and Cerete (4.15 t ha-1). The validation in each location allowed for the determination of the grain yield, harvest index, biomass and the amount of water needed for crop growth, which averaged 3.45 kg of biomass per m3 of evapotranspired water and was reflected in an average yield of 1.26 kg of grain per m3 of evapotranspired water., Debido al cambio climático y el aumento de las necesidades de alimentos, es importante desarrollar modelos simples de amplia aplicación para determinar las necesidades de riego. El objetivo del estudio fue calibrar y validar el modelo AquaCrop en el cultivo de maíz de la variedad ICA V156 en las condiciones de tres localidades de Colombia: Chinchiná (Caldas), Palmira (Valle del Cauca) y Cereté (Córdoba), ubicadas a las altitudes de 20, 900 y 1.340 msnm, respectivamente. Como parte de la calibración del modelo se registró la biomasa, el índice de cosecha y el rendimiento. Después del calibrado, se realizó el cálculo de coeficiente de correlación de Pearson y los respectivos análisis de varianza para cada una de las variables. La biomasa, el índice de cosecha y el rendimiento del grano fueron diferentes en cada sitio de estudio, siendo la localidad de Cereté (Córdoba) la de mejor rendimiento de grano, seguida de Chinchiná y por último Palmira. La modelación en cada una de las localidades mostró similitud entre la información de campo y la simulación en cada uno de los sitios evaluados. En la calibración, Palmira mostró el mayor rendimiento de grano (4,9 t ha-1), seguido por Chinchiná (4,83 t ha-1) y por último Cereté (4,15 t ha-1). La validación en cada una de las localidades permitió determinar el rendimiento, el índice de cosecha, la biomasa y la cantidad de agua necesaria para el desarrollo del cultivo, la que fue en promedio de 3,45 kg de biomasa por m3 de agua evapotranspirada, la que se reflejó en un rendimiento medio de 1,26 kg de grano por m3 de agua evapotranspirada.

Due to climate changes and increasing food needs, it is important to develop simple models of wide application to determine the irrigation needs. The aim of this study was to calibrate and validate the AquaCrop model in maize crop of the variety ICA V156 in different locations of Colombia, such as Chinchina (Caldas), Palmira (Valle del Cauca) and Cerete (Cordoba), situated at altitudes of 20, 900, and 1,340 m a.s.l., respectively. As part of the model calibration, the biomass, harvest index, and grain yield were recorded. After the calibration, the Pearson correlation coefficient and the respective analysis of variance were calculated for each variable. The biomass, harvest index and grain yield were different in each study site, with the highest grain obtained in Cerete, followed by Chinchina and, finally, Palmira. The modeling in each of the locations showed similarity between the field data and the simulated data in each of the sites. In the calibration, Palmira had the highest grain yield (4.9 t ha-1), followed by Chinchina (4.83 t ha-1) and Cerete (4.15 t ha-1). The validation in each location allowed for the determination of the grain yield, harvest index, biomass and the amount of water needed for crop growth, which averaged 3.45 kg of biomass per m3 of evapotranspired water and was reflected in an average yield of 1.26 kg of grain per m3 of evapotranspired water., Debido al cambio climático y el aumento de las necesidades de alimentos, es importante desarrollar modelos simples de amplia aplicación para determinar las necesidades de riego. El objetivo del estudio fue calibrar y validar el modelo AquaCrop en el cultivo de maíz de la variedad ICA V156 en las condiciones de tres localidades de Colombia: Chinchiná (Caldas), Palmira (Valle del Cauca) y Cereté (Córdoba), ubicadas a las altitudes de 20, 900 y 1.340 msnm, respectivamente. Como parte de la calibración del modelo se registró la biomasa, el índice de cosecha y el rendimiento. Después del calibrado, se realizó el cálculo de coeficiente de correlación de Pearson y los respectivos análisis de varianza para cada una de las variables. La biomasa, el índice de cosecha y el rendimiento del grano fueron diferentes en cada sitio de estudio, siendo la localidad de Cereté (Córdoba) la de mejor rendimiento de grano, seguida de Chinchiná y por último Palmira. La modelación en cada una de las localidades mostró similitud entre la información de campo y la simulación en cada uno de los sitios evaluados. En la calibración, Palmira mostró el mayor rendimiento de grano (4,9 t ha-1), seguido por Chinchiná (4,83 t ha-1) y por último Cereté (4,15 t ha-1). La validación en cada una de las localidades permitió determinar el rendimiento, el índice de cosecha, la biomasa y la cantidad de agua necesaria para el desarrollo del cultivo, la que fue en promedio de 3,45 kg de biomasa por m3 de agua evapotranspirada, la que se reflejó en un rendimiento medio de 1,26 kg de grano por m3 de agua evapotranspirada.

