A bayesian model for the analysis of lactation curves of dairy goats

This article aims to determine the effect of certain covariates, such as season of kidding, parity, and time of kidding on the characteristics of the lactation curve of Saanen dairy goats. Characteristics investigated are peak milk yield, time of peak milk yield, total milk production, persistency, and the relationship between fat and protein in milk composition, as well as between lactation curves of the same animal in successive years. The analysis is carried out using a hierarchical Bayesian approach, together with Wood’s model, to model lactation. Posterior distributions of quantities of interest are obtained by means of the Markov chain Monte Carlo (MCMC) methods. These clearly illustrate the significant effect of especially parity, but also season and time of kidding on the characteristics of the lactation curve. Total and peak milk yield increase with increasing parity up to about the third or fourth parity, while peak yield is later for first than for later parities. The analysis also enables estimation of lactation characteristics of untested animals, prediction of future characteristics and identification of exceptional animals.     

Recovery of cover-crop-N in the soil-plant system in the Guinea savannah zone of Ghana

In order to understand the efficiency of residue-N use and to estimate the minimum input required to obtain a reasonable level of crop response, it is important to quantify the fate of the applied organic-N. The recovery of N from ¹⁵N-labelled Crotalaria juncea was followed in the soil and the succeeding maize crop. Apparent N recovery (ANR) by maize from unlabelled Crotalaria juncea, Crotalaria retusa, Calopogonium mucunoides, Mucuna pruriens and mineral fertilizer at three locations were also evaluated. The maize crop recovered 4.7% and 7.3% of the ¹⁵N-labelled C. juncea-N at 42 days after sowing (DAS) and at final harvest, respectively. The corresponding ¹⁵N recovery from the soil was 92.4% and 58.5%. The highest mean ANR of 57.4% was with mineral fertilizer, whereas the mean ANR of 14.3% from C. retusa was the lowest. A large pool substitution and added-N interaction effect was observed when comparing N recovery from the labelled and unlabelled C. juncea. The amount of residue-N accounted for by the isotope dilution method at 42 DAS was 97.1% and at final harvest 65.8%. The large residue-N recovery in the soil organic-N pool explains the residual effect usually observed with organic residue application.     

Nitrogen and carbon mineralisation of leather meal in soil as affected by particle size of fertiliser and microbiological activity of soil

Carbon and nitrogen mineralisation of leather meal fertilisers were studied in two soils characterised by different respiration activity. Both C and N mineralisation were highest in the most active soil, and when leather meal was added as a powder rather than as 2- to 4- and 4- to 6-mm particles. Fast and slow soluble N pools were determined after extraction with cold water and with hot buffer, respectively. The N remaining after the second extraction with hot buffer was named slow-release N. The percentage of slow-release N rose as the size of the applied leather meal particles increased, whereas fast soluble N was highest in the coarsest (4-6 mm) fertiliser.     

Proton toxicity interferes with the screening of common bean (Phaseolus vulgaris L.) genotypes for aluminium resistance in nutrient solution

Common bean (Phaseolus vulgaris L.) proved to be very sensitive of low pH (4.3), with large genotypic differences in proton sensitivity. Therefore, proton toxicity did not allow the screening of common bean genotypes for aluminium (Al) resistance using the established protocol for maize (0.5 mM CaCl₂, 8 μM H₃BO₃, pH 4.3). Increasing the pH to 4.5, the Ca²⁺ concentration to 5 mM, and addition of 0.5 mM KCl fully prevented proton toxicity in 28 tested genotypes and allowed to identify differences in Al resistance using the inhibition of root elongation by 20 μM Al supply for 36 h as parameter of Al injury. As in maize, Al treatment induced callose formation in root apices of common bean. Aluminium‐induced callose formation well reflected the effect of Ca supply on Al sensitivity as revealed by root‐growth inhibition. Aluminum‐induced callose formation in root apices of 28 bean genotypes differing in Al resistance after 36 h Al treatment was positively correlated to Al‐induced inhibition of root elongation and Al contents in the root apices. However, the relationship was less close than previously reported for maize. Also, after 12 h Al treatment, callose formation and Al contents in root apices did not reflect differences in Al resistance between two contrasting genotypes, indicating a different mode of the expression of Al toxicity and regulation of Al resistance in common bean than in maize.     

Effect of bensulfuron-methyl (a sulfonylurea herbicide) on the soil bacterial community of a paddy soil microcosm

The effect of bensulfuron-methyl (BSM) on a soil microbial community in a model paddy microcosm was studied. Total bacterial numbers in the overlying water and surface soil were monitored for 2 months after the application of BSM at the field rate and a ten-fold field rate. Pentachlorophenol (PCP) was used for comparison. Neither chemical affected the total bacterial numbers remarkably, either in the overlying water or in the surface soil. In contrast, the nitrification potential was significantly suppressed by the BSM application. The bacterial community structure, as evaluated by the denaturing gradient gel electrophoresis (DGGE) of PCR amplification products from bacterial 16S rDNA, was unaffected by the BSM treatments over 8 weeks in the surface soil, compared with the control (no pesticide). In contrast, the surface soil exposed to PCP at a ten-fold field rate showed different patterns from the controls at 4 weeks and 8 weeks after application. The DGGE patterns of the overlying water were much more variable than those of the surface soil in any treatments. Cluster analysis showed that the BSM plots were classified within the same group as the control at 1 week after application and that the BSM and PCP plots from 2 weeks onward after application were grouped differently from the control. Of 22 clones excised from the DGGE gels, 20 clones belonged to the Proteobacteria and two belonged to the Verrucomicrobia. It was considered that the impact of BSM on the overall microbial community (total numbers, community structure of soil) was negligible, although BSM had an impact on some specific functions of the soil microbial community (nitrification) and a part of the community (overlying water).     

