Weeds have patchy distributions within fields. This suggests site-specific weed management could be valuable and, in fact, herbicide use had been reduced 40 to 60% in trials of this management strategy; however, there have been few cost-benefit analyses of site-specific weed management. Our goal was to quantify the cost of identifying and counting weed seeds and seedlings to create seed bank and seedling maps for site-specific weed management. We sampled 1225 or more sites in eight commercial corn fields. Soil was collected just after planting and seeds were extracted by elutriation. Seedlings were sampled in 152 cm of crop row at the time for a postemergence decision. A model for describing the time required to count and identify weed seedlings was a log-linear form with time as a function of the number of seedlings and the number of species and, for seeds, a log-linear form with time as a function of the number of seeds and percentage of sand in the soil.

Effectiveness of rotary hoeing with cultivation and comparison of an in-row cultivator with a standard row-crop cultivator were determined in dry edible bean. The effectiveness of in-row cultivation conducted at various timings and frequencies was examined. The in-row cultivator was more effective in reducing weed populations than the standard cultivator, although at least two mechanical weeding operations were needed to reduce weed populations to levels of the herbicide check (EPTC [S-ethyl dipropyl carbamothioate] plus ethalfluralin). When the in-row cultivation was delayed until the second trifoliolate stage or later, weed populations were greater than those in the herbicide check. In situations with high weed populations, rotary hoeing prior to cultivation was required to reduce weed populations to levels similar to the herbicide check. An in-row cultivator has potential to improve mechanical weed control options in a crop such as dry edible bean. The types of adjustments made in combination with soil textures, soil moisture, and operator experience affect overall weed control. Thus, it is expected that the level of weed control will vary from year to year and even field to field for the same operator.

Fifty irrigated cornfields in five eastern Colorado counties were sampled for their seedbanks and annual weed seedlings and mature populations between 1988 and 1992. Fourteen annual broadleaf species and seven annual grass species were identified in the 50 seedbanks sampled after the fields were tilled in the fall. Redroot pigweed and a mixture of green and yellow foxtail were the weed species encountered most, occurring in 90 and 54% of the fields, respectively. The single-plant populations of broadleaf and grass species in June and September were similar to those observed in the seedbanks. The number of weed species as seeds in the seedbank, June seedlings, and September plants per field ranged from zero to five grass species and zero to eight broadleaf species.

GWM is a decision support system designed for evaluating soil-applied and post-emergence weed management options in row crops. It has a general structure to allow use with different crops. The system consists of a simulation model, databases, and a database management module. The simulation model has a set structure for linking processes of weed population dynamics during a single season, but allows flexibility in how each process is modeled. Databases store model prameters, information about management options, and field-specific simulation inputs. The database management module allows a user to specify entirely the simulation model or modify existing versions without programming. GWM has been parameterized to evaluate weed management as in two existing models (WEEDSIM and WEEDCAM) and for dry bean production. The structure of GWM and associated databases appears to capture essential aspects of weed biology influencing management decisions. GWN can be enhanced as knowledge of weed biology and ecology is refined.

Cooperative research was initiated by a multidisciplinary team of weed scientists and agricultural economists in 1975 that laid the foundation for integrated weed management research in Colorado. Colorado's integrated weed management research has four phases: weed seed bank decline, systems approach to weed management, bioeconomic modeling, and multiple weed management tactics. Each phase considered weed seed bank, weed control efficacy, weed control costs, crop yield, and gross margin. All four phases emphasize the need for a weed management system that minimizes seed production in situations where a high soil weed seed bank exists. However, once the weed seed bank is reduced, a weed management program with less than 100% weed control can be employed without increasing the seed bank. Intensive weed management systems are seldom justified when economics, weed control, and weed seed bank are considered. Integrated weed management approaches require integrating crop and weed biology with management tactics. Integrated weed management requires advanced managerial skills and often more time than traditional approaches.

