Agronomy Journal

The time required for dispersing soils for the hydrometer method of making particle size analyses was reduced from 25 minutes to only 2 minutes. The procedure consists of soaking the soils in a 5% Calgon solution for 15 to 20 hours and then dispersing them with a soil mixer running at a speed of about 16,000 r.p.m., for 2 minutes.

This article introduces the FAO crop model AquaCrop. It simulates attainable yields of major herbaceous crops as a function of water consumption under rainfed, supplemental, deficit, and full irrigation conditions. The growth engine of AquaCrop is water‐driven, in that transpiration is calculated first and translated into biomass using a conservative, crop‐specific parameter: the biomass water productivity, normalized for atmospheric evaporative demand and air CO₂ concentration. The normalization is to make AquaCrop applicable to diverse locations and seasons. Simulations are performed on thermal time, but can be on calendar time, in daily time‐steps. The model uses canopy ground cover instead of leaf area index (LAI) as the basis to calculate transpiration and to separate out soil evaporation from transpiration. Crop yield is calculated as the product of biomass and harvest index (HI). At the start of yield formation period, HI increases linearly with time after a lag phase, until near physiological maturity. Other than for the yield, there is no biomass partitioning into the various organs. Crop responses to water deficits are simulated with four modifiers that are functions of fractional available soil water modulated by evaporative demand, based on the differential sensitivity to water stress of four key plant processes: canopy expansion, stomatal control of transpiration, canopy senescence, and HI. The HI can be modified negatively or positively, depending on stress level, timing, and canopy duration. AquaCrop uses a relatively small number of parameters (explicit and mostly intuitive) and attempts to balance simplicity, accuracy, and robustness. The model is aimed mainly at practitioner‐type end‐users such as those working for extension services, consulting engineers, governmental agencies, nongovernmental organizations, and various kinds of farmers associations. It is also designed to fit the need of economists and policy specialists who use simple models for planning and scenario analysis.

Leaf area index (LAI) and leaf angle distribution are widely used indices of vegetative canopy structure that are difficult to measure directly. This study was conducted to test a commercially available instrument for rapidly determining LAI and foliage inclination information from “fisheye” measurements of light interception. The instrument's estimates of LAI are compared with direct measurements in soybean [Glycine max (L.) Merr.], winter wheat (Triticum aestivum L.), and prairie grass. The dominant grass species in the plots were indian grass [Sorghastrum nutans (L.) Nash], switchgrass (Panicum virgatum L.), and big bluestem (Andropogon gerardii Vitman). The instrument's LAI resolution was better than 3%, and its LAI error was generally less than 15%. Variations in sky brightness patterns caused variations in LAI estimates in winter wheat of less than 10%, and the presence of direct solar radiation increased LAI errors to more than 30% in canopies of differing species and LAI. In the presence of gaps in the canopy, the sensor's azimuthal view should be reduced. A simple test indicates if a canopy's gaps are significant.

Balancing the amount of N needed for optimum plant growth while minimizing the NO₃that is transported to ground and surface waters remains a major challenge for everyone attempting to understand and improve agricultural nutrient use efficiency. Our objectives for this review are to examine how changes in agricultural management practices during the past century have affected N in midwestern soils and to identify the types of research and management practices needed to reduce the potential for nonpoint NO₃leakage into water resources. Inherent soil characteristics and management practices contributing to nonpoint NO₃loss from midwestern soils, the impact of NO₃loading on surface water quality, improved N management strategies, and research needs are discussed. Artificial drainage systems can have a significant impact on water quality because they behave like shallow, direct conduits to surface waters. Nonpoint loss of NO₃from fields to water resources, however, is not caused by any single factor. Rather, it is caused by a combination of factors, including tillage, drainage, crop selection, soil organic matter levels, hydrology, and temperature and precipitation patterns. Strategies for reducing NO₃loss through drainage include improved timing of N application at appropriate rates, using soil tests and plant monitoring, diversifying crop rotations, using cover crops, reducing tillage, optimizing N application techniques, and using nitrification inhibitors. Nitrate can also be removed from water by establishing wetlands or biofilters. Research that is focused on understanding methods to minimize NO₃contamination of water resources should also be used to educate the public about the complexity of the problem and the need for multiple management strategies to solve the problem across agricultural landscapes.

The AquaCrop model was developed to replace the former FAO I&D Paper 33 procedures for the estimation of crop productivity in relation to water supply and agronomic management in a framework based on current plant physiological and soil water budgeting concepts. This paper presents the software of AquaCrop for which the concepts and underlying principles are described in the companion paper (Steduto et al., 2009). Input consists of weather data, crop characteristics, and soil and management characteristics that define the environment in which the crop will develop. Algorithms and calculation procedures modeling the infiltration of water, the drainage out of the root zone, the canopy and root zone development, the evaporation and transpiration rate, the biomass production, and the yield formation are presented. The mechanisms of crop response to cope with water shortage are described by only a few parameters, making the underlying processes more transparent to the user. AquaCrop is a menu‐driven program with a well‐developed user interface. With the help of graphs which are updated each time step (1 d) during the simulation run, the user can track changes in soil water content, and the corresponding changes in crop development, soil evaporation and transpiration rate, biomass production, and yield development. One can halt the simulation at each time step, to study the effect of changes in water related inputs, making the model particularly suitable for developing deficit irrigation strategies and scenario analysis.

