Using midday stem water potential for scheduling deficit irrigation in mid–late maturing peach trees under Mediterranean conditions

Irrigation techniques that reduce water applications are increasingly applied in areas with scarce water resources. In this study, the effect of two regulated deficit irrigation (RDI) strategies on peach [Prunus persica (L.) Batsch cv. “Catherine”] performance was studied over three growing seasons. The experimental site was located in Murcia (SE Spain), a Mediterranean region. Two RDI strategies (restricting water applications at stage II of fruit development and postharvest) based on stem water potential (Ψ_s) thresholds (?1.5 and ?1.8 MPa during fruit growth and ?1.5 and ?2.0 MPa during postharvest) were compared to a fully irrigated control. Soil water content (θ_v), Ψ_s, gas exchange parameters, vegetative growth, crop load, yield and fruit quality were determined. RDI treatments showed significantly lower values of θ_v and Ψ_s than control trees when irrigation water was restricted, causing reductions in stomatal conductance and photosynthesis rates. Vegetative growth was reduced by RDI, as lower shoot lengths and pruning weights were observed under those treatments when compared to control. However, fruit size and yield were unaffected, and fruit quality was slightly improved by RDI. Water savings from 43 to 65 % were achieved depending on the year and the RDI strategy, and no negative carryover effect was detected during the study period. In conclusion, RDI strategies using Ψ_s thresholds for scheduling irrigation in mid–late maturing peach trees under Mediterranean conditions are viable options to save water without compromising yield and even improving fruit quality.     

Measured and estimated water use and crop coefficients of grapevines trained to overhead trellis systems in California’s San Joaquin Valley

The use of overhead trellis systems for the production of dry-on-vine (DOV) raisins and table grapes in California is expanding. Studies were conducted from 2006 to 2009 using Thompson Seedless grapevines grown in a weighing lysimeter trained to an overhead arbor trellis and farmed as DOV raisins for the first two years and for use as table grapes thereafter. Maximum canopy coverage for the two lysimeter vines across years was in excess of 80 %. Seasonal (15 March–31 October) evapotranspiration for the lysimeter vines (ET_Lys) was 952 mm in 2007 (farmed as DOV raisins) and 943 and 952 mm (when farmed as table grapes). The maximum crop coefficient (K _cLys) across all 4 years ranged from 1.3 to 1.4. These maximum values were similar to those estimated using the relationship where K _c is a function of the amount of shaded area measured beneath the canopy at solar noon (K _c = 0.017 × percent shaded area). Covering the lysimeter’s soil surface with plastic (and then removing it) numerous times during the 2009 growing season (1 June–14 September) reduced ET_Lys from an average of 6.4 to 5.6 mm day^?1 and the K _c from 1.07 to 0.93. A seasonal basal K _c (K _cb) was calculated for grapevines using an overhead trellis system with a 13 % reduction in the K _cLys across the growing season.     

Crop response of drought-tolerant and conventional maize hybrids in a semiarid environment

In the High Plains, corn (Zea mays L.) is an important commodity for livestock feed. However, limited water resources and drought conditions continue to hinder corn production. Drought-tolerant (DT) corn hybrids could help maintain high yields under water-limited conditions, though consistent response of such hybrids is unverified. In this two-year study, the effects of three irrigation treatments were investigated for a DT and conventional maize hybrid, Pioneer AQUAMax P0876HR and Pioneer 33Y75, respectively. In 2013, the drier of the 2 years, irrigation amounts and crop water use (ET_c) were greater for the conventional hybrid, but grain water use efficiency (WUE) and harvest index were significantly greater for the DT hybrid. In 2014, grain yields and WUE were not significantly different between hybrids. However, irrigation amounts, ET_c and biomass yields were greater for the conventional hybrid. Results from both years indicate that the DT hybrid required less water to maximize grain yield as compared to the conventional hybrid. Producing relatively high yields with reduced amounts of water may provide a means for producers to continue corn production in a semiarid environment with declining water supplies.     

Simulation of growth and production in sheep-model 1: A computer program to estimate energy and nitrogen utilisation,body composition and empty liveweight change,day by day for sheep of any age

A computer program based on empirical relationships is described. It predicts daily energy and nitrogen utilisation repetitively for sheep of any age, before, during and after weaning; provision is also made for pregnancy, lactation and cold stress. Input information includes: intake, protein content and digestibility of the diet; age, empty body weight, fat content and feeding activity of the sheep; ambient temperature and wind speed; times of shearing and mating.Metabolisable energy from milk and/or dry feed is estimated and energy requirements for maintenance, including the cost of feeding activities and homeostasis in the cold, are deducted to obtain energy balance. The amount of amino acid nitrogen absorbed from the small intestine is estimated, and nitrogen balance in body tissues and wool is calculated from this, allowing for body weight and net energy intake. Potential wool growth is calculated from nitrogen and energy intakes, and potential conceptus growth or milk production is estimated primarily from stage of pregnancy or lactation. The use of nitrogen and energy for these products is assessed and balances of energy and nitrogen in body tissues are then obtained by difference. If achievement of the potential rates of production in pregnant or lactating animals would cause excessive loss of energy or nitrogen from body tissues, production of wool and conceptus or milk is reduced sufficiently to avoid this problem. Gain or loss of body fat and protein, and hence change of empty live weight, are finally derived and the animal parameters are incremented before proceeding to calculation for the next day.Evidence is presented that the model is stable in predicting lifetime performance, and that predictions of growth curves, body composition and various nutritional parameters are reasonably accurate in a variety of circumstances.     

Modeling soil water dynamics in a drip-irrigated intercropping field under plastic mulch

Intercropping, drip irrigation, and the use of plastic mulch are important management practices, which can, when utilized simultaneously, increase crop production and save irrigation water. Investigating soil water dynamics in the root zone of the intercropping field under such conditions is essential in order to understand the combined effects of these practices and to promote their wider use. However, not much work has been done to investigate soil water dynamics in the root zone of drip-irrigated, strip intercropping fields under plastic mulch. Three field experiments with different irrigation treatments (high T1, moderate T2, and low T3) were conducted to evaluate soil water contents (SWC) at different locations, for different irrigation treatments, and with respect to dripper lines and plants (corn and tomatoes). Experimental data were then used to calibrate the HYDRUS (2D/3D) model. Comparison between experimental data and model simulations showed that HYDRUS (2D/3D) described different irrigation events and SWC in the root zone well, with average relative errors of 10.8, 9.5, and 11.6 % for irrigation treatments T1, T2, and T3, respectively, and with corresponding root mean square errors of 0.043, 0.035, and 0.040 cm³ cm^?3, respectively. The results showed that the SWC in the shallow root zone (0–40 cm) was lower under non-mulched locations than under mulched locations, irrespective of the irrigation treatment, while no significant differences in the SWC were observed in the deeper root zone (40–100 cm). The SWC in the shallow root zone was significantly higher for the high irrigation treatment (T1) than for the low irrigation treatment, while, again, no differences were observed in the deeper root zone. Simulations of two-dimensional SWC distributions revealed that the low irrigation treatment (T3) produced serious severe water stress (with SWCs near the wilting point) in the 30–40 cm part of the root zone, and that using separate drip emitter lines for each crop is well suited for producing the optimal soil water distribution pattern in the root zone of the intercropping field. The results of this study can be very useful in designing an optimal irrigation plan for intercropped fields.     

Sensitivity analysis of optimal operation of irrigation supply systems with water quality considerations

A model for optimal operation of water supply/irrigation systems of various water quality sources, with treatment plants, multiple water quality conservative factors, and dilution junctions is presented. The objective function includes water cost at the sources, water conveyance costs which account for the hydraulics of the network indirectly, water treatment cost, and yield reduction costs of irrigated crops due to irrigation with poor quality water. The model can be used for systems with supply by canals as well as pipes, which serve both drinking water demands of urban/rural consumers and field irrigation requirements. The general nonlinear optimization problem has been simplified by decomposing it to a problem with linear constraints and nonlinear objective function. This problem is solved using the projected gradient method. The method is demonstrated for a regional water supply system in southern Israel that contains 39 pipes, 37 nodes, 11 sources, 10 agricultural consumers, and 4 domestic consumers. The optimal operation solution is described by discharge and salinity values for all pipes of the network. Sensitivity of the optimal solution to changes in the parameters is examined. The solution was found to be sensitive to the upper limit on drinking water quality, with total cost being reduced by 5% as the upper limit increases from 260 to 600 mg Cl l^–1. The effect of income from unit crop yield is more pronounced. An increase of income by a factor of 20 results in an increase of the total cost by a factor of 3, thus encouraging more use of fresh water as long as the marginal cost of water supply is smaller than the marginal decrease in yield loss. The effect of conveyance cost becomes more pronounced as its cost increases. An increase by a factor of 100 results in an increase of the total cost by about 14%. The network studied has a long pipe that connects two distinct parts of the network and permits the supply of fresh water from one part to the other. Increasing the maximum permitted discharge in this pipe from 0 to 200 m³ h^–1 reduces the total cost by 11%. Increasing the maximum discharge at one of the sources from 90 to 300 m³ h^–1 reduces the total cost by about 8%.     

“WaterMan”: an on-farm water management game with heuristic capabilities

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game.     

The Validation of Pesticide Leaching Models

The validation of pesticide leaching models presents particular problems where the number of model predictions is far in excess of the observed data. Normally, however, there are more frequent field observations for other parameters (notably the site hydrology) than for pesticide concentrations in either water or soil. A five-stage validation procedure which takes advantage of the most frequently available observations and which tests each of the components of the model in a cumulative way, is thus advocated: Stage 1: Parameterisation of the model using only independently measured parameters. Stage 2: Hydrological validation: the validation of the predictions of water movement and water content of the soil. Stage 3: Solute movement validation: where field data are available for solutes other than pesticide, the model should first be validated for them, especially if they are more abundant than the pesticide observations. Conserved solutes such as chloride or bromide are preferred, although nitrate may be used for short periods. Stage 4: Pesticide fate in the soil: models should use parameters of pesticide fate derived from independent studies. Stage 5: Pesticide leaching: only in the last stage are the relatively small number of pesticide observations compared with the model predictions with respect to patterns and orders of magnitude of occurrence. With this scheme, the results of each stage are carried forward to the next, and confidence in the model is built with each stage. This is illustrated using the CRACK-P model and hydrological, nitrate and pesticide data from the Brimstone Farm Experiment Oxfordshire, UK.