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Scarce freshwater resources in arid and semiarid regions means that recreational landscapes should use recycled or low-quality waters for irrigation, increasing the risk of salinity and infiltration problems. We map salinity distribution within turf fields using electromagnetic sensing, evaluate need for leaching and evaluate post leaching results for subsequent management decisions. Electromagnetic measurements were made with two EM38 instruments positioned vertically and horizontally in order to determine salinity distribution. Sensor readings were coupled to GPS data to create spatial salinity maps. Next, optimal calibration point coordinates were determined via Electrical Conductivity Sampling Assessment and Prediction (ESAP) software. Soil samples from 0–15 and 15–30 cm depths were used for each calibration point. Laboratory soil saturation percentage, moisture content, electrical conductivity (ECe) and pHe of saturation extracts were determined for calibration to convert resistivity measurements to ECe. Next, ECe maps were created using ESAP software. Leaching for reclamation was performed by means of sprinkling. Treated municipal wastewater was utilized both for irrigation and for reclamation leaching. Low water content and high spatial variability of soil texture adversely affected the accuracy of the readings. Pre and post leaching surveys indicate that in one fairway there was only a 43% and 58% decrease in soil salinity at 0–15 and 15–30 cm depths, respectively which is very low relative to expected results considering the amount of water applied. This relatively low reduction in salinity and the lack of runoff during irrigation combined with infiltration measurements suggests that aeration techniques for healthier grasses led to water bypassing small pores thus limiting leaching efficiency. In this instance practices to improve infiltration lead paradoxically to less salinity reclamation than expected.

Scarce freshwater resources in arid and semiarid regions means that recreational landscapes should use recycled or low quality waters for irrigation, increasing the risk of salinity and infiltration problems. We map salinity distribution within turf fields using electromagnetic sensing, evaluate need for leaching and evaluate post leaching results for subsequent management decisions. Electromagnetic measurements were made with two EM38 instruments positioned vertically and horizontally in order to determine salinity distribution. Sensor readings were coupled to GPS data to create spatial salinity maps. Next, optimal calibration point coordinates were determined via ESAP software. Soil samples were taken from 0-60 cm at 5 depths for each calibration point. Laboratory soil saturation percentage, moisture content, ECe and pHe of saturation extracts were determined for calibration to convert resistivity measurements to ECe. Next, ECe maps were created using ESAP software. Leaching for reclamation was performed by means of sprinkling. Treated municipal wastewater was utilized both for irrigation and for reclamation leaching. Low water content and high spatial variability of soil texture adversely affected the accuracy of the readings. Pre and post leaching surveys indicate that there was only a 30% decrease in salinity, very low relative to expected results considering the amount of water applied. This relatively low reduction in salinity and the lack of runoff during irrigation combined with infiltration measurements suggests that aeration techniques for healthier grasses led to water bypassing small pores thus limiting leaching efficiency. In this instance practices to improve infiltration lead paradoxically to less salinity reclamation than expected.

Directed soil sampling based on geospatial measurements of apparent soil electrical conductivity (EC a ) is a potential means of characterizing the spatial variability of any soil property that influences EC a including soil salinity, water content, texture, bulk density, organic matter, and cation exchange capacity. Multi-field EC a survey data often exhibit abrupt changes in magnitude across field boundaries that complicate the calibration of EC a to soil salinity (i.e., EC e , electrical conductivity of the saturation extract) over large spatial extents. The primary objective of this study is to evaluate three regression techniques for calibrating EC a to EC e over spatial scales ranging from a few thousand to a hundred thousand hectares, where EC a was measured using electromagnetic induction equipment. The regression techniques include analysis of covariance (ANOCOVA), field specific regression (FSR), and common coefficient regression (CCR). An evaluation was made by comparing jack-knifed mean square prediction errors (MSPE) of EC e for two case studies: 2400 ha of the Broadview Water District in California's San Joaquin Valley and roughly 100,000 ha of the west side of Kittson County in the Red River Valley of Minnesota. The ANOCOVA model outperformed the FSR and CCR regression models on a prediction accuracy basis with the smallest MSPE estimates for depth predictions of soil salinity. The implication of this evaluation is that once ANOCOVA models for each depth are established for a representative set of fields within a regional-scale study area, then the slope coefficients can be used at all future fields, thereby significantly reducing the need for ground-truth soil samples at future fields, which substantially reduces labor and cost. Land resource managers, producers, agriculture consultants, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of regional-scale maps of soil salinity.

Soil salinity is a spatially complex and dynamic property of soil that influences crop yields when the threshold salinity level is exceeded. The mapping and monitoring of soil salinity is necessary for reclamation, crop selection, and site-specific irrigation management of salt-affected soils in the arid and semi-arid agricultural regions of the world. Because of its spatial and temporal heterogeneity, soil salinity is difficult to map and monitor at field scales. There are various methods for characterizing soil salinity variability, but none of these approaches has been as extensively investigated and is as reliable and cost effective as apparent soil electrical conductivity (ECa) directed soil sampling. Geospatial measurements of ECa are well-suited for characterizing soil salinity spatial distribution because they are reliable, quick, and easy to take with GPS-based mobilized ECa measurement equipment. However, ECa is influenced by a variety of soil properties, which makes the measurement of soil salinity at field scale problematic. It is the goal of this review and analysis paper to provide an overview of the field-scale characterization of soil salinity distribution using ECa-directed soil sampling. Guidelines, special considerations, protocols, and strengths and limitations are presented for characterizing spatial and temporal variation in soil salinity using ECa-directed soil sampling. Original data is presented showing the critical importance of conducting ECa surveys at or near field capacity (≥70% of field capacity). A case study of a 32.4-ha field in San Jacinto, California, is provided as an example to demonstrate the effectiveness of generating soil salinity maps. Land resource managers, farmers, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of field-scale maps of soil salinity.