At present, there is limited understanding of how biochar application to soil could be beneficial to crop growth in temperate regions and which biochar types are most suitable. Biochar’s (two feedstocks: willow, pine; three pyrolysis temperatures: 450 °C, 550 °C, 650 °C) effect on nitrogen (N) availability, N use efficiency and crop yield was studied in northwestern European soils using a combined approach of process-based and agronomic experiments. Biochar labile carbon (C) fractions were determined and a phytotoxicity test, sorption experiment, N incubation experiment and two pot trials were conducted. Generally, biochar caused decreased soil NO3−availability and N use efficiency, and reduced biomass yields compared to a control soil. Soil NO3−concentrations were more reduced in the willow compared to the pine biochar treatments and the reduction increased with increasing pyrolysis temperatures, which was also reflected in the biomass yields. Woody biochar types can cause short-term reductions in biomass production due to reduced N availability. This effect is biochar feedstock and pyrolysis temperature dependent. Reduced mineral N availability was not caused by labile biochar C nor electrostatic NH4+/NO3− sorption. Hence, the addition of fresh biochar might in some cases require increased fertilizer N application to avoid short-term crop growth retardation.

Recent spikes in global food prices have emphasized how monitoring agriculture production at a national, regional and global scale is at the core of modern economic, geostrategic and humanitarian concerns. While crop growth models can be used to estimate potential yield based on the agro-meteorological growing conditions, their application at regional or continental scales for operational monitoring is hampered by uncertainties related to agricultural practices, nutrient availability, soil moisture content, pest management and landscape heterogeneity. Earth observation by satellite remote sensing has the potential to greatly reduce these uncertainties by providing synoptic information on crop status throughout the growing season and over large geographic extents. Despite remarkable advances in each field, there is still a major methodological gap between operational agricultural monitoring, crop growth modelling and remote sensing. This thesis contributes towards bridging this gap by establishing a framework to retrieve spatially and temporally consistent crop specific information from satellite imagery which can be coupled with crop growth models at regional scale. The spatial resolution requirements of the satellite imagery which are necessary for agricultural monitoring are first defined quantitatively based on the observed landscape. Green Area Index (GAI), a measure of the photosynthetic surface of the canopy, is then shown to be retrievable for a specific crop (wheat) all along its growing season from surface reflectance measurements by satellite using radiative transfer modelling. The method was then upscaled from field to regional level (using different instruments providing imagery with 20 m and 250 m pixels respectively) by controlling the adequacy between the observation footprint and the target fields. The extension over wider geographic areas (>10,000 km²) in highly fragmented agricultural landscapes for 6 growing seasons shows a high temporal and inter, (AGRO 3) -- UCL, 2011

This thesis aims to present the essential background on how to perform climate change impact assessments, and to present the results from a climate impact assessment on water balance and nitrate leaching for an arable Swedish soil. The soil is a sandy soil in southwestern Sweden, grown with spring cereals. This study is meant to be a benchmark example, and cannot be seen as a regional or national assessment for Sweden, rather as an approach to present and analyze the most important parts of these kinds of assessments. A dynamical simulation model (COUP, Jansson and Karlberg, 2004) was used for this study. The model was parameterized and calibrated against data from an experimental site, located in Mellby in Hallands county, south western Sweden. Measurements were carried out between 1st of April 1988 and 1st of April 1991. The data set consists of daily standard weather data and discharge, data on soil water content, soil nitrogen and nitrogen contents in drainage water from to experimental fields grown with spring cereals. The model was calibrated against the 4-year data set based on a GLUE-procedure in which a number of “acceptable parameter sets” were identified. One of these parameter sets were randomly chosen for the climate impact model runs performed in this study. The driving data for the model are 30-year climate data, including data for precipitation, temperature, solar radiation, relative humidity and wind speed, which enables long-term simulations of water and nitrogen flows. Three different simulations were performed, one for present climate as a reference scenario with climate data from 1971-2000, and two different emission scenarios representing year 2071-2100. The driving data were constructed by the delta-change method, which is a common way of interfacing regional climate model output with impact models. Results show that, for both scenarios, that nitrate leaching will increase with 41 % and 66 % respectively. This is mainly due to increased winter, Syftet med den här studien är att presentera bakgrunden till hur klimatförändringarnas potentiella effekter på mark-växt-systemet kan uppskattas, samt resultat från en modellstudie av klimatförändringens effekter på vattenbalans och nitratutlakning från en svensk jordbruksmark odlad med vårkorn.. Denna studie syftar till att vara ett exempel, och det är inte inom studiens ramar att fungera som ett regionalt eller nationellt underlag för hur nitratutlakningen in Sverige påverkas av ett föränderligt klimat. En dynamisk simuleringsmodell (COUP, Jansson och Karlberg, 2004), har använts i studien. Modellen är parameteriserad och kalibrerad mot data från ett fyra-årigt försök vid mätstationen i Mellby, Hallands län, sydvästra Sverige. Ett antal acceptabla parameter-set identifierades baserat på GLUE-metoden och ett av dessa valdes slumpmässigt ut för denna studie. Drivdata till modellen är 30-åriga klimatdata, innehållande daglig information om nederbörd, temperatur, sol instrålning, relativ fuktighet och vindhastighet. Dessa data möjliggör långtids simuleringar av vatten och kväveflöden i marken med daglig utdata. Tre scenarier användes för att studera klimatförändringens effekter, ett referens scenario som motsvarar dagens klimat mellan 1971-2000, samt två olika klimatscenarier som motsvarar åren 2071-2100. Drivdata-seten konstruerades med hjälp av den så kallade ”delta-change” - metoden, vilket är en metod för att transformera utdata från regionala klimatmodeller (RCM) till drivdata för platsspecifika modeller. Resultaten visar ökat läckage av nitratkväve för båda klimatscenarierna (41 % och 66 % från års medelvärde). Detta berodde huvudsakligen på ökad nederbörd samt ökat temperatur under vinterhalvåret, då marken är obevuxen. Netto mineraliseringen ökade med 22 % och 32 % respektive, och dräneringen genom markprofilen med 20 % och 33 % för respektive scenario. Tidigare skördetidpunkter bidrog också till ökat kväve-läckage på grund av att perioden av obevuxen mark för

