Rheological and chemical predictors of texture and taste in dessert banana (Musa spp.)

To be able to account for sensory qualities earlier in the assessment of a new banana hybrid in a selection scheme, predicting the sensory perception of banana texture and taste by instrumental parameters was investigated. Thirteen cultivated banana and four new triploid hybrids were characterized by sensory profiling, and rheological and chemical analyses. Multilinear regressions were used to calibrate predictions using 13 cultivated bananas, and the quality of predictions was validated using four hybrids. The sensory characteristics sourness and sweetness were predicted by titratable acidity (R² = 0.68) and pH (R² = 0.66). Malate and citrate were the main contributors to sweetness and sourness. Astringency was predicted by total tannins (R² = 0.55). Rheological parameters from texture profile analyses (stress at fracture, fracturability) were more suitable than pulp puncture force to predict the sensory texture properties firmness (R² = 0.47) and melting (R² = 0.60). These textural properties were predicted by titratable acidity and dry matter content (R² = 0.62). Predictions of mealiness, adhesiveness, and heterogeneity were not efficient. Differences of 3.6–3.7 meq 100 g⁻¹ FW in titratable acidity or of 0.30 g 100 g⁻¹ FW in malate or citrate were required to ensure a detectable difference in sourness or sweetness (p = 0.9). Pulp puncture force needed to differ by a minimum of 0.9 N before a difference in firmness could be perceived by the panelists. In conclusion, while models to predict sourness and sweetness can now be used for high throughput phenotyping, we recommend additional tests for other sensory attributes.     

油松针叶面积估计模型及比叶面积的研究

叶面积和比叶面积是植物生长过程中的重要参数.本研究基于河北木兰围场实测油松数据,通过winSEEDLE种子和针叶图像分析系统获得油松522个单个针叶的表面积LA、针叶长度L、针叶宽W、针叶周长P,分别建立了以针叶长、针叶宽、针叶周长等形状属性为自变量的叶面积估计模型和以针叶干质量为自变量的叶面积估计模型.用总相对误差、平均相对误差、平均相对误差绝对值、均方根误差、预估精度5个统计量来检验模型的误差和拟合优度,经检验模型LA=-2.761 +0.464 L +6.608W和LA =1.345 +0.501X分别为这两种模型中最好,X为针叶干质量.通过对算术平均法、比估计法、最小二乘法3种方法的比较,得到油松的比叶面积为7.08 m2 ·kg-1.本研究为油松叶面积的估计提供了一个简单可靠的方法.     

低氮胁迫下我国不同年代玉米品种产量及产量构成因子变化趋势研究

试验以我国不同年代的35个玉米品种为材料,在施氮肥和不施氮肥两个水平下对产量、穗长、穗粗、穗粒数、秃尖长、轴粗、百粒重共7个农艺性状进行考查比较。结果表明,除轴粗以外,其余几个农艺性状不同年代间差异均达到显著或极显著水平,随年代变化玉米品种产量显著提高,氮胁迫压力下不同年代玉米品种产量均下降。正常施氮条件下,各年代玉米品种的穗长、穗粗、穗粒数呈上升趋势,低氮胁迫降低了穗长、穗粗、穗粒数及百粒重,而对轴粗无明显影响。研究还表明,1950年以来我国玉米品种的耐低氮能力没有明显提高。育种工作要在自交系选育中重视低氮条件,为进一步培育耐低氮杂交种奠定基础。     

Pod Dehiscence in Relation to Chemical Components of Pod Shell in Soybean

Abstract

The relationship between chemical components of pod shell and pod dehiscence was investigated using 25 soybean cultivars; 16 with easily dehiscing pods (susceptible cultivars) and 9 with hardly dehiscing pods (resistant cultivars). After air-drying for about three weeks, the pod shells were ground and analyzed for the contents of neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), hemi-cellulose (HCe), cellulose (Ce), uronic acid and calcium. The correlation of the contents of chemical components with the percentage of pod dehiscence (%PD) was examined by principal component analysis. The first principal ingredient score was given by the formula; score = – 0.421[ADF] – 0.038[ADL] + 0.821[HCe] – 0.382[Ce] + 20.556, where, [ADF], [ADL], [HCe] and [Ce] are percentage of each component in dried pod shell. This score gave an eigenvalue of 30.2 and contribution rate of 97.1%, and the score was higher in the susceptible cultivars than in the resistant cultivars on the average. The multiple regression analysis of the relationship between %PD and the content of chemical components also showed that %PD was best predicted by the regression equation with two chemical components, [HCe] and [Ce]. Water retention capacity and cellulose crystallinity of the pod shell were less different between the susceptible and resistant cultivars. The results in this study suggested that the chemical analysis of dry pod shell may provide useful information on breeding and selection of the resistant cultivars.     

Developmental Responses of Wheat cv. Norin 61 to Fluence Rate of Green Light

Summary

Wheat (Triticum aestivum L. cv. Norin 61) plants were grown under five different photon flux densities obtained by modulating the number of green light-emitting diodes (LEDs) under white fluorescent lamps. The experiment was conducted under continuous irradiation at a constant temperature of 20°C to clarify the developmental responses of wheat to the fluence rate of green light. The higher the photon flux density of green light, the shorter the number of days from emergence to heading. The earliest heading was observed in the plants grown under 496 green LEDs, 32.0 days after emergence. A significant logarithmic function could fit the relationship between the fluence rate of green light and developmental rate. In this report, principal component analysis (PCA) was adopted to analyze the confounding of green light versus photosynthetic photon flux density (PPFD) with 17 developmental and morphological traits. The eigenvalues explained were 5.64, 3.20, and 2.61, respectively, for the first, second and third principal components (PCs). The first PC was assumed as the factor related to the isometric growth, and the third PC was assumed as the factor related to the developmental rate and culm elongation. Therefore, it was supposed that the first and third PCs were affected by the PPFD and the photon flux density of green light, respectively. The results suggested that the fluence rate of green light affects the development of wheat as a signal source. Furthermore, the development of wheat was promoted by the green light independent of PPFD.     

