Using the Heckman framework, we develop profiles of households who purchase Greek yogurt and non-Greek yogurt and estimate own-price, cross-price, and income elasticities of demand. Attention is centered on the impacts of age, race, education, and ethnicity of the household head, household income, household size, region, the presence of children, and prices of Greek yogurt and non-Greek yogurt. This analysis rests on data acquired from Nielsen pertaining to 164,484 households over calendar years 2018–2020. Own-price elasticities are estimated to be −1.36 for Greek yogurt and −0.70 for non-Greek yogurt. Additionally, these yogurt products are not only substitutes but also necessities.

Smallflower umbrella sedge is a prolific C3 weed commonly found in rice fields in 47 countries. The increasing infestation of herbicide-resistant smallflower umbrella sedge populations threatens rice production. Our objectives for this study were to characterize thermal requirements for germination of smallflower umbrella sedge seeds from rice fields in California and to parameterize a population thermal-time model for smallflower umbrella sedge germination. Because the use of modeling techniques is hampered by the lack of thermal-time model parameters for smallflower umbrella sedge seed germination, trials were carried out by placing field-collected seeds in a thermogradient table set at constant temperatures of 11.7 to 41.7 C. Germination was assessed daily for 30 d, and the whole experiment was repeated a month later. Using probit regression analysis, thermal time to median germination [θT(50)], base temperature for germination (Tb), and SD of thermal times for germination [σθT(50)] were estimated from germination data, and model parameters were derived using the Solver tool in Microsoft Excel®. Germination rates increased linearly below the estimated optimum temperatures of 33.5 to 36 C. Estimated Tb averaged 16.7 C, whereas θT(50) equaled 17.1 degree-days and σθT(50) was only 0.1 degree-day. The estimated Tb for smallflower umbrella sedge is remarkably higher than that of japonica and indica types of rice, as well as Tb of important weeds in the Echinochloa complex. Relative to the latter, smallflower umbrella sedge has lower thermal-time requirements to germination and greater germination synchronicity. However, it would also initiate germination much later because of its higher Tb, given low soil temperatures early in the rice growing season in California. When integrated into weed growth models, these results might help optimize the timing and efficacy of smallflower umbrella sedge control measures.

A field experiment was conducted in 1986 and 1987 to determine the minimum effective rate (MER)3 of imazaquin and chlorimuron applied postemergence to common cocklebur. MER is defined as the quantity required to provide at least 90% control. Based on probit regression analyses, the mean calculated MERs of imazaquin and chlorimuron for 2-leaf common cocklebur were 27.5 and 4.5 g ai/ha, respectively. Under optimum growing conditions, the calculated MERs of imazaquin and chlorimuron for 6-leaf common cocklebur were 34 and 4.6 g/ha, respectively. When applied to 6-leaf plants under slight moisture stress, the calculated MERs for imazaquin and chlorimuron were 54 and 17.4 g/ha, respectively.

Navua sedge, a member of the Cyperaceae family, is an aggressive weed of pastures in Fiji, Sri Lanka, the Malay Peninsula, Vanuatu, Samoa, the Solomon Islands, and Tahiti and is now a weed of pastures and roadsides in north Queensland, Australia. Primarily restricted to areas with an annual rainfall exceeding 2,500 mm (98.4 in), Navua sedge is capable of forming dense stands, smothering many tropical pasture species. Seventeen herbicides were field tested at three sites in north Queensland, with glyphosate, halosulfuron, hexazinone, imazapic, imazapyr, or MSMA as the most effective for Navua sedge control. Environmental problems, such as persistence in soil, lack of selectivity, and movement off-site, may occur using some herbicides at the predicted 90% lethal concentration (LC90) control level rates. A seasonality trial using halosulfuron (97.5 g ai ha−1 [1.4 oz ac−1]) gave better Navua sedge control (84%) by spraying in March to September than by spraying at other times (50%). In a frequency trial, sequential glyphosate applications (2,160 g ae ha−1) every 2 mo was more effective for continued Navua sedge control (67%) than a single application of glyphosate (36%), although loss of ground cover would occur. In a management trial, single applications of glyphosate (2,160 to 3,570 g ae ha−1) using either a rope wick, ground foliar spraying, or a rotary rope wick gave 59 to 73% control, whereas other treatments (rotary hoe, 3%; slashing, −13%; crushing, −30%) were less effective. In a second management trial, four monthly rotary wick applications were much more effective (98%) than four monthly crushing applications (42%). An effective management plan must include the application of regular herbicide treatments to eliminate Navua sedge seed being added to the soil seed bank. Treatments that result in seed burial, for example, discing, are likely to prolong seed persistence and should be avoided. The sprouting activity of vegetative propagules and root fragmentation also needs to be considered when selecting control options.

Probit-based models relating a proportional response variable to a temporal explanatory variable, assuming that the times to response are normally distributed within the population, have been used in seed biology for describing the rate of loss of viability during seed ageing and the progress of germination over time in response to environmental signals (e.g. water, temperature). These models may be expressed as generalized linear models (GLMs) with a probit (cumulative normal distribution) link function, and, using GLM fitting procedures in current statistical software, parameters of these models are efficiently estimated while taking into account the binomial error distribution of the dependent variable. The fitted parameters can then be used to calculate the ‘traditional’ model parameters, such as the hydro- or hydrothermal time constant, the mean or median response of the seeds (e.g. mean time to death, median base water potential), and the standard deviation of the normal distribution of that response. Furthermore, through consideration of the deviance and residuals, performing model evaluation and modification can lead to improved understanding of the underlying physiological/ecological processes. However, fitting a binomial GLM is not appropriate for the cumulative count data often collected from germination studies, as successive observations are not independent, and time-to-event/survival analysis should be considered instead. This review discusses well-known probit-based models, providing advice on how to collect appropriate data and fit the models to those data, and gives an overview of alternative analysis approaches to improve understanding of the underlying mechanisms of seed dormancy and germination behaviour.

Micro-data from a 1984 survey of adult education in Canada are used in the study. The data for persons 65 years of age and over are analysed using probit techniques. Prior level of education is found to be of considerable importance in determining the probabilities that elderly people will make use of adult education facilities. It is argued that future elderly population cohorts will have higher average education levels than present ones and that their members will therefore be more likely to take courses. Projections of increases in course enrolment by persons 65 and over are made for the next quarter century, based on the results of the probit analysis and projections of the population.