A soil sampler, elutriator, and associated sample flushing device were designed and constructed for an intensive study of weed seedbanks. This equipment was used in 1993 to collect and process 4980 soil samples. The sampler was durable, core size was consistent, and sampling was efficient, Cores were approximately 200 cm(3) and two people could take 120 cores/h. The elutriator separated weed seeds from 36 of these cores at a time. Washing required 60 to 75 min depending on soil texture. Seeds as small as 0.3 mm in diam were recovered and almost 100% of the seeds were recovered from samples spiked with barnyardgrass, redroot pigweed, velvetleaf, and witchgrass. The flushing device was used to transfer sample contents from strainers of the elutriator to propyltex bags for drying and storing. Equipment like this, plus improved technology for identifying and counting seeds, is needed to make weed seedbank studies more feasible.

The question of when to control weeds traditionally has been approached with the calculation of critical periods (CP) based on crop yields. The concept of economic critical period (ECP) and early (EEPT) and late (LEFT) economic period thresholds are presented as a comprehensive approach to answer the same question based on economic losses and costs of control. ECP is defined as the period when the benefit of controlling weeds is greater than its cost. EEPT and LEFT are the limits of the ECP and can be used to determine when first and last weed control measures should be performed. Calculation of EEPT accounts for the economic losses due to weed competition that occur between planting and postemergence weed control. In this way it is possible to better evaluate the economic feasibility of using preplant or preemergence control tactics. The EEPT for DCPA application is analyzed in the context of onion production in Colorado. The EEPT for DCPA application was calculated from an empirical regression model that assessed the impact of weed load and time of weed removal on onion yields. The EEPT was affected by control efficacy, weed-free yield, DCPA cost, and onion price. DCPA application was economically advisable in only one of 20 fields analyzed because of the tow DCPA efficacy (60%).

An integrated approach to weed management in pinto bean is needed since available herbicides seldom adequately control all weed species present in a field. A two-year study was conducted to assess weed control efficacy and pinto bean tolerance to mechanical weeding from a rotary hoe or flex-tine harrow at crook, unifoliolate, and trifoliolate stages of bean development. Weed control was similar for both implements and all timings in 1993. In 1994, mechanical weeding at trifoliolate and both crook and trifoliolate stages controlled more weeds than at other growth stages, regardless of type of implement. Using the flex-tine harrow reduced pinto bean stand, but results based on growth stage were not consistent each year. Damage to pinto bean hypocotyls and stems was observed with the flex-tine harrow used at both crook and trifoliolate stages in 1994. Rotary hoeing did not reduce pinto bean stand or cause injury. Yield and seed weight did not differ among treatments in either year.

Information on the effects of multiple weed management tactics in corn is needed to develop integrated weed management systems. The effectiveness and compatibility of an in-row cultivator as compared to a standard interrow cultivator used with reduced rates of a soil-applied herbicide, rotary hoeing, and/or a bioeconomic model for POST herbicide selection was examined, Weed control with a single rotary hoeing at corn emergence controlled annual weeds similarly to two rotary hoeings. One-third recommended use rate of alachlor controlled weeds similarly to a two-thirds rate. Reduced rates of alachlor controlled more weeds than rotary hoeing over 2 yr. The in-row cultivator required early-season weed control (rotary hoeing or reduced alachlor rate) for optimum efficacy. The in-row cultivator provided better weed control than the standard cultivator while the cost of operating the two cultivators was similar. Thus, the in-row cultivator was more efficient than the standard cultivator. Furthermore, less intensive early-season weed control was required with the in-row cultivator for maximum weed control as compared to the standard cultivator. Rotary hoeing plus the in-row cultivator provided similar weed control to other weed management tactics that required both soil-applied and POST herbicides. Gross margin was influenced more by corn yield than cost of weed management tactics.

