Methane, in addition to being a significant source of energy loss to the animal that can range from 0·02 to 0·12 of gross energy intake, is one of the major greenhouse gases being targeted for reduction by the Kyoto protocol. Thus, one of the focuses of recent research in animal science has been to develop or improve existing methane prediction models in order to increase overall understanding of the system and to evaluate mitigation strategies for methane reduction. Several dynamic mechanistic models of rumen function have been developed which contain hydrogen gas balance sub-models from which methane production can be predicted. These models predict methane production with varying levels of success and in many cases could benefit from further development. Central to methane prediction is accurate volatile fatty acid prediction, representation of the competition for substrate usage within the rumen, as well as descriptions of protozoal dynamics and pH. Most methane models could also largely benefit from an expanded description of lipid metabolism and hindgut fermentation. The purpose of the current review is to identify key aspects of rumen microbiology that could be incorporated into, or have improved representation within, a model of ruminant digestion and environmental emissions.
Genotype by environment (G x E) interaction effects are of special interest for breeding programmes to identify adaptation targets and test locations. Their assessment by additive main effect and multiplicative interaction (AMMI) model analysis is currently defined for this situation. A combined analysis of two former parametric measures and seven AMMI stability statistics was undertaken to assess G x E interactions and stability analysis to identify stable genotypes of 11 lentil genotypes across 20 environments. G x E interaction introduces inconsistency in the relative rating of genotypes across environments and plays a key role in formulating strategies for crop improvement. The combined analysis of variance for environments (E), genotypes (G) and G x E interaction was highly significant (P<0.01). suggesting differential responses of the genotypes and the need for stability analysis. The parametric stability measures of environmental variance showed that genotype ILL 6037 was the most stable genotype, whereas the priority index measure indicated genotype FLIP 82-1L to be the most stable genotype. The first seven principal component (PC) axes (PC1-PC7) were significant (P<0.01), but the first two PC axes Cumulatively accounted for 71% of the total G x E interaction. In contrast, the AMMI stability statistics suggested different genotypes to be the most stable. Most of the AMMI stability statistics showed biological stability, but the SIPCF statistics of AMMI model had agronomical concept stability. The AMMI stability value (ASV) identified genotype FLIP 92-12L as a more stable genotype, which also had high mean performance. Such an outcome could be regularly employed in the future to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for recommendations for lentil and other crops in the Middle East and other areas of the world.
The use of secondary traits such as number of ears per plant, grains per ear, the interval from anthesis to silking, leaf senescence and leaf rolling, together with management of water stress and recurrent selection, have permitted a considerable increase in drought tolerance in the CIMMYT maize source germplasm populations Drought Tolerant Population (DTP) and La Posta Sequia (LPS). Inbred lines were extracted from DTP C-9 and LPS C-7 cycles and then used for generating single and three-ways hybrids. These were evaluated under normal irrigation and managed drought conditions. A weak, and in some cases no longer significant, correlation was found between grain yield and the traits initially used for selection. Most prominently, the relationship between an thesis-silking interval and grain yield became much weaker in these hybrids. Conversely, significant negative correlations were found between tassel dry weight and grain yield. Three-way hybrids involving two DTP lines yielded more than those involving one only, indicating the feasibility of gene pyramiding for drought tolerance. Overall, the results suggested that the relationship between grain yield and secondary traits has been modified due to continuous selection in the LPS and DTP populations. Some long-established secondary traits have become less important, while others have become more relevant. Mean grain weight, previously not used within a drought selection index, was strongly correlated with yield in the present study. The importance of traits related to the availability in C products for the development of ears and grains are discussed. The results indicate that the traits of source organs contribute marginally to drought tolerance; variation of leaf or root traits seems to be less important than variation in tassel parameters for increasing drought tolerance. For ensuring further progress in drought tolerance in maize, the solution might reside in the manipulation of sink organs. It is therefore suggested that selection for even greater number of ears, bigger grains and smaller tassels may help to increase grain yield under water limited environments in the near future. A short discussion on the optimal choice of parental lines for developing hybrids with maximum expression of drought tolerance concludes the paper.