Expansion of human activities has major impact on the environment, generating changes that must be countered, such as climate change and dispersion of pollutants from industry and agriculture, through strategies that enable the conservation of soil and water reserves. The implementation of strategies with systems approach, covering mathematical simulation models, enables better decision making and a better understanding of the complexity and interaction of the different processes that affect the fate of nutrients, pollutants and chemicals in the environment - soil – on cultures and dynamic water. The WAVE system is presented in this article as a mathematical tool that describes the transport and transformations of matter and energy in the soil, crops and unsaturated soil, however it is not support the processes of water groundwater, drains and rivers., La expansión de las actividades humanas tiene gran impacto en el medio ambiente, generando cambios que deben ser contrarrestados, como el cambio climático y la dispersión de contaminantes de la industria y la agricultura; a través de estrategias que permitan la conservación del suelo y de las reservas de agua. La implementación de estrategias con enfoque de sistemas, que abarque modelos de simulación matemáticos, permite una mejor toma de decisiones y una mejor comprensión de la complejidad y la interacción de los diferentes procesos que afectan el destino de los nutrientes, contaminantes y sustancias químicas en el medio ambiente - suelo- en los cultivos y en las zonas de movimiento de aguas. El sistema WAVE se presenta en el presente artículo como una herramienta matemática que describe el transporte y transformaciones de la materia y la energía en el suelo, los cultivos y el suelo no saturado, sin embargo no es compatible con los procesos de las aguas subterráneas, drenajes y ríos.

Expansion of human activities has major impact on the environment, generating changes that must be countered, such as climate change and dispersion of pollutants from industry and agriculture, through strategies that enable the conservation of soil and water reserves. The implementation of strategies with systems approach, covering mathematical simulation models, enables better decision making and a better understanding of the complexity and interaction of the different processes that affect the fate of nutrients, pollutants and chemicals in the environment - soil – on cultures and dynamic water. The WAVE system is presented in this article as a mathematical tool that describes the transport and transformations of matter and energy in the soil, crops and unsaturated soil, however it is not support the processes of water groundwater, drains and rivers., La expansión de las actividades humanas tiene gran impacto en el medio ambiente, generando cambios que deben ser contrarrestados, como el cambio climático y la dispersión de contaminantes de la industria y la agricultura; a través de estrategias que permitan la conservación del suelo y de las reservas de agua. La implementación de estrategias con enfoque de sistemas, que abarque modelos de simulación matemáticos, permite una mejor toma de decisiones y una mejor comprensión de la complejidad y la interacción de los diferentes procesos que afectan el destino de los nutrientes, contaminantes y sustancias químicas en el medio ambiente - suelo- en los cultivos y en las zonas de movimiento de aguas. El sistema WAVE se presenta en el presente artículo como una herramienta matemática que describe el transporte y transformaciones de la materia y la energía en el suelo, los cultivos y el suelo no saturado, sin embargo no es compatible con los procesos de las aguas subterráneas, drenajes y ríos.