Soil spatial variability has a profound influence on most agronomic and environmental processes at field and landscape scales, including site-specific management, vadose zone hydrology and transport, and soil quality. Mobile sensors are a practical means of mapping spatial variability because their measurements serve as a proxy for many soil properties, provided a sensor-soil calibration is conducted. A viable means of calibrating sensor measurements over soil properties is through linear regression modeling of sensor and target property data. In the present study, two sensor-directed, model-based, sampling scheme delineation methods were compared to validate recent applications of soil apparent electrical conductivity (EC)-directed spatial simulated annealing against the more established EC-directed response surface sampling design (RSSD) approach. A 6.8-ha study area near San Jacinto, CA, was surveyed for EC, and 30 soil sampling locations per sampling strategy were selected. Spatial simulated annealing and RSSD were compared for sensor calibration to a target soil property (i.e., salinity) and for evenness of spatial coverage of the study area, which is beneficial for mapping nontarget soil properties (i.e., those not correlated with EC). The results indicate that the linear modeling EC-salinity calibrations obtained from the two sampling schemes provided salinity maps characterized by similar errors. The maps of nontarget soil properties show similar errors across sampling strategies. The Spatial Simulated Annealing methodology is, therefore, validated, and its use in agronomic and environmental soil science applications is justified.

The ability to inventory and map soil salinity at regional scales remains a significant challenge to scientists concerned with the salinization of agricultural soils throughout the world. Previous attempts to use satellite or aerial imagery to assess soil salinity have found limited success in part because of the inability of methods to isolate the effects of soil salinity on vegetative growth from other factors. This study evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery in conjunction with directed soil sampling to assess and map soil salinity at a regional scale (i.e., 10-10(5) km(2)) in a parsimonious manner. Correlations with three soil salinity ground truth datasets differing in scale were made in Kittson County within the Red River Valley (RRV) of North Dakota and Minnesota, an area where soil salinity assessment is a top priority for the Natural Resource Conservation Service (NRCS). Multi-year MODIS imagery was used to mitigate the influence of temporally dynamic factors such as weather, pests, disease, and management influences. The average of the MODIS enhanced vegetation index (EVI) for a 7-yr period exhibited a strong relationship with soil salinity in all three datasets, and outperformed the normalized difference vegetation index (NDVI). One-third to one-half of the spatial variability in soil salinity could be captured by measuring average MODIS EVI and whether the land qualified for the Conservation Reserve Program (a USDA program that sets aside marginally productive land based on conservation principles). The approach has the practical simplicity to allow broad application in areas where limited resources are available for salinity assessment.

In an effort to elucidate the physiological processes involved in cowpea differential growth response of four major USA cowpea cultivars (CB5, CB27, 8517 and 7964) to increasing salinity, we investigated the effect of salinity on leaf gas exchange of net photosynthetic rate per unit leafmass(Pnm)andperunitleafarea(Pna),andstomatalconductance(gs)ofthefourcowpeacultivars.Theexperimentwassetupasastandard split-plot design in which cowpea plants were grown in greenhouse sand tanks irrigated with nutrient solutions. Seven salinities ranging from 2.6 to 20.5 dS m � 1 were constructed based on Colorado River water salt composition with NaCl, CaCl2 and MgSO4 as the salinization salts. Light-saturated Pnm, Pna and gs of fully expanded trifoliage were examined at the vegetative growth and flowering stages, and the data were analyzed using a split-plot analysis of variance (ANOVA) model. We found a highly significant (P � 0.0001) reduction of Pnm, Pna and gs due to salinity. The responses of Pnm, Pna and gs to salinity could be further described by a general model of log(y )= a1 + a2x + a3x 2 ,w herey represents either Pnm, Pna, or gs; a1, a2 and a3, empirical constants; x, salinity. We found that Pnm was more sensitive to salinity than Pna. Additionally, we found that increasing stomatal closure with increasing salinity might limit Pnm or Pna. While we did not find any significant difference (P > 0.05) of Pnm and Pna among the four cultivars, we did find a significant difference (P � 0.05) in gs. No significant

Over the last several years, there has been increasing interest in amending the soil using cover crops, especially in desert agriculture. One cover crop of interest in the desert Coachella Valley of California is cowpea [Vigna unguiculata (L.) Walp.]. Cowpea is particularly useful in that as an excellent cover crop, fixing abundant amounts of nitrogen which can reduce fertilizer costs. However, soil salinity problems are of increasing concern in the Coachella Valley of California where the Colorado River water is a major source of irrigation water. Unfortunately, little information is available on the response of cowpea growth to salt stress. Thus, we investigated the growth response of 12 major cowpea cultivars (`CB5', `CB27', `CB46', `IT89KD-288', `IT93K-503-1', `Iron Clay', `Speckled Purple Hall', `UCR 134', `UCR 671', `UCR 730', `8517', and `7964') to increasing salinity levels. The experiment was set up as a standard Split Plot design. Seven salinity levels ranging from 2.6 to 20.1 dS·m–1 were constructed, based on Colorado River water salt composition, to have NaCl, CaCl2 and MgSO4 as the salinization salts. The osmotic potential ranged from –0.075 to –0.82 MPa. Salt stress began 7 days after planting by adding the salts into irrigating nutrient solution and ended after 5 consecutive days. The plants were harvested during flowering period for biomass measurement (53 days after planting). Data analysis using SAS analysis of variance indicated that the salinity in the range between 2.6 and 20.1 dS·m–1 significantly reduced leaf area, leaf dry weight, stem dry weight and root dry weight (P ≤ 0.05). We applied the data to a salt-tolerance model, log(Y) = a1 + a2X + a3X2, where Y represents biomass, a1, a2 and a3 are empirical constants, and X represents salinity, and found that the model accounted for 99%, 97%, 96%, 99%, and 96% of salt effect for cowpea shoot, leaf area, leaf dry weight, stem dry weight and root dry weight, respectively. We also found significant differences (P ≤ 0.05) of each biomass parameter among the 12 cultivars and obtained different sets of the empirical constants to quantitatively describe the response of each biomass parameter to salinity for individual cowpea cultivars. Since a significant salt × cultivar interaction effect (P ≤ 0.05) was found on leaf area and leaf dry weight, we concluded that salt tolerance differences exist among the tested cultivars.