Watermelon is a crop with a high water demand and is frequently grown under conditions of higher than normal root-zone salinity. In the present study. seedlings of watermelon (cv. Fantasy, Citrullus lanatus (Thunb.) Matsum & Nakai) were grown either ungrafted or grafted on three rootstocks: Strong Tosa, S1 (both Cucurbita maxima x Cucurbita moschata), or Emphasis All the plants were exposed to an NaCl-induced salinity stress (electrical conductivity, EC=2.2, 4.0. or 6.0 dS/m). The vegetative growth of all the plants substantially reduced after 2 weeks of exposure to 6.0 dS/m: however. growth of the plants grafted on Strong Tosa reduced less than that of the others. The leaf water content and specific leaf area (SLA, m(2)/g) decreased with an increasing salinity in grafted plants, but not in ungrafted plants. Salinity induced an increase of superoxide dismutase (SOD) activity in grafted plants LIP to two-Fold depending on the rootstock, whereas it had no effect on this enzyme activity In ungrafted plants. Leaf Na+ concentration increased with increasing, salinity in ungrafted and SI grafted plants, whereas there was no significant leaf Na+ accumulation in Emphasis and Strong Tosa grafted plants. Leaf K+ concentration was affected by the rootstock but not by salinity, thus, the ability to keep,I high K+/Na+ ratio was achieved mainly by limiting leaf Na+ concentration. The rootstock determined the leaf Cl- accumulation, with lower overall concentrations found if plants were grafted on the S1 rootstock than on Emphasis or ungrafted plants. Salinity significantly decreased the leaf NO3- concentration on Emphasis grafted plants only, while the NO3-/Cl- ratio was reduced in all the rootstocks. The capacity of Strong Tosa to withstand salt stress better than other tested rootstocks was probably due to the ability to induce anatomical adaptation (SLA) and SOD activity in response to salt stress, and also to the efficiency of Na+ exclusion from the shoot.
A series of studies were carried out to measure the methane (CH4) production by Japanese goats fed 19 different diets (D-1-D-19) varying in nutritive composition in the open circuit respiration chamber (RC) and to compare them with CH4 estimated by the in vitro gas production test (IVGPT). Adult Japanese goats (>2 years old) with a mean body weight of 26 +/- 54 kg were used in these experiments. Each diet was fed to four randomly selected goats and feeding was carried out at 1.1 maintenance (M) as per National Research Council (NRC) (1981) for goats. Average CH4 emission by goats in the RC ranged from 0.23 to 0.39 (mean value 31 ml/g dry matter intake (DMI)): when it was expressed as a proportion of gross energy or with methane conversion rate (MCR) it ranged from 5.0 to 8.2. with an average of 6.6. Incorporation of by-products like sweet potato vine silage (SPVS) (P = 0.016), dried pumpkin (P = 0.052) and brewers' grain in the diet suppressed (P < 0.01) methanogenesis in goats, when compared with that of standard farm diet (D-1). The CH4 output measured in the RC was very close to that estimated from the gas collected after 24 h and higher after 48 h of in vitro incubation. Although composition of the diets' acid detergent fibre (ADF) had a significant effect on methane emission, methane output estimated by IVGPT was very close to that measured in the RC demonstrating that this system Could be used to estimate the CH, production potential from diets in preparing a database and also in the planning of mitigation strategies in small ruminants to improve their performance as well as to reduce greenhouse gas emissions.
Increased harvest index (HI) has been one of the principal factors contributing to genetic yield improvements in spring barley (Hordelim vulgare L.), oat (Avena sativa L.) and wheat (Triticum aestivum L.) cultivars. Although high HI demonstrates high-yielding ability when cultivars are compared, it can also indicate challenges to yield formation when comparisons are made across differing growing conditions. The present study was designed to investigate variation in HI among modern cereal cultivars relative to that brought about by a northern environment, to assess whether HI still explains the majority of the differences in grain yield when only modern cereal cultivars are compared, and to monitor key traits contributing to HI. Stability of HI was also investigated with reference to the role of tillers. Twelve experiments (3 years, two locations, two nitrogen fertilizer regimes) were carried out in Southern Finland to evaluate 12 two-row spring barley, 10 six-row barley, 10 oat and I I wheat cultivars. In addition to HI, days to heading and maturity, length of grain filling period, grain yield, test weight and 13 traits characterizing plant stand structure were measured and analysed with principal component analysis (PCA) to detect traits associated with HI and those contributing to stability of H L Although only modern cereals were studied, differences among cultivars were significant both in mean HI and stability of HI, and HI was associated with short plant stature in all modern cereal species. Also, single grain weight was associated with HI in all species. Differences between, but not within, species in HI were partly attributable to differences in filler performance. Grain yield was associated closely with HI except in two-row barley. It may be possible to further increase HI of wheat, as it still was relatively low. High HI did, however, not indicate the degree of success in yield determination when environments are compared.