The use of gypsiferous mine water for irrigation of agricultural crops is a promising technology, which could alleviate a shortage of irrigation water and address the problem of disposal of mine effluent. A field trial was established at Kleinkopje Colliery in Witbank (Mpumalanga Province, South Africa) during the 1997-1998 season. Sugar beans and wheat were irrigated with three center pivots, on both virgin and rehabilitated land. The objectives were to determine crop response to irrigation with two types of mine water, to determine the impact of irrigation with inferior quality water on virgin and rehabilitated soil, and to collect atmospheric, crop and soil data for detailed validation of the soil water balance (SWB) computer model. Crop yields were generally satisfactory. Yield of sugar beans on rehabilitated land was low compared with virgin land, probably due to the late planting date, hail damage and soil compaction. SWB simulations were compared with field measurements of weather, crop growth, water and salt balance parameters. Both field measurements and model simulations indicated an increase in soil salinity, with limited drainage and salt leaching. Long-term simulations of the water and salt balance were carried out with SWB to predict the long-term sustainability of irrigating with gypsiferous water.

The use of gypsiferous mine water for irrigation of agricultural crops is a promising technology, which could alleviate a shortage of irrigation water and address the problem of disposal of mine effluent. A field trial was established at Kleinkopje Colliery in Witbank (Mpumalanga Province, South Africa) during the 1997-1998 season. Sugar beans and wheat were irrigated with three center pivots, on both virgin and rehabilitated land. The objectives were to determine crop response to irrigation with two types of mine water, to determine the impact of irrigation with inferior quality water on virgin and rehabilitated soil, and to collect atmospheric, crop and soil data for detailed validation of the soil water balance (SWB) computer model. Crop yields were generally satisfactory. Yield of sugar beans on rehabilitated land was low compared with virgin land, probably due to the late planting date, hail damage and soil compaction. SWB simulations were compared with field measurements of weather, crop growth, water and salt balance parameters. Both field measurements and model simulations indicated an increase in soil salinity, with limited drainage and salt leaching. Long-term simulations of the water and salt balance were carried out with SWB to predict the long-term sustainability of irrigating with gypsiferous water.

The effects of water stress on plant water relations, growth, water use and sucrose accumulation were investigated with the aid rainshelters. In the first experiment various aspects of the water status of cane growing in large pots were measured. The pots were weighed to determine water use. In the second experiment similar measurements were made on cane grown in the field. Crop growth was measured non-destructively and water use was determined with a neutron probe. The threshold leaf water potentials for various attributes were determined as follows: 1) at -0.2 MPa, plant extension rate fell below potential, 2) at -0.3 MPa, stomatal resistance started to increase, 3) at -0.4 to -0.9 MPa plant extension ceased, 4) at -0.8 MPa, leaves started to roll, 5) at -1.0 to -1.7 MPa, green leaf area was reduced, 6) at -1.2 to -1.7 MPa, stomatal resistance rose rapidly, 7) at -1.4 to -2.3 MPa, stomata finally closed, 8) at -2.0 MPa, young leaves were fully rolled and 9) at -2.8 MPa, the apical meristem was permanently damaged. Osmotic adjustments during stress were reversed when plants recovered and there was no evidence of osmotic hardening. Stomata became more, rather than less sensitive to stress after a stress period in the field. The drought resistance of N12 was evidently due to its relatively low stress threshold for stomatal closure. This behaviour of stomata distinguished the species as one that avoids rather than endures drought. A crop water stress index (CWSI) based on infra-red thermometry correlated reasonably well with plant extension rate, leaf water potential and canopy resistance. Crop growth potential and water use efficiency appeared to vary considerably through the year. Cane yield increased by more than 1',0t had -1 during the hottest months,Water stres sappeared to have no permanent effect on cane growth rate provided stalk death did not result from stress. Water stress promoted ripening when plant extension was reduced and before stomata finally closed.

Opportunity exists for Australian growers to develop a commercial cannabis/hemp industry to meet globaldemand for seed, fibre and pharmaceutical products. Development of a commercial scale hemp industryrequires improved knowledge of hemp crop water relations to maximise yield, understand irrigationrequirements in new production regions, and for scheduling of harvest. Currently little is known of the hempplant-water relations. This study sought to evaluate the growth, development and physiology of industrialhemp under varying irrigation treatments. A preliminary greenhouse experiment was conducted to monitorresponse of industrial hemp cultivar Ferimon 12 to different irrigation treatments (2, 4, 6, 8 and 10 dayintervals). We found significantly taller plants for 2 day compared with the 8 and 10 day irrigation intervals.Significantly higher above ground dry biomass was observed for plants irrigated with 6, 8 and 10 dayintervals compared to the 2 and 4 days interval at 42 DAS. Significantly higher PSII photochemical capacity(Fv/Fm) and leaf chlorophyll content (SPAD value) was observed for plants irrigated with 6 and 10 dayintervals compared with the 2 day intervals. There for 6 day irrigation interval is probably the best frequencyof irrigation. Results from the preliminary experiment will be used to inform the design of future researchwhich will be used to develop irrigation recommendations and refine the hemp crop simulation model tofurther support farmer decision making regarding water management.