Soybean is an important crop worldwide. Soybean cultivars differ in their sensitivity to soil salinity and herbicide damage. In these experiments, we examined the impact of salinization an...

An assessment of field-scale variation and the characterization of correlated crop response are the first steps in evaluating the potential for variable-rate technologies and other techniques used in site-specific management (SSM). The responses of sugar beets to salinity and to residual and applied soil N were studied at sites in California's Imperial and San Joaquin Valleys to evaluate the potential of electromagnetic induction (EMI) techniques for SSM. Electromagnetic induction was used to create geo-referenced assessments of apparent soil electrical conductivity (EC"a) and correlated soil properties in salt-affected fields in the Imperial (IV) and San Joaquin (SJV) Valleys. Soils at the two sites were primarily fine, smectitic (calcareous) thermic, vertic Torifluvents and Fluvequents, respectively. Two crops were grown in the IV and one in the SJV. Root and gross sugar yields were evaluated at field scale using a yield monitor and in subplots centered on soil sampling locations chosen using ESAP-95 (v. 2.01) software that were harvested by hand. Average subplot root yields differed from field-scale averages derived from the yield monitor by less than 4% for all three crops. In the IV field, average salinity increased with depth, indicating leaching of salts. The natural logs of electrical conductivity of the saturation paste extract (EC"e) and saturation percentage (SP) were strongly correlated with measured EC"a (r=0.97 and r=0.86, respectively) and nitrate was moderately correlated (r=0.55). Root and sugar yields declined at the higher salinity levels from 18.0 to 8.0mgha^-^1. The SJV site was poorly drained and leaching was not apparent. EC"e was strongly correlated with EC"a (r=0.94), but SP was not (r=0.20). Gross sugar yields apparently were influenced by SP rather than by EC"e and varied from 2.9 to 14.1mgha^-^1. Where crop growth and yield are influenced by salinity, EMI is useful for estimating optimum fertilizer N application rates and for identifying areas of the field that will have unprofitable yields. Irrigation might be withheld from these areas and the water saved for other beneficial uses.

Sustaining irrigated agricultural production systems in semi-arid and arid regions requires consideration of with saline and sodic soil conditions. The spatial variability of these conditions makes soil reclamation an ideal practice in which to apply site-specific management (SSM). We discuss an application of SSM in which preliminary measurements of apparent soil electrical conductivity (EC"a), supplemented by EC"a-directed soil sampling, are used to construct a GIS map of salinity zones on which site-specific amendment application can be based. Our primary objective was to develop a field-implementable methodology for site-specific soil amendment application. The focus of the program was on cotton production, although the method should be applicable to other crops. A second objective was to establish experiments to test the effectiveness of this program. Evaluating the effectiveness of a sprinkler application for the first irrigation was incorporated as a part of this program in hopes of reducing variability due to poor germination. This study consisted of two commercial fields located in the San Joaquin Valley of California. Based on the consideration that EC"a is directly related to electrical conductivity from soil saturation paste extract (EC"e) for known saline-sodic conditions, we developed a four-step method for site-specific salinity management in commercial fields. The steps included the following: (1) generation of an EC"a map; (2) directed soil sampling for EC"e; (3) determination of the estimated amendment requirement as a function of location in the field; and (4) integration of the individual amendment requirements into a practical spatial pattern for amendment application. Cotton yield monitors were utilized to indicate spatial yield variation throughout the replicated plots instead of aggregated yield values. Because of the high levels of variability in these commercial fields and the time required for amendments to have a substantial effect, we can provide only short-term results of these experiments. In both of the experiments no significant differences existed between the irrigation and amendment treatments (p>0.05), but increased yield trends supported the benefit of sprinkler application of the first irrigation. A Scheffe test of the cotton yield monitor data indicated significant yield differences between in-plot treatment zones.

Greenhouse experiments were conducted to determine the effect of salinity, imazethapyr, and chlorimuron on weed growth. Five species, barnyardgrass, common cocklebur, ivyleaf morningglory, common purslane, and yellow nutsedge, were grown in potting soil and irrigated with nonsaline (EC ∼ 2 dS m−1) or sulfate-dominated saline (EC ∼ 7 dS m−1) nutrient solution. Plants were treated after emergence with imazethapyr (Pursuit formulation) at 70 g ae ha−1 or chlorimuron ethyl (Classic formulation) at 8.8 g ai ha−1. Results indicated that irrigation with saline water had no overall effect on the growth or survival of most tested weed species. Growth of yellow nutsedge (maximum height and stem diameter) was reduced for plants irrigated with saline water. Observed growth and survival trends in saline and nonsaline treatments were consistent with information on the herbicide label. Complete control of common purslane was not achieved by either chlorimuron or imazethapyr. Growth and survival of ivyleaf morni...