Irrigated agriculture is a vital component of total agriculture and supplies many of the fruits, vegetables, and cereal foods consumed by humans; the grains fed to animals that are used as human food; and the feed to sustain animals for work in many parts of the world. Irrigation worldwide was practiced on about 263 Mha in 1996, and about 49% of the world's irrigation occurred in India, China, and the USA. The objectives of this paper are to (i) review irrigation worldwide in its ability to meet our growing needs for food production, (ii) review irrigation trends in the USA, (iii) discuss various concepts that define water use efficiency (WUE) in irrigated agriculture from both engineering and agronomic viewpoints, and (iv) discuss the impacts of enhanced WUE on water conservation. Scarcely one‐third of our rainfall, surface water, or ground water is used to produce plants that are useful to mankind. Without appropriate management, irrigated agriculture can be detrimental to the environment and endanger sustainability. Irrigated agriculture is facing growing competition for low‐cost, high‐quality water. In irrigated agriculture, WUE is broader in scope than most agronomic applications and must be considered on a watershed, basin, irrigation district, or catchment scale. The main pathways for enhancing WUE in irrigated agriculture are to increase the output per unit of water (engineering and agronomic management aspects), reduce losses of water to unusable sinks, reduce water degradation (environmental aspects), and reallocate water to higher priority uses (societal aspects).

Cover crops (CCs) can provide multiple soil, agricultural production, and environmental benefits. However, a better understanding of such potential ecosystem services is needed. We summarized the current state of knowledge of CC effects on soil C stocks, soil erosion, physical properties, soil water, nutrients, microbial properties, weed control, crop yields, expanded uses, and economics and highlighted research needs. Our review indicates that CCs are multifunctional. Cover crops increase soil organic C stocks (0.1–1 Mg ha⁻¹ yr⁻¹) with the magnitude depending on biomass amount, years in CCs, and initial soil C level. Runoff loss can decrease by up to 80% and sediment loss from 40 to 96% with CCs. Wind erosion potential also decreases with CCs, but studies are few. Cover crops alleviate soil compaction, improve soil structural and hydraulic properties, moderate soil temperature, improve microbial properties, recycle nutrients, and suppress weeds. Cover crops increase or have no effect on crop yields but reduce yields in water‐limited regions by reducing available water for the subsequent crops. The few available studies indicate that grazing and haying of CCs do not adversely affect soil and crop production, which suggests that CC biomass removal for livestock or biofuel production can be another benefit from CCs. Overall, CCs provide numerous ecosystem services (i.e., soil, crop–livestock systems, and environment), although the magnitude of benefits is highly site specific. More research data are needed on the (i) multi‐functionality of CCs for different climates and management scenarios and (ii) short‐ and long‐term economic return from CCs.

Many forms of the Penman combination equation have been proffered for estimating daily evapotranspiration (ET) by the agricultural reference crops grass and alfalfa (Medicago sativa L.). This study was conducted to evaluate popular forms of the Penman equation, and to develop and evaluate general relationships for estimating daily average values of canopy and aerodynamic resistance parameters required by the Penman‐Monteith equation. For simplicity and ease of use, resistance relationships were expressed as linear and logarithmic functions of mean plant height. The Penman‐Monteith and other forms of the Penman equation were compared at 11 international lysimeter sites, with the Penman‐Monteith method and a Penman equation with variable wind function developed at Kimberly, ID providing the best estimates of reference ET across the sites. Ratios of computed alfalfa to grass reference ET during peak months at various locations averaged 1.32, and ranged from 1.12 to 1.43. Values of computed ratios were related to local wind and humidity conditions. The development of relationships for canopy and aerodynamic resistances as functions of reference crop height allowed use of the Penman‐Monteith equation in an operational mode, and improved transferability of this resistance form of the Penman equation to a wide variety of climates.

Crop models have many current and potential uses for answering questions in research, crop management, and policy. Models can assist in synthesis of research understanding about the interactions of genetics, physiology, and the environment, integration across disciplines, and organization of data. They can assist in preseason and in‐season management decisions on cultural practices, fertilization, irrigation, and pesticide use. Crop models can assist policy makers by predicting soil erosion, leaching of agrichemicals, effects of climatic change, and large‐area yield forecasts. Cautions and limitations in model uses are suggested, because appropriate use for a particular purpose depends on whether the model complexity is appropriate to the question being asked and whether the model has been tested in diverse environments. There is a need for both complex and simple models. In some cases, simple models are not appropriate because they are not programmed to address a particular phenomenon. In other cases, complex models are not appropriate because they may require inputs that are not practical to obtain in a field situation. Modelers need to be forthright in model description and promotion. For example, what does a given model respond to? What are the limitations of the model? What factors does the model not address? What are the limitations of inputs to run the models? Examples are given of model use to evaluate genetic improvement in photosynthesis and seed‐filling duration, yield response to planting date and row spacing, and effects of change in seasonal temperature. We believe that use of crop growth models will play an increasingly important role in research understanding, crop management, and policy questions.

For thousands of years, agriculture and tillage were considered synonymous. It was simply not thought possible to grow crops without first tilling the soil before planting and for weed control. The advent of modern herbicides permitted no‐tillage (NT) to be developed and practiced on actual working family farms. No‐tillage is generally defined as planting crops in unprepared soil with at least 30% mulch cover. Adoption of NT after its successful demonstration in the 1950s was slow. However, with better planters, herbicides, and accumulated experience, NT began to be widely adopted in the 1980s in the United States and then in Australia, South America, and Canada. Today, approximately 23% of the total cropland in the United States is planted using NT. No‐tillage has revolutionized agricultural systems because it allows individual producers to manage greater amounts of land with reduced energy, labor, and machinery inputs. At the same time, NT is a very effective erosion control measure and improves water and fertilizer use efficiency so that many crops yield better under NT than under tilled systems. Tillage, like crops, can be rotated but the benefits of NT are most likely to be realized with continuous application. We review some of the early work that led to the development of NT and how NT impacts the crop, soil, hydrology, and farm economics. While highly sustainable, there are still many challenges that remain for researchers to solve so the benefits of NT can be realized on expanded land area and for more crops, worldwide.