Semiquantitative multi‐analysis of plasma obtained from Romney lambs (Ovis aries) by inductively coupled plasma mass spectrometry,and the classification according to feed type

The establishment of a classification system for domestic animals on consumed feed stuff is thought to be important from both a hygiene and market point of view. We collected plasma samples of Romney lambs (Ovis aries) which were fed one of the following: a herb‐clover mix (n = 10) which included chicory, red clover, white clover and plantain; a plant‐grass mix (n = 10) which included plantain, ryegrass and white clover; or a grass mix (n = 10) which included ryegrass and white clover. A total of 20 elements in plasma samples obtained from the lambs were analyzed using inductively coupled plasma mass spectrometry. The data were then analyzed by principal component analysis. The lambs were divided into three groups on a score plot depending on the different feed conditions. Furthermore, discriminant analyses of the elements were examined, using linear discriminant analysis with forward stepwise regression. This discriminant function correctly classified the samples from each group. The accuracy of classification of each group, as shown by 10‐fold cross‐validation, proved the effectiveness of the established discriminant function. It is concluded that using linear discriminant analysis might be a useful tool for the validation of elements from plasma in lambs grown in different conditions.     

Proximal sensing of the seasonal variability of pasture nutritive value using multispectral radiometry

The nutritive value of pasture is an important determinant of the performance of grazing livestock. Proximal sensing of in situ pasture is a potential technique for rapid prediction of nutritive value. In this study, multispectral radiometry was used to obtain pasture spectral reflectance during different seasons (autumn, spring and summer) in 2009–2010 from commercial farms throughout New Zealand. The analytical data set (n = 420) was analysed to develop season‐specific and combined models for predicting pasture nutritive‐value parameters. The predicted parameters included crude protein (CP), acid detergent fibre (ADF), neutral detergent fibre (NDF), ash, lignin, lipid, metabolizable energy (ME) and organic matter digestibility (OMD) using a partial least squares regression analysis. The calibration models were tested by internal and external validation. The results suggested that the global models can predict the pasture nutritive value parameters (CP, ADF, NDF, lignin, ME and OMD) with moderate accuracy (0·64 ≤ r² ≤ 0·70) while ash and lipid are poorly predicted (0·33 ≤ r² ≤ 0·40). However, the season‐specific models improved the prediction accuracy, in autumn (0·73 ≤ r² ≤ 0·83) for CP, ADF, NDF and lignin; in spring (0·61 ≤ r² ≤ 0·78) for CP and ash; in summer (0·77 ≤ r² ≤ 0·80) for CP and ash, indicating a seasonal impact on spectral response.     

Genotypic Diversity of Cross-Tolerance to Oxidative and Drought Stresses in Rice Seedlings Evaluated by the Maximum Quantum Yield of Photosystem II and Membrane Stability

Abstract

The genotypic variation of oxidative damage under oxidative and drought stresses was evaluated for a total of 67 rice cultivars consisting of 61 from the rice diversity research set of germplasm and 6 high-yielding varieties. The maximum quantum yield of photosystem II (F_v/F_m) and the membrane stability index (MSI) were measured to assess the oxidative damage induced by methyl viologen (MV) for oxidative stress and polyethylene glycol (PEG) for drought stress. Considerable variations in F_v/F_m and MSI among the cultivars in MV treatment indicated the existence of genotypic diversity in the susceptibility to oxidative damage. The weak relationships of F_v/F_m and MSI between MV and PEG treatment suggested that mechanisms other than oxidative stress tolerance affected the genotypic diversity of oxidative damage in PEG treatment. We used principal component analysis to quantify the cross-tolerance to oxidative damage under MV and PEG treatments: cross-tolerance was higher in cultivars in the japonica group than in the indica groups and higher in the improved cultivars than in the landraces. These results suggest that genotypic diversity of cross-tolerance is related to adaptation to the ecosystem where the genotypes originated and that the characteristics responsible for the tolerance to oxidative damage have been selected during breeding for improved grain yield.     

Analysis of horse movements from non-commercial horse properties in New Zealand

AIMS: To investigate property-level factors associated with the movement of horses from non-commercial horse properties, including the size and location of the property, number and reason for keeping horses.

METHODS: Using a cross-sectional survey 2,912 questionnaires were posted to randomly selected non-commercial horse properties listed in a rural property database. The survey collected information about the number of horses, and reasons for keeping horses on the property, and any movement of horses in the previous 12 months. Three property-level outcomes were investigated; the movement status of the property, the frequency of movement events, and the median distance travelled from a property. Associations were examined using logistic regression and Kruskal-Wallis analysis of variance.

RESULTS: In total 62.0% (488/791) of respondents reported at least one movement event in the year prior to the survey, for a total of 22,050 movement events. The number of movement events from a property varied significantly by the number of horses on the property (p<0.02), while the median distance travelled per property varied significantly by both region (p<0.03) and property size (p<0.01). Region, property size, the number of horses kept, and keeping horses for competition, recreation, racing or as pets were all significantly associated with movement status in the multivariable analyses (p<0.001).

CONCLUSION AND CLINICAL RELEVANCE: This study showed that there are characteristics of non-commercial horse properties that influence movement behaviour. During an exotic disease outbreak the ability to identify properties with these characteristics for targeted control will enhance the effectiveness of control measures.