Crop yield inconsistently correlates with apparent soil electrical conductivity (EC a ) because of the influence of soil properties (e.g., salinity, water content, texture, etc.) that may or may not influence yield within a particular field and because of a temporal component of yield variability that is poorly captured by a state variable such as EC a . Nevertheless, in instances where yield correlates with EC., maps of EC, are useful for devising soil sampling schemes to identify soil properties influencing yield within a fleld. A west side San Joaquin Valley field (32A ha) was used to demonstrate how spatial distributions of EC a can guide a soil sample design to determine the soil properties influencing seed cotton (Gossypium hirsutum L.; 'MAXXA' variety) yield. Soil sample sites were selected with a statistical sample design utilizing spatial EC, measurements. Statistical results are presented from correlation and regression analyses between cotton yield and the properties of pH, B, NO 3 -N, Cl - , salinity, leaching fraction (LF), gravimetric water content, bulk density, percentage clay, and saturation percentage. Correlation coefficients of -0.01, 0.50, -0.03, 0.25, 0.53, -0.49, 0.42, -0.29, 0.36, and 0.38, respectively, were determined. A site-specific response model of cotton yield was developed based on ordinary least squares regression analysis and adjusted for spatial autocorrelation using maximum likelihood. The response model indicated that salinity, plant-available water, LF, and pH were the most significant soil properties influencing cotton yield at the study site. The correlations and response model provide valuable information for site-specific management.

The correlation structure between apparent soil electrical conductivity (EC a ) and various soil properties can often appear radically dissimilar in different field surveys. Ideally, some type of methodology for survey data validation should be developed that can predict the expected correlation structure between EC, survey data and various soil properties, given information about the soil properties themselves. In this paper, we review an existing model for EC a and hypothesize that this model can be used to accurately predict the expected correlation structure between EC, data and multiple soil properties of interest (such as soil salinity, saturation-paste percentage, and soil water content). Our objective is twofold: (i) to demonstrate how this model can be employed to produce the expected correlation structure and (ii) to extend this EC, model to handle survey data collected under low water content situations by dynamically adjusting the model's assumed water content function. This adjustment can be estimated using acquired EC, signal and soil sample data, and its statistical significance can be determined for each specific survey situation. We demonstrate both of these techniques using acquired electromagnetic induction signal data and measured soil properties of interest from 12 different field salinity surveys performed in California and Colorado and in Alberta, Canada. Results from these 12 surveys suggest that the ordinary model is able to accurately predict the expected correlation structure between conductivity and soil property when the water content is near field capacity and that the dynamically adjusted model is able to substantially improve the accuracy of the predicted correlation structure when the water content is significantly below field capacity.

Depth of standing water in rice paddy fields is an important agronomic parameter in the management of irrigation-related salinity problems. It was hypothesized that reductions in the yield of rice under salinity stress can be ameliorated by adjusting the water depth. This study was designed to determine the interactive effects of salinity and water depth on seedling establishment and grain yield in rice. Plants were grown in a greenhouse and irrigated with nutrient solutions amended with NaCl and CaCl2 (5:1 molar concentrations). Treatments were three salt levels with electrical conductivities at 0.9, 3.3 and 6.0 dS m−1 and six water depths at 4, 7, 10, 13, 16 and 20 cm. The effects of both salinity and water depth were significant on plant growth and yield. However, there was no interaction between the effects of salinity and water depth. Reductions in seedling establishment and grain yield with increases of salinity and water depth resulted from a simple combination of the two different stresses on plants. Highly significant negative correlations were identified between water depth and seedling establishment and also between water depth and grain yield when data were combined across salt levels. Generally, plants performed better with respect to seedling establishment and grain yield in shallow water (i.e. 10 cm). Under salt stress, the effect of water depth was significant for panicle number, but not significant for panicle weight. The loss of grain yield under salt stress with the increases of water depth was mainly due to reduction in fertile tiller number. We suggest that water depth be lowered during the initiation and growth of productive tillers. However, the practice by lowering water depth must be incorporated with appropriate field management such as the increase of irrigation frequency, precision leveling, and effective weed control methods.

Though more costly than petroleum-based fuels and a minor component of overall military fuel sources, biofuels are nonetheless strategically valuable to the military because of intentional reliance on multiple, reliable, secure fuel sources. Significant reduction in oilseed biofuel cost occurs when grown on marginally productive saline-sodic soils plentiful in California’s San Joaquin Valley (SJV). The objective is to evaluate the feasibility of oilseed production on marginal soils in the SJV to support a 115 ML yr−1 biofuel conversion facility. The feasibility evaluation involves: (1) development of an Ida Gold mustard oilseed yield model for marginal soils; (2) identification of marginally productive soils; (3) development of a spatial database of edaphic factors influencing oilseed yield and (4) performance of Monte Carlo simulations showing potential biofuel production on marginally productive SJV soils. The model indicates oilseed yield is related to boron, salinity, leaching fraction, and water content at field capacity. Monte Carlo simulations for the entire SJV fit a shifted gamma probability density function: Q = 68.986 + gamma (6.134,5.285), where Q is biofuel production in ML yr−1. The shifted gamma cumulative density function indicates a 0.15–0.17 probability of meeting the target biofuel-production level of 115 ML yr−1, making adequate biofuel production unlikely.

