Group-testing regression methods are effective for estimating and classifying binary responses and can substantially reduce the number of required diagnostic tests. However, there is no appropriate methodology when the sampling process is complex and informative. In these cases, researchers often ignore stratification and weights that can severely bias the estimates of the population parameters. In this paper, we develop group-testing regression models for analysing two-stage surveys with unequal selection probabilities and informative sampling. Weights are incorporated into the likelihood function using the pseudo-likelihood approach. A simulation study demonstrates that the proposed model reduces the bias in estimation considerably compared to other methods that ignore the weights. Finally, we apply the model for estimating the presence of transgenic corn in Mexico and we give the SAS code used for the analysis.

Intact grains of barley (Hordeum distichum cv. Triumph) germinated rapidly in the dark or when exposed to brief daily light breaks in the temperature range 15–25°C, although germination proceeded less rapidly at low temperatures. Prolonged illumination (16 h/day) or continuous light inhibited germination of grains most effectively when conditions were less than optimal for germination, i.e. under low temperatures, restricted water, and low water potential induced by mannitol. Embryos isolated from grains responded in a similar way to light applied when the amount of water was restricted; water stress did not affect germination percentages in the dark or after one brief light break (3 min) but appreciably reduced the rate of germination. While light was only slightly inhibitory to embryos under optimal germination conditions, its inhibitory effect was intensified when other factors tending to delay germination were present. Water restriction also caused ABA contents in embryos to rise. Under conditions of water stress (water restriction or low osmotic potential), CaCl2 enhanced the inhibitory effect of light; however, addition of LaCl3 reversed this effect. The nature of light-induced inhibition of germination is discussed.

Seed dispersal has key implications for community dynamics and restoration ecology. However, estimating seed rain (the number and diversity of seeds arriving in a given area) is challenging, and the lack of standardization in measurement prevents cross-site comparisons. Seed trap effectiveness and accuracy of seed sorting methods are key components of seed rain estimates in need of standardization. We propose and describe a standardized protocol for evaluating the effectiveness of two seed trap types (sticky and funnel traps) and the accuracy of a seed sorting method. We used widely available seeds (arugula, quinoa, sesame and sunflower) to produce a gradient of seed size, weight and colour. Proof-of-concept was tested in a tropical grassland, where traps were set for 30 days. Our results suggest that we underestimate dispersal of seeds with less than 2 mm width that can be easily mistaken for debris and soil particles or that fail to adhere to sticky traps. Seeds on sticky traps may be more vulnerable to removal by wind and rain, whereas seeds in funnel traps are more susceptible to decay. We found no evidence of observer bias on seed sorting for funnel trap samples. However, accuracy on seed sorting for funnel trap samples tended to decline for seeds with less than 2 mm width, suggesting a size-dependence in seed retrieval success. Our standardized protocol addressing trap effectiveness and seed sorting methods will increase the reliability of data obtained in seed rain studies and allow more reliable comparisons between datasets.

In the present study a combination of BLAST mediated homology search and 3′ RACE was utilized to isolate the full-length gene of Eleusine coracana alpha prolamin (Ec-α-prolamin) from finger millet. Phylogenetic analysis of Ec-α-prolamin along with related prolamin genes of different cereals and millets shows the clustering of Ec-α-prolamin in a separate group. Secondary structure prediction reveals 59.4% alpha helix structure, a structural hallmark of Ec-α-prolamin. Besides this, the protein also possesses a balanced proportion of all essential amino acids. Expression analysis based on qPCR shows increased accumulation of α-prolamin transcripts in developing grains of finger millet until attainment of seed maturity. Western blotting, using a monospecific anti-α-prolamin antibody, further confirmed the expression of a 22 kDa band in the S3 and S4 stages of developing spikes. The heterologous expression of isolated full-length Ec-α-prolamin could be potentially harnessed for making nutritionally enhanced functional food products and value-added industrial products.

This work provides insights into the deterioration of cacti seeds of Escontria chiotilla (F.A.C. Weber ex K. Schum) and Stenocereus pruinosus (Otto ex Pfeiff.) Buxbaum stored ex situ at 25 °C, under dry and dark conditions or buried in situ conditions in a xerophytic shrubland. Viability, germination speed, electrolyte leakage and indicators of the redox balance including glutathione content, glutathione half-cell reduction potential (EGSSG/2GSH) and malondialdehyde (MDA), oxidized protein content, together with water-soluble antioxidant enzyme activity were assessed. Over a period of two years of storage, viability was maintained when seeds were stored ex situ at 7–9% water content compared to seeds buried in the soil. A second burial experiment showed that seeds of E. chiotilla maintained viability during a year of storage that included a rainy season followed by a dry season. Thereafter, they died rapidly during the second rainy season. In contrast, those of S. pruinosus started to lose viability after 6 months of burial at the end of the rainy season and were mostly dead at the end of the dry season. This difference in persistence between species was related to a difference in the glutathione content and antioxidant enzyme activities. In both storage experiments, the loss of viability of both species was associated to a EGSSG/2GSH shift to a more oxidative state during burial. Yet, contents in MDA and oxidized soluble proteins were not related to redox imbalance and loss of viability, indicating that these compounds are not good markers of oxidative stress in cacti seeds during storage.

Seed lot heterogeneity is often evaluated through the range between germination percentages of four seed samples, considering normal and binomial approximations for calculating the tolerated range (S). In this paper, an exact test for the germination count range (R) is derived based on the hypergeometric and the binomial probability model for germination count. Through Monte Carlo simulations, the empirical distribution of R is built to evaluate the quantiles of the exact distributions. Moreover, a power analysis is performed by simulation. Sample size and germination rate effects are evaluated. In lots with a high germination rate, the proposed test based on the hypergeometric model is about 20% more powerful than the test based on the S-value. A table containing the critical values is presented and recommended to be used in off-range heterogeneity testing.

The germination percentage (GP) is commonly employed to estimate the viability of a seed population. Statistical methods such as analysis of variance (ANOVA) and logistic regression are frequently used to analyse GP data. While ANOVA has a long history of usage, logistic regression is considered more suitable for GP data due to its binomial nature. However, both methods have inherent issues that require attention. In this study, we address previously unexplored challenges associated with these methods and propose the utilization of a likelihood ratio test as a solution. We demonstrate the advantages of employing the likelihood ratio test for GP data analysis through simulations and real data analysis.