Methods to interpolate soil categorical variables from profile observations: Lessons from Iran

The paper compares semi-automated interpolation methods to produce soil-class maps from profile observations and by using multiple auxiliary predictors such as terrain parameters, remote sensing indices and similar. The Soil Profile Database of Iran, consisting of 4250 profiles, was used to test different soil-class interpolators. The target variables were soil texture classes and World Reference Base soil groups. The predictors were 6 terrain parameters, 11 MODIS EVI images and 17 physiographic regions (polygon map) of Iran. Four techniques were considered: (a) supervised classification using maximum likelihoods; (b) multinominal logistic regression; (c) regression-kriging on memberships; and (d) classification of taxonomic distances. The predictive capabilities were assessed using a control subset of 30% profiles and the kappa statistics as criterion. Supervised classification and multinominal logistic regression can lead to poor results if soil-classes overlap in the feature space, or if the correlation between the soil-classes and predictors is low. The two other methods have better predictive capabilities, although both are computationally more demanding. For both mapping of texture classes and soil types, the best prediction was achieved using regression-kriging of indicators/memberships (κ = 45%, κ = 54%). In all cases kappa was smaller than 60%, which can be explained by the preferential sampling plan, the poor definition of soil-classes and the high variability of soils. Steps to improve interpolation of soil-class data, by taking into account the fuzziness of classes directly on the field are further discussed.     

Nitrogen fertilizer–induced mineralization of soil organic C and N in six contrasting soils of Bangladesh

A 90‐day laboratory incubation study was carried out using six contrasting subtropical soils (calcareous, peat, saline, noncalcareous, terrace, and acid sulfate) from Bangladesh. A control treatment without nitrogen (N) application was compared with treatments where urea, ammonium sulfate (AS), and ammonium nitrate (AN) were applied at a rate of 100 mg N (kg soil)^–1. To study the effect of N fertilizers on soil carbon (C) turnover, the CO₂‐C flux was determined at nine sampling dates during the incubation, and the total loss of soil carbon (TC) was calculated. Nitrogen turnover was characterized by measuring net nitrogen mineralization (NNM) and net nitrification (NN). Simple and stepwise multiple regressions were calculated between CO₂‐C flux, TC, NNM, and NN on the one hand and selected soil properties (organic C, total N, C : N ratio, CEC, pH, clay and sand content) on the other hand. In general, CO₂‐C fluxes were clearly higher during the first 2 weeks of the incubation compared to the later phases. Soils with high pH and/or indigenous C displayed the highest CO₂‐C flux. However, soils having low C levels (i.e., calcareous and terrace soils) displayed a large relative TC loss (up to 22.3%) and the added N–induced TC loss from these soils reached a maximum of 10.6%. Loss of TC differed depending on the N treatments (urea > AS > AN >> control). Significantly higher NNM was found in the acidic soils (terrace and acid sulfate). On average, NNM after urea application was higher than for AS and AN (80.3 vs. 71.9 and 70.9 N (kg soil)^–1, respectively). However, specific interactions between N‐fertilizer form and soil type have to be taken into consideration. High pH soils displayed larger NN (75.9–98.1 mg N (kg soil)^–1) than low pH soils. Averaged over the six soils, NN after application of urea and AS (83.3 and 82.2 mg N (kg soil)^–1, respectively) was significantly higher than after application of AN (60.6 mg N (kg soil)^–1). Significant relationships were found between total CO₂ flux and certain soil properties (organic C, total N, CEC, clay and sand content). The most important soil property for NNM as well as NN was soil pH, showing a correlation coefficient of –0.33** and 0.45***, respectively. The results indicate that application of urea to acidic soils and AS to high‐pH soils could be an effective measure to improve the availability of added N for crop uptake.     

冬播麦区Glu-1和Glu-3位点变异及1B/1R易位与小麦加工品质性状的关系

 贮藏蛋白组成是决定小麦加工品质的重要因素。本文调查了我国冬播麦区251份主栽品种和高代品系的高分子量麦谷蛋白亚基（HMW-GS）、低分子量麦谷蛋白亚基（LMW-GS）和1B/1R易位的分布状况，研究了它们与加工品质性状的关系。结果表明，品质较差的HMW-GS N、7+9、2+12和LMW-GS Glu-A3a与Glu-B3j（1B/1R易位）在冬播麦区分布较广，频率分别为39.4%、45.0%、59.8%、37.1%和44.6%。HMW-GS和LMW-GS等位变异对籽粒蛋白质含量影响较小，对SDS沉降值、和面时间与耐揉性的加性和互作效应达1%的显著水平。按位点对加工品质性状的贡献大小，Glu-D1>Glu-B3>Glu-B1>Glu-A3>Glu-A1；就单个亚基而言，Glu-A1位点，1>2*>N；Glu-B1位点，7+8>14+15>7+9；Glu-D1位点，5+10>4+12>2+12；Glu-A3位点，Glu-A3d>Glu-A3a>Glu-A3c>Glu-A3e，Glu-B3位点； Glu-B3d>Glu-B3b>Glu-B3f >Glu-B3j。1B/1R易位对SDS沉降值、和面时间和耐揉性等加工品质性状有显著负面效应。通过选择优质高低分子量麦谷蛋白亚基和淘汰1B/1R易位系，将有助于提高我国小麦的面筋质量。     

Development and testing of a surface roughness measurement device based on aerial ultrasonic reflections

Paddy and Water Environment - Repairs of concrete irrigation channels in Japan are guided to a large extent by the degree to which their walls have degraded over decades of use. Current methods of...