Differential sensitivity during growth stages is one of the major issues in the management of saline water for irrigation. This study was designed to analyze the effects of salinity on plant growth and yield components of rice by composing 20-day periods of salinization at different growth stages. Plants were grown in sand tanks in a greenhouse and irrigated with nutrient solutions. Treatments were three levels of salinity with electrical conductivities at 1.8, 3.2 and 4.6 dS m−1 and five timing treatments. Plants were salinized on the day of seeding, 1-leaf, 3-leaf, panicle initiation (PI), and booting stages, respectively, and stress was relieved after 20 days in each timing treatment. Salinity-induced reductions in shoot dry weights of plants harvested before PI were significant, but there were no significant differences among timing treatments. Reduction in shoot dry weight of plants harvested at seed maturity was significant only when plants were salinized for a 20-day duration before booting, but not after booting. Reduction in tiller number per plant was significant only when plants were salinized for a 20-day duration before PI. The reductions in spikelets per panicle and seed weight per panicle were most pronounced when plants were stressed between the 3-leaf and PI stages or between PI and booting stages and minor when stressed at the other stages. A 20-day period between 3-leaf and PI stages was most sensitive to salinity in terms of seed yield. These results indicate that the differential sensitivity at growth stages can be clearly shown when stages are well defined in the timing treatments and the stress is quantified at growth stages based on the same duration of salinization. The interaction between cultivar and timing treatment was not significant. Uniform management options can be developed for irrigation using saline water for the cultivars with similar genetic backgrounds.

ADDITIONAL INDEX WORDS. salinity, salt stress, water reuse, irrigation water, drainage water ABSTRACT. Saline agricultural drainage water may be used as a resource to grow high value horticultural crops and reduce the volume of drainage for eventual disposal. To explore reuse options the effects of salinity and timing of application were tested on selected leafy vegetables grown in 24 sand culture plots in Riverside, Calif. The leafy winter vegetables included 'Ruby Red Chard' Swiss chard ( Beta vulgaris L. var. flavescens (Lam.) Lam.), 'Space' spinach ( Spinacia oleracea L.), 'Vitamin Green' salad greens ( Brassica rapa L. (Narinosa Group)), 'Red Giant' mustard greens ( Brassica juncea L. (Czerniak)), pac choi (Brassica rapa L. (Chinensis Group)), 'Winterbor' kale ( Brassica oleracea L. (Acephala Group)), tatsoi (Brassica rapa L. (Narinosa Group)), 'Salad King' curly endive ( Cichorium endivia L.), and 'Red Preco No. 1' radicchio (Cichorium intybus L.). All vegetables were planted at the same time and irrigated initially with tap water and nutrients. At 3 and 7 weeks after seeding (application times), six salinity treatments were initiated by adding salts to the irrigation water to represent the chemical compositions of drainage waters found typically in the San Joaquin Valley, Calif. The six salinity treatments had electrical conductivities of 3 (control), 7, 11, 15, 19, or 23 dS·m -1 . A randomized complete block design was used with (6 salinities × 2 application times × 2 replications). Within each plot a 1.5-m row of each of the nine vegetables was grown as split plots. Salinity reduced fresh weight (FW) yields of all species. Salt stress applied at 3 weeks after seeding reduced FWs for seven of the nine vegetables compared to salination at 7 weeks. Analyses of salt tolerance curves, maximum yields, and the point of 50% yield reduction (C 50) were conducted. Greens produced the highest biomass at 874 g/plant, but was the most affected by application time. Swiss chard and radicchio were not significantly affected by timing of salinity application, and Swiss chard was the most salt tolerant overall. Greens, kale, pac choi, and to a lesser extent, tatsoi, have potential as winter-grown, leafy vegetables in drainage water reuse systems. markets. Potential crops include winter vegetables, flowers, herbs, medicinals, and other species that are tolerant to drainage water irrigation and would provide high economic return (Shan- non and Grieve, 1999, 2000). In this study, we used synthetic drainage water with ion composition similar to that found typically in the San Joaquin Valley to irrigate nine leafy winter vegetables. The purpose of the study was to determine potential yield and salt tolerance over a range of salinities and to determine if improved yields could be obtained if initial salination were delayed past the early plant establishment stage in which most plants are considered to be salt sensitive (Shannon et al., 1994).

The response of two speciality vegetable crops, New Zealand spinach ( Tetragonia tetragonioides Pall.) and red orach ( Atriplex hortensis L.), to salt application at three growth stages was investigated. Plants were grown with a base nutrient solution in outdoor sand cultures and salinized at 13 (early), 26 (mid), and 42 (late) d after planting (DAP). For the treatment salt concentrations, we used a salinity composition that would occur in a typical soil in the San Joaquin Valley of California using drainage waters for irrigation. Salinity treatments measuring electrical conductivities (EC i ) of 3, 7, 11, 15, 19 and 23 dS m −1 were achieved by adding MgSO 4 , Na 2 SO 4 , NaCl and CaCl 2 to the base nutrient solution. These salts were added to the base nutrient solution incrementally over a 5-d period to avoid osmotic shock to the seedlings. The base nutrient solution without added salts served as the non-saline control (3 dS m −1 ). Solution pH was uncontrolled and ranged from 7.7 to 8.0. Both species were salt sensitive at the early seedling stage and became more salt tolerant as time to salinization increased. For New Zealand spinach, the salinity levels that gave maximal yields (C max ) were 0, 0 and 3.1 dS m −1 and those resulting in a 50% reduction of biomass production (C 50 ) were 9.1, 11.1 and 17.4 dS m −1 for early, mid and late salinization dates, respectively. Maximal yield of red orach increased from 4.2 to 10.9 to 13.7 dS m −1 as the time of salinization increased from 13, to 26, to 42 DAP, respectively. The C 50 value for red orach was unaffected by time of salt imposition (25 dS m −1 ). Both species exhibited high Na + accumulation even at low salinity levels. Examination of K-Na selectivity data indicated that K + selectivity increased in both species with increasing salinity. However, increased K-Na selectivity did not explain the increased salt tolerance observed by later salinization. Higher Na-Ca selectivity was determined at 3 dS m −1 in New Zealand spinach plants treated with early- and mid-salinization plants relative to those exposed to late salinization. This corresponded with lower C max and C 50 values for those plants. Lower Ca uptake selectivity or lower Ca levels may have inhibited growth in young seedlings. This conclusion is supported by similar results with red orach. High Na-Ca selectivity found only in the early-salinization plants of red orach corresponded to the lower C max values measured for those plants.