The transition from conventional to organic farming is accompanied by changes in soil chemical properties and processes that could affect soil fertility. The organic system is very complex and the present work carries out a short-term comparison of the effects of, organic and conventional agriculture on the chemical properties of a silty loam Soil (Xerofluvenet) located in the Guadalquivir River valley. Seville, Spain, through a Succession of five crop cycles over a 3-year period. Crop rotation and varieties were compared in a conventional system using inorganic Fertilizer and two organic systems using either plant compost or Manure. At the end of the Study, Organic farming management resulted in hi,,her soil organic carbon (OC). N and available P, K, Fe and Zn. The available Mn and especially Cu values did not show significant differences. In general. treatment with manure resulted in more rapid increases in soil nutrient Values than did plant compost. which had an effect on several crop cycles later. The present study demonstrated that the use of organic composts results in an increase in OC and the storage of nutrients. Which call provide long-term fertility benefits. Nevertheless, at least 2-3 years of organic management are necessary. depending on compost characteristics, to observe significant differences. Average crop yields were 23% lower in organic crops. Nevertheless, only two crops showed statistically significant differences.
The Cornell-Penn-Miner (CPM) Dairy is an applied mathematical nutrition model that computes dairy cattle requirements and the supply of energy and nutrients based on characteristics of the animal, the environment and the physicochemical composition of the feeds under diverse production scenarios. The CPM Dairy was designed as a steady-state model to use rates of degradation of feed carbohydrate and protein and the rate of passage to estimate the extent of ruminal fermentation, microbial growth, and intestinal digestibility of carbohydrate and protein fractions in computing energy and protein post-rumen absorption, and the supply of metabolizable energy and protein to the animal. The CPM Dairy version 3.0 (CPM Dairy 3.0) includes an expanded carbohydrate fractionation scheme to facilitate the characterization of individual feeds and a sub-model to predict ruminal metabolism and intestinal absorption of long chain fatty acids. The CPM Dairy includes a non-linear optimization algorithm that allows for least-cost formulation of diets while meeting animal performance, feed availability and environmental restrictions of modern dairy cattle production. When the CPM Dairy 3.0 was evaluated with data of 228 individual lactating dairy cows containing appropriate information including observed dry matter intake, the linear regression between observed and model-predicted milk production values indicated the model was able to account for 79.8 % of the variation. The concordance correlation coefficient (CCC) was high (r(c) = 0.89) without a significant mean bias (0-52 kg/d; P= 0.12). The accuracy estimated by the CCC was 0.997. The root of mean square error of prediction (MSEP) was 5.14 kg/d (0.16 of the observed mean) and 87.3 % of the MSEP was due to random errors, suggesting little systematic bias in predicting milk production of high-producing dairy cattle. Based upon these evaluations, it was concluded the CPM Dairy 3.0 model adequately predicts milk production at the farm level when appropriate animal characterization, feed composition and feed intake are provided; however, further improvements are needed to account for individual animal variation.
Nine spring wheat cultivars, selected on the basis of height, tillering capacity and maturity, were grown in differing levels of natural weed presence at three locations in Edmonton and New Norway, Alberta between 2003 and 2004. The objectives of the study were to (1) identify competitive traits in wheat cultivars, (2) determine whether traits associated with competitive ability differ under increasing weed pressure and (3) assess cultivar stability in and adaptation to environments differing in yield potential and weed competition. Eight experimental environments (including conventionally and organically managed fields with and without common oats sown as a weed analogue) were grouped into low, medium and high weed pressure levels, based on mean total weed biomass. Tallness and early heading and maturity were related to increased grain yield at the highest weed level. Greater spikes/m(2), tallness and early heading were associated with reduced weed biomass, depending on weed level. Principal component analysis (PCA) revealed that height accounted for a small amount of variation in low weed environments, yet was more important as weed pressure increased. Finlay-Wilkinson (Finlay & Wilkinson 1963) stability analysis demonstrated that cultivars responded differently in environments differing in yield potential and in weed pressure. Older wheat cultivars were generally more yield-stable across environments, while modern semidwarf cultivars were more sensitive to changes in weed level. The cultivar Park (released in 1963) was the most yield and weed-stable cultivar, coupled with relatively high yields and average weed biomass accumulation, and may therefore be well adapted to low yielding or high weed environments.
A centenary review presents an opportunity to ponder over the processes of concept development and give thought to future directions. The current review aims to ascertain the ontogeny of current concepts, underline the connection between ideas and people and pay tribute to those pioneers who have contributed significantly to modelling in animal nutrition. Firstly, the paper draws a brief portrait of the use of mathematics in agriculture and animal nutrition prior to 1925. Thereafter, attention turns towards the historical development of growth modelling, feed evaluation systems and animal response models. Introduction of the factorial and compartmental approaches into animal nutrition is noted along with the particular branches of mathematics encountered in various models. Furthermore, certain concepts, especially bioenergetics or the heat doctrine, are challenged and alternatives are reviewed. The current state of knowledge of animal nutrition modelling results mostly from the discernment and unceasing efforts of our predecessors rather than serendipitous discoveries. The current review may stimulate those who wish for greater understanding and appreciation.