The impact of weed density and weed distribution on irrigated corn yield was investigated in Colorado. Weed densities examined were 0,33,50, or 100% of the indigenous weed population. A series of weed distribution treatments were achieved by varying the length of the weed-free and weedy zones within the corn row while maintaining a constant weed population of 33 or 50% of the indigenous weed level. Grain yield was affected by weed density, but not by weed distribution. Each additional weed reduced corn yield 8.5 and 2.3 kg ha−1in 1991 and 1992, respectively. When corn yields were estimated with a computer weed/corn management model, weed densities 5 to 8 wk after planting provided a better yield reduction estimate than weed densities immediately before harvest.

A 3-yr field study was conducted to compare an in-row cultivator versus a standard row-crop cultivator to decisions made with WEEDCAM, a weed/corn management computer decision aid, for controlling annual weeds within the row in irrigated corn. In the absence of herbicides, weeds were always controlled better with the in-row cultivator than with the standard row-crop cultivator. However, grain yield and gross margin were affected only in 1991 when weeds emerged simultaneously with corn, and rain delayed the first cultivation 10 d. The in-row cultivator plots not only averaged 34% more grain ha-1than the standard row-crop cultivator plots, but gross margin was $143 ha-1more. Weed densities each year were about 95% less in plots managed in accordance with the computer model WEEDCAM simulations than in the non-herbicide treated post-planting tillage plots. Grain yields and gross margins were not affected by weed seedbank density, pre-cultivation tillage, or type of cultivator when weed management decisions were based on WEEDCAM simulation ranking. In the absence of herbicides, weeds can be controlled successfully in corn with an in-row cultivator, but success will depend on such factors as weed seedbank density, cultivation timeliness, and relative time of weed and corn emergence.

Rice is the principal source of dietary energy and protein of tropical Asians. Acceptability of milled rice is determined by physical appearance and starch properties, particularly apparent amylose content (AC, linear fraction of starch). This chapter demonstrates the changing role of the chemist or biochemist involved in food quality evaluation and improvement of rice grain. Traditionally, breeders used parents with excellent grain quality, and screening was mainly based on physical properties. With the use of wide crosses for increased productivity and resistance/tolerance to biotic and abiotic stresses and the involvement of parents with diverse grain quality, the breeding program in the 1960s had to rely on physicochemical properties to screen for quality: apparent amylose content, alkali spreading value (gelatinization temperature of starch), and, recently, gel consistency. As the breeding program for quality intensifies, many lines with similar starch properties need to be evaluated and differentiated by texture (hardness) measurements of cooked rice.

A fixed (conventional) weed management strategy in corn was compared to three other strategies (two mixed and one flexible) in terms of weed control, grain yield, gross margin (gross income minus herbicide treatment costs), and herbicide use under furrow irrigation for four consecutive years. The fixed strategy prespecified preplanting, preemergence, postemergence, and layby herbicides. The flexible strategy herbicide treatments were specified by a computer bioeconomic model. Model decisions were based on weed seed in soil before planting, weed densities after corn emergence, herbicide costs, expected corn grain yield and selling price, and other parameters. The two mixed strategies were a combination of fixed and flexible strategies and designated either specified soil-applied herbicides (mixed/soil), or no soil-applied herbicide (mixed/no soil); postemergence treatments were determined by the model. Average corn grain yield was 10 280 kg ha–1and gross income was 920 $ ha–1and neither differed among strategies. Total weed density and gross margin were significantly higher for the mixed/no soil and flexible strategies compared to the mixed/soil and fixed strategies. Total weed density averaged 28 720, 28 100, 10 910, and 680 plants ha–1for the mixed/no soil, flexible, mixed/soil, and fixed strategies, respectively. Annual gross margins for the four strategies averaged 885, 875, 845, and 810 $ ha–1, respectively. Herbicide use over the 4-yr period for these four strategies averaged 3.8, 5.3, 20.5, and 26.9 kg ha–1, respectively, and each value differed from the other. Thus, weeds can be managed in corn, gross margins increased, and herbicide use decreased by employing a bioeconomic weed-corn model to make weed management decisions.

Bioeconomic sugarbeet weed management models for preplant, postemergence, and layby herbicides, and late-season handweeding decisions are presented. The personal computer/spreadsheet models are based on number of weed seed in soil, field survey of weed populations, growth stages of weeds and sugarbeets, expected yield loss from weeds, herbicide weed control, weed control cost, and sugarbeet price. The models incorporate two producer risk levels. Several weed scenarios were used to verify the models for reasonable recommendations.

The impact of three till-plant and two weed management systems on weed seed reserves of soil, yearly weed problems, and corn production was assessed under center-pivot irrigation for 3 consecutive years. Annual weeds were controlled in disced, bedded, and strip rotary till-plant systems with a moderate or intensive level of herbicides. Weed seed of seven annual weed species were identified, with common lambsquarters and stinkgrass, comprising 45 and 41%, respectively, of the initial 305 million seed/ha in the upper 25 cm of the soil profile. After the third cropping year, overall decline in total seed number in soil was 45% when averaged over till-plant and weed management systems. Grain yields did not differ between weed management systems, but the disced till-plant system produced 16% less grain than the bedded and strip rotary till-plant systems over 2 yr.

The impact of four weed management systems on weed seed reserves in soil, yearly weed problem, and production of barley, corn, pinto bean, and sugarbeet was assessed where these crops were grown in rotation for 4 consecutive years in four cropping sequences. Weeds were controlled in each crop with only conventional tillage or conventional tillage plus minimum, moderate (system 1), and intensive (system 2) levels of herbicides. Seed of annual weeds from 11 genera were identified, with barnyardgrass and redroot pigweed comprising 66 and 19%, respectively, of the initial 90 million weed seed/ha present in the upper 25 cm of the soil profile. After the fourth cropping year, overall decline in total number of weed seed in soil was 53% when averaged over four cropping sequences and four weed management systems. Over the 4-yr period, about 10 times more weeds escaped control in system 1 than in system 2; and within a crop, the fewest number of weeds escaped control annually in barley. System 2 had the highest herbicide use in each cropping sequence, the fewest weeds at harvest, and the smallest adjusted gross return over the 4-yr period in three of four cropping sequences.

An economic analysis of four weed management systems employed on four crop sequences in a barley-corn-pinto bean-sugarbeet rotation in eastern Colorado was computed. Weeds were controlled in each crop with only conventional tillage or conventional tillage plus minimum levels of herbicides (systems 3 and 4), moderate levels of herbicides (system 1), or intensive levels of herbicides (system 2). Adjusted gross returns were higher for systems 3 and 4 where herbicide use was less/year and decreased over 4 yr than for systems 1 and 2 where herbicide use was higher/year and constant. When the four crop sequences were aggregated using yield and sucrose indices, the least herbicide-intensive weed management system had $440/ha/4 yr higher indexed adjusted gross return than the most herbicide-intensive weed management system. An income risk analysis showed that the herbicide-intensive weed management system was not risk efficient and that producers would select one of the other three less herbicide-intensive weed management systems depending upon their risk preferences.

Grass and broadleaf weed densities and seed numbers, weed control practices, and grain yields were included in a bioeconomic model that evaluates alternative weed management strategies for continuous corn (Zea maysL.). Weed seed numbers in soil and herbicide carry-over provided intertemporal links. Four weed management strategies – two fixed, one mixed, and one flexible – were evaluated with annualized net returns as the performance indicator. The flexible strategy (weed control based on observed conditions) had the largest annualized net return for high and low initial weed seed numbers. The fixed weed management strategy (weed control predetermined) of an annual application of only a preemergence herbicide ranked second in terms of annualized net returns for high weed seed numbers. The mixed weed management strategy of alternative year applications of preemergence herbicide and “as needed” applications of postemergence herbicide ranked second for low initial weed seed numbers. The fixed weed management strategy of alternate year application of preemergence herbicide only generated the lowest annualized net return, regardless of initial weed seed numbers.