Electromagnetic induction surveys are often used in practice to estimate field-scale soil salinity patterns, and to infer changing salinity conditions with time. We developed a statistical monitoring strategy that uses electromagnetic induction data and repetitive soil sampling to measure changing soil salinity conditions. This monitoring approach requires (i) the estimation of a conditional regression model that is capable of predicting soil salinity from electromagnetic (EM) survey data, and (ii) the acquisition of new soil samples at two or more previously established survey sites, so that formal tests can be made on the differences between the predicted and observed salinity levels. We examined two test statistics in detail: a test for detecting dynamic spatial variation in the new salinity pattern and a test for detecting a change in the field median salinity level with time. We applied this monitoring and testing strategy to two EM survey-soil salinity data sets collected at multiple points in time from the saline irrigation district of Flumen, Spain, Our results demonstrate that this monitoring approach was successfully able to quantify the temporal changes in the soil salinity patterns occurring within these two fields.

A unique technology-package for measuring the spatial distributions of salinity in irrigated soils and fields and for evaluating the appropriateness of some related irrigation-, drainage- and salinity control-management practices is described. This assessment technology is based on the use of: (1) geophysical-instrumental systems for intensively measuring bulk soil electrical conductivity and associated spatial coordinates; (2) statistical algorithms for site selection and salinity calibration; and (3) algorithms for data analysis and graphical display to facilitate interpretation. Results are presented to demonstrate some of the utility of the technology. Additionally, examples are given which show that much of the apparent chaos observed in the spatial pattern of soil salinity in irrigated fields is man-induced and related to such management practices as irrigation, drainage, and tillage.

Grain yield in wheat (Triticum aestivum L. emend. Thell.) is highly dependent upon the number of spike-hearing tillers produced by each plant. Soil salinity can greatly decrease their number and productivity. Knowing the contribution of specific tillers is essential for breeding salt-tolerant genotypes and for developing wheat growth simulation models. Our objective was to determine the effects of soil salinity on the contribution of individual cuhns to total grain and dry matter yields of two spring wheat cultivars, Anza and Yecora Rojo. Plants were grown in Pacbappa fine sandy loam soil (mixed, thermic, Mollic Haploxeralf) in outdoor lysimeters for 2 yr. Three salinity treatments were imposed by irrigating with waters containing equal weights of NaCl and CaClr (electrical conductivities z 1, 12, or 18 dS m-r). Despite substantial losses in the number of tillers at moderate levels of salt stress, grain yields of the main stem (MS) and tillers Tl and T2 were as great or greater than those on nonstressed plants of both cultivars. The contribution of the MS to yield on a land area basis increased from about 25 to 35% in nonsaline treatments to over 80% with increasing salinity. The contribution of primary tillers (E 5865% in nonsaline conditions) decreased substantially only at the highest salinity levels. Salinity stress significantly decreased the number of spikelets per spike but the number of kernels per spike either increased or was unaffected except at the highest level of stress. Increasing salinity decreased total straw yields primarily because of fewer tillers, but dry weights of the MSs and remaining tillers were also smaller. Results show that loss of spike-bearing tillers accounts for most of the yield reduction in salt-stressed wheat.

A geostatistical analysis of soil salinity in an agricultural area in the San Joaquin Valley included measurements of electrical conductivity of soil paste extract (EC3 and water content of soil samples supplemented by surface measurements of apparent electrical conductivity (EM”). Prediction of soil salinity at unsampled points by cokriging log@C3 and EMa is worthwhile because EM” measurements are quicker than soil sampling. This work studies how patterns of loa predicted by cokriging with EMa are influenced by variation in gravimetric water content (W). The data are mean EM” = 1.00 f 0.13 dS m-’ for 2378 locations, mean @(EC.) = 1.40 f 0.29 dS m-l, and mean gravimetric W = 0.260 f 0.003, both averaged for four samples from 0.3-m intervals to 1.2-m depth for 315 locations. The coefficient of determination (R*) for EMa vs. &(EC.) increased with depth from 0.05 to 0.54 whereas the R2 for EMa vs. W decreased from 0.48 to 0.28. A gray-scale EM” map contained nine out of 56 quarter-section boundaries coinciding with step variations in EM”. The t-statistics for differences in mean W were six of nine significant at 0.001 and nine of nine at 0.05, but mean log@C,) had only two of nine at 0.05, implying that W caused EMa steps. Water-affected EMa impaired prediction of EC. at depth by cokriging, because near-surface variations in Wmasked EC,. Two subareas were defined, one where management factors, such as irrigation, controlled EMH, causing steps, and one where near-surface W varied less, making cokriging predictions more reliable.

Wheat (Triticum aestivum L. emend. Thell.) grain yields are highly dependent upon the number of spike-bearing tillers produced per plant. Salinity, drought, and other environmental stresses can greatly affect the development and viability of tillers. We determined the effects of soil salinity on the occurrence and rate of tiller development and the incidence of tiller abortion in spring wheat cultivars, Anza and Yecora Rojo. Plants were grown in Pachappa fine sandy loam soil (mixed, thermic, Mollic Haploxeralf) in outdoor lysimeters. Three salinity treatments were imposed by irrigating with waters containing equal weights of NaCl and CaCl 2 (electrical conductivities of ≃ 1, 12, or 18 dS m −1 ). Salinity significantly decreased the number of primary and secondary tillers in both cultivars [...]