A large body of published research now exists on economic, social, technical and policy related aspects of organic production. The dramatic increase in published research over the last 20 years reflects not only the existence of policy support for organic farming in some countries but also the availability of government funding for research on organic farming. This has resulted in a broadening out of organic research from privately funded, specifically organic research organizations, into universities and mainstream research institutes. In parallel, publication of research results from organic farming has increasingly appeared in refereed literature in addition to literature sources more available to farmers and advisors. Research scientists from Europe, North America and Australasia have all made important contributions to the peer-reviewed literature. The literature is dominated by comparisons of organic and other forms of agriculture, although in many cases these comparisons are not fully valid. Research directed specifically at organic systems is often much more valuable in developing improved production systems than comparative research. Research on organic farming embodies both holistic and reductionist research approaches. Trans-disciplinary research also has an important role to play in understanding the complexities of the ecological approach to agriculture typified by organic farming. Working within the principles and standards of organic agriculture will mean that some research will always be specific to organic production systems. However, in future an increased transfer of knowledge from organic to conventional agriculture and vice versa is envisaged.
Pearl millet [Pennisetum glaucum (L) R. Br.] is an important cereal crop in Niger, West Africa and a potential crop for the United States of America (USA). Only a few studies have been conducted in either country to identify the optimum planting dates for high and stable yields, in part because planting date experiments are resource-intensive. Crop simulation models can be an alternative research tool for determining optimum planting dates and other management practices. The objectives of the present study were to evaluate the performance of the Cropping System Simulation Model (CSM)-CERES-Millet model for two contrasting environments, including Mead, Nebraska, USA and Kollo, Niger, West Africa and to use the model for determining the optimum planting dates for these two environments. Field experiments were conducted in both environments to study the impact of nitrogen fertilizer on grain yield of three varieties in Kollo and three hybrids in Mead and their associated growth and development characteristics. The CSM-CERES-Millet model was able to accurately simulate growth, development and yield for millet grown in these two contrasting environments and under different management practices that included several genotypes and different nitrogen fertilizer application rates. For Kollo, the optimum planting date to obtain the maximum yield was between 13 and 23 May for variety Heini Kirei, while for the other varieties the planting dates were between 23 May and 2 June. For Mead, the planting date analysis showed that the highest simulated yield was obtained, on average, between 19 and 29 June for hybrid 59022A x 89-083 and 1361M x 6Rm. Further studies should focus on evaluation and application of the millet model for other agroclimatic regions where pearl millet is an important crop.
Remotely sensed estimates of biochemical parameters of agricultural crops are central to the precision management of agricultural crops (precision farming). Past research using in situ and airborne spectral reflectance measurements of various vegetation species has proved the usefulness of hyperspectral data for the estimation of various biochemical parameters of vegetation. In order to exploit the vast spectral and radiometric resources offered by space-borne hyperspectral remote sensing for the improved estimation of plant biochemical parameters, the relationships observed between spectral reflectance and various biochemical parameters at in situ and airborne levels needed to be evaluated in order to establish the existence of a reliable and stable relationship between spectral reflectance and plant biochemical parameters at the pixel scale. The potential of the EO-1 Hyperion hyperspectral sensor was investigated for the estimation of total chlorophyll and nitrogen concentrations of cotton crops in India by developing regression models between hyperspectral reflectance and laboratory measurements of leaf total chlorophyll and nitrogen concentrations. A comprehensive and rigorous analysis was carried out to identify the spectral bands and spectral indices for accurate retrieval of leaf total chlorophyll and nitrogen concentrations of cotton crop. The performance of these critical spectral reflectance indices was validated using independent samples. A new vegetation index, named the plant biochemical index (PBI), is proposed for improved estimation of the plant biochemicals from space-borne hyperspectral data; it is simply the ratio of reflectance at 8 10 and 560 nm. Further, the applicability of PBI to a different crop and at a different geographical location was also assessed. The present results suggest the use of space-borne hyperspectral data for accurate retrieval of leaf total chlorophyll and nitrogen concentrations and the proposed PBI has the potential to retrieve leaf total chlorophyll and nitrogen concentrations of various crops and at different geographical locations.
Currently, society awareness, legislations and competing markets demand dairy farming systems which are sustainable. In the near future, farm management and animal genetics will be key elements in developing such sustainability. Although the effect of farm management on some attributes of sustainability has already been studied, the impacts and scope for realizing goals of agricultural multifunctionality through genetic changes are still to be tested. Sustainable and Integrated Management Systems for Dairy Production (SIMSDAIRY) is a new farm level modelling framework which integrