Flesh firmness is a characteristic used to indicate fruit quality. Experimental design and data analysis are important when comparing devices that measure fruit firmness. We compared the Effegi penetrometer operated by hand, mounted in a drill press and then operated by hand, and mounted on a motorized drive and operated remotely; the hand-operated EPT pressure tester; the Instron with an Effegi probe; and a hand-operated prototype of the twist tester. Devices varied in operator differences and precision. Comparisons between devices were at the within-fruit level of variability and, therefore, more precise than comparisons where different device-operators used different fruit. We demonstrate statistical methods that are appropriate for making the comparisons of interest and discuss the possible cause of differences between operators and between devices. We also discuss how the mechanical properties of the devices may affect results and consider implications for their practical use. In this study, we found the precision of discrimination between soft and hard apples was best using the Instron in 1992, while the Instron and hand-held Effegi penetrometer were comparable in 1991. For kiwifruit, the hand-held Effegi penetrometer consistently gave the most precise measurements of softening in 1991, while the twist test was the most precise in 1992.
F.R. Harker, J.H. Maindonald and P.J. Jackson
Mark J. Bassett
Common bean (Phaseolus vulgaris L.) plant introduction 527829 (formerly Lamprecht M0048) has dark seal-brown (DSB) seedcoats and pink flowers. An investigation was conducted to determine the genotype of DSB seedcoat color. M0048 was crossed with Florida breeding line 5-593, which has genotype P [C r] D J G B V Rk. A series of crosses involving M0048, 5-593, and three genetic tester stocks (v BC2 5-593, c u BC2 5-593, and b v BC2 5-593) led to determination of the genotype. Data analysis indicated that M0048 has the genotype P [? R] J G B v lae, where DSB color is produced by the interaction of R with B. Crosses between [? R] and testers with [C r] always produced seedcoat mottling in F1, except where V masks the effect. The cross [? R] B v (DSB) × c u BC2 5-593 (cartridge buff seedcoat) produced marbled seedcoats (black/cartridge buff) with genotype [? R]/[c u ?] B V. No way was found to determine whether the mottled or marbled seedcoat patterns were controlled at C or R; hence, the allelic ambiguity is indicated with a question mark. Illustrations are provided showing the difference between seedcoat mottling (a highly variable low-contrast patterning) and seedcoat marbling (a less variable high-contrast patterning, usually with cartridge buff as the background color). The development of a new genetic tester stock, [? R] b v BC3 5-593, was described, where [? R] b v gives unpatterned dominant red seedcoat color.
Michel Génard and Claude Bruchou
An approach to studying fruit growth is presented for peach fruit (Prunus persica L. Batsch). It combines a functional description of growth curves, multivariate exploratory data analysis, and graphical displays. This approach is useful for comparing growth curves fitted to a parametric model, and analysis is made easier by the choice of the model whose parameters have a meaning for the biologist. Growth curves were compared using principal component analysis (PCA) adapted to the table of estimated parameters. Growth curves of 120 fruits were fitted to a model that assumes two growth phases. The first one described the pit growth and the first part of the flesh growth. The second described the second part of the flesh growth. From PCA, firstly it was seen that fruit growth varied according to cumulated growth during both growth phases and to date of maximal absolute growth. Secondly, fruit growth varied according to cumulated growth and relative growth rates during each phase. Further examples are presented where growth curves were compared for varying fruit number per shoot and leaf: fruit ratio, and for different sources of variation (tree, shoot, and fruit). Growth of individual fruit was not related to fruit number per shoot or to leaf: fruit ratio. Growth variability was especially high between fruit within shoots.
Graham Sanders, Elsa Sanchez and Kathleen Demchak
The increased demand for organic and sustainably grown produce has resulted in a demand for information on organic and biorational fungicides. The efficacy of these fungicides is often not established, yet they are aggressively advertised. In 2005 the efficacy of six organic and biorational fungicides and two controls were evaluated on field-grown red raspberries (Rubus idaeus `Prelude' and `Nova') for gray mold (Botrytis cinerea) management. Phytotoxicity of the fungicide treatments was evaluated on a weekly basis following each fungicide application. Fruit was harvested by hand, sorted into marketable and unmarketable categories and weighed. Subsamples of fruit were evaluated for postharvest disease development. Data analysis showed `Nova' was more susceptible to phytotoxicity than `Prelude'. The application of Phostrol resulted in the highest phytotoxicity rating when compared to all other fungicide treatments. The water spray control, standard fungicide (Captan/Elevate rotation) control, Endorse, and Lime Sulfur treatments resulted in negligible phytotoxity ratings. Applying Milstop, Milstop + Oxidate, and Oxidate + Vigor Cal Phos resulted in similar intermediate phytotoxicity ratings. Differences in marketable yield were nonexistent for the two cultivars and eight fungicide treatments. The predominant diseases observed in the postharvest evaluations were gray mold, blue mold (Penicillium sp.), and rhizopus soft rot (Rhizopus sp.) and/or mucor mold (Mucor sp.). This evaluation will be repeated in 2006.
Job Teixeira de Oliveira, Rubens Alves de Oliveira, Lucas Allan Almeida Oliveira, Paulo Teodoro and Rafael Montanari
Among the crops that are usually grown under irrigation, one can mention garlic, which is a product with high demand in Brazil and the world, it is highly valued in the cuisine of several countries, and is an aggregated crop with high economic value. In 2018, this work was conducted in Yellow Red Latosol. The objective was to characterize the structure and magnitude of the spatial distribution of garlic production components and to map the productive components to visualize spatial distribution and to evaluate the spatial correlation between garlic bulb yield (BY) and other variables of the crop: total plant mass (TPM), number of leaves (NL), floral tassel length (FTL), leaf length (LL), leaf width (LW), pseudostem diameter (PD), shoot wet mass (SWM), shoot dry mass (SDM), number of cloves per bulb (NCB), clove mass (CM), root dry mass (RDM), and irrigation (IRR). All these traits were sampled in a 90-point grid georeferenced. Data analysis using statistical and geostatistical techniques made it possible to verify that the production components and BY, TPM, NL, FTL, LL, LW, PD, SWM, SDM, CM, and IRR presented special dependence. The spatial correlation between BY and TPM, LW, and CM showed a moderate spatial dependence.
Sudarsono and Ronald G. Goldy
advice on statistical data analysis of William H. Swallow. The cost of publishing this paper was defrayed in part by the payment of page charges. Under postal regulations, this paper therefore must be hereby marked advertisement solely to indicate this
Karen E. Nix, Gregg Henderson, Betty C.R. Zhu and Roger A. Laine
degree. We thank Lixin Mao, Abner Hammond, and Seth Johnson for review of this manuscript, Douglas Hurst for his assistance in the field aspect of this experiment, and Huxin Fei, Lixin Mao, and Brian Marx for their help in the data analysis. Huxin Fei is
W. J. Lamont
of D.E. Adams. Steve Weist is gratefully acknowledged for a major contribution in data analysis. The research reported in this publication was funded by the North Carolina Agricultural Research Service. Use of trade names does not imply endorsement by
D.S. Lawson, S.K. Brown, J.P. Nyrop and W.H. Reissig
We thank David Terry and Stephen Valerio for their technical assistance, Ian Merwin for his critical review of this manuscript, John Barnard for his assistance in data analysis, and Alan Lakso for his insightful suggestions about methods for
Yuefang Wang, Carol D. Robacker and S. Kristine Braman
azalea lace bug colonies and plants in the field plots and G.D. Buntin (Dept. of Entomology), M. Van lersel, and J.G. Latimer (Dept. of Horticulture) for reviewing this manuscript. We also thank Yongfu Ge for his assistance with data analysis. The