Salt tolerance of wheat (Triticum aestivum L.) is known to change during different stages of growth. The effects of salinity on growth and yield components of wheat at different stages of growth were determined in a 2-yr field plot study at Brawley, CA. Four salinity levels were imposed on a Holtville silty clay [clayey over loamy, montmorillonitic (calcareous), hyperthermic Typic Torrifluvent] by irrigating with waters salinized with NaCl and CaCl 2 (1:1 w/w). Electrical conductvities of the irrigation waters were 1.4, 10.0, 20.0, and 30.0 dS m −1 in 1989), and 1.4, 8.0, 16.0, and 24.0 dS m −1 in 1990. The three irrigation treatments were (i) salinity imposed throughout the growing season, (ii) szaline irrigation initiated after terminal spikelet differentiation (TSD), and (iii) saline irrigation discontinued at TSD [...]

Salt stress is known to affect adversely shoot apex development in cereals. This study was conducted to determine rate and duration of leaf and spikelet primordia initiation as related to bmal leaf and spikelet numbers in salt-stressed wheat (Triticum aestivum L.). Early shoot development of two hard red spring wheat cultivars, Yecora Rojo and Anza, was studied in both greenhouse sand cultures and outdoor field lysimeters. In each case, two saline treatments were compared with a nonsaline control treatment. The sand cultures were irrigated with complete nutrient solutions to which NaCl and CaCl 2 (2:1 molar ratio) were added to achieve electrical conductivities (κ iw ) of 1.7, 12.2, and 15.1 dS m -1

Grain development in wheat (Triticum aestivum L.) is a complex process tha tresponds to interactions among primary genotypic factors and the environment. This study was conducted to determine the effects of salinity stress on kernel occurence and kernel mass distributions within the main spike. Mexican semidwarf wheat cultivars Yecora Rojo and Anza were grown in sand tanks in the greenhouse with saline and nonsaline nutrient solutions. At harvest, each spikelet position and grain position was identified and the weight of every kernel was determined (...)

Grain yield potential of wheat (Triticum aestivum L.) main spikes is genetically determined and depends upon the number of spikelets per spike, the number of kernels per spikelet, and the weight of individual kernels. Environmental factors may interact with the genotype to influence the expression of these components. This study was initiated to determine the effects of salinity on main-spike yield components of two Mexican semidwarf, hard red spring wheat cultivars, Yecora Rojo and Anza (...)

A statistical modeling approach is presented that predicts spatial soil salinity patterns from aboveground electromagnetic induction (EM) readings. In this approach, EM readings are obtained from a field sampled on a uniform (centric systematic) grid. A small number of these sample sites are chosen for soil sampling, based on the observed EM field pattern. The salinity levels for these soil samples are determined and then the remaining nonsampled salinity values are predicted from the corresponding EM readings through a multiple linear regression equation. Experimental results suggest that this approach will work well in fields having low to moderate levels of soil textural variability. For example, 95% of the spatial variability in soil salinity within typical 16.2-ha (40-acre) cotton (Gossypium hirsutum L.) fields could be accounted for with only 36 soil samples, as opposed to the 200 to 300 soil samples typically required if no EM readings were available. This approach makes EM readings a more practical and cost-effective tool by substantially reducing the number of soil samples needed for accurate mapping of spatial salinity patterns at the field scale. A SOIL SALINITY ASSESSMENT is neCCSsary for agriculture management. Excessive soil salinity affects crop production and may cause crop loss and, eventually, land degradation. Cost-effective appraisal techniques designed to assess and monitor the salinity levels can help minimize such losses. Field-scale soil salinity conditions can be characterized using ECa measurements. Soil ECa is influenced by chemical and physical properties of the soil liquid and solid phases. Soil salinity, as represented by ECe, can be determined from field ECa measurements (Rhoades et al., 1989b). On farmland, practical measurements of ECa can be made with either in situ or remote devices. Three kinds of portable sensors are available: (i) four-electrode sensors, including either surface-array or insertion probes; (ii) EM induction sensors, and (iii) time domain reflectometric sensors (Rhoades and Oster, 1986; Rhoades and Miyamoto, 1990; Rhoades, 1990). The surface-array, four-electrode, or EM techniques all give depth-weighted ECa measurements. The weighting functions vary with the configuration of the electrodes or electromagnetic coils, frequency of electrical current used in the measurement, distribution of ECa within the various depths of the soil profile, and other factors. All of these factors must be compensated for when interpreting soil salinity with these devices. Two approaches have been used to determine U.S. Salinity Lab., USDA-ARS, 4500 Glenwood Dr., Riverside, CA 92501. Contribution from the U.S. Salinity Lab. Received 4 Dec. 1990. *Corresponding author. Published in Soil Sci. Soc. Am. J. 56:540-548 (1992). salinity by depth in the soil from EM measurements. Rhoades et al. (1989a) developed a salinity prediction model to estimate ECe using either EM or four-electrode measurements, provided that soil water and clay content were known. Empirical equations that predict soil ECe from EM measurements have also been developed for specific soil and water-content situations (Rhoades and Corwin, 1981; Corwin and Rhoades, 1982; Williams and Baker, 1982; Williams and Hoey, 1987; Slavich and Petterson, 1990; McKenzie et al., 1989). For some purposes, establishing a direct ECe = f(EM) prediction equation is advantageous, such as in a single field under uniform management where water content, bulk density, and other soil properties are reasonably homogeneous. Under such conditions, it is possible to establish an accurate ECe-EM relationship using a limited number of soil samples. Geostatistical procedures have traditionally been used for salinity mapping when soil samples are available (Webster, 1989). However, such procedures generally require intensive sampling to obtain accurate variogram estimates. We have developed a more practical, cost-effective predictive technique—field-specific models that use limited ECe ground-truth data and extensive EM measurements for spatial salinity predicion and mapping.

The sodium adsorption ratio (SAR) and salinity criteria for water suitability for irrigation have been developed for conditions where irrigation water is the only water source. It is not clear that these criteria are applicable to environments where there is a combination of rain and irrigation during the growing season. The interaction of rainfall with irrigation water is expected to result in increased sodicity hazard because of the low electrical conductivity of rain. In this study we examined the effects of irrigation waters of SAR 2, 4, 6, 8, and 10 mmol(1/2) L(-1/2) and electrical conductivities of 1 and 2 dS m(-1) on the infiltration rate of two soils with alternating cycles of rain (simulated with a rainfall sprinkler) and irrigation water, separated by drying cycles. The infiltration rate of surface samples from two soils, Kobase silty clay (fine, smectitic, frigid, Torrertic Haplustept) and Glendive very fine sandy loam (coarse-loamy, mixed superactive, calcareous, frigid Aridic Ustifluvent) were evaluated under alfalfa (Medicago sativa) cropped conditions for over 140 d and under full canopy cover. Reductions in infiltration were observed for both soils for SAR above 2, and the reductions became more severe with increasing SAR. Saturated hydraulic conductivity measurements taken from undisturbed cores at the end of the experiment were highly variable, suggesting that in situ infiltration measurements may be preferred when evaluating SAR effects.

Greater urban demand for finite water resources, increased frequency of drought resulting from erratic weather, and increased pressure to reduce drainage water volumes have intensified the need to reuse drainage water. A study was initiated in 1999 on a 32.4-ha saline-sodic field (Lethent clay loam series; fine, montmorillonitic, thermic, Typic Natrargid) located on the west side of California's San Joaquin Valley (WSJV) with the objective of evaluating the sustainability of drainage water reuse with respect to impact on soil quality. An evaluation after 5 yr of irrigation with drainage water is presented. Geo-referenced measurements of apparent soil electrical conductivity (EC(a)) were used to direct soil sampling at 40 sites to characterize the spatial variability of soil properties (i.e., salinity, Se, Na, B, and Mo) crucial to the soil's intended use of growing Bermuda grass (Cynodon dactylon (l.) Pers.) for livestock consumption. Soil samples were taken at 0.3-m increments to a depth of 1.2 m at each site in August 1999, April 2002, and November 2004. Drainage water varying in salinity (0.8-16.2 dS m(-1)), SAR (5.4-52.4), Mo (80-400 microg L(-1)), and Se (

A vegetative treatment area (VTA) offers alternative solutions to traditional feedlot runoff holding ponds, but the distribution of nutrients is not easily defined. Methods for monitoring salt accumulations in soils have been demonstrated at the United States Salinity Laboratory, Riverside, CA. This study was conducted to determine if methods developed to inventory saline soils can be used to inventory a VTA designed to control feedlot runoff. A soil conductivity map was generated at a VTA site using electromagnetic induction equipment (Dualem-1S) and global positioning satellite. The ESAP software package, developed by the United States Salinity Laboratory at Riverside, CA, was used to determine a representative set of (n = 20) soil sampling locations for estimating the chloride distribution in the VTA (Cl - : selected as an indicator ion to track feedlot runoff). An additional set of (n = 20) stratified random sampling (SRS) locations were selected for comparison. The ESAP-generated, prediction-based sampling plan exhibited better design optimality criteria than the SRS plan. Statistical validation tests confirmed that the regression model estimated from the ESAP-generated sample data was capable of producing accurate and unbiased predictions of the natural log (Cl - ) levels at the independently chosen SRS sites. The combination of geo-referenced soil conductivity, directed soil sample data, and regression modeling provides a cost-effective tool to observe and manage liquid flow patterns in a VTA.

Key components of precision agriculture are (i) identifying the site-specific factors that influence within-field crop yield variation and (ii) spatially characterizing those factors. Geo-referenced measurements of apparent soil electrical conductivity (ECa) provide a potential means of characterizing the spatial variability of edaphic properties that influence crop yield. It is the objective (i) to utilize an intensive ECa survey to direct soil sampling, (ii) to identify soil properties that influence cotton yield, and (iii) to use this spatial information to make site-specific management recommendations to increase cotton yield. A 32.4-ha field in California’s San Joaquin Valley was used as a study site. Cotton yield monitoring data were collected in August 1999 followed by an intensive ECa survey of 4000 measurements using electrical resistivity. Sixty soil sample sites were selected based upon a responsesurface sampling design utilizing the spatial ECa measurements. Scatter plots were obtained and correlation and regression analyses were performed to assess the relationship between cotton yield and the properties of pH, boron (B), nitrate-nitrogen (NO3-N), chloride (Cl-), salinity (i.e., electrical conductivity of the saturation extract; ECe), leaching fraction (LF), water content (θg), bulk density (ρb), % clay, and saturation percentage (SP). Correlation coefficients of -0.01, 0.50, -0.03, 0.25, 0.53, -0.49, 0.42, -0.29, 0.36, and 0.38, respectively, were found. The correlation coefficient between yield and ECa was 0.51. A site-specific response model of cotton yield based on ordinary least squares (OLS) and adjusted for spatial autocorrelation using restricted maximum likelihood was developed. The response model indicated that leaching fraction, salinity, water content, and pH were the most significant soil properties influencing cotton yield: cotton yield (Mg ha-1) = 19.28 0.22 ECe – 0.02 ECe 2 – 4.42 LF2 – 1.99 pH 6.93 θg. The spatial information and response model provide sufficient information to make site-specific management recommendations to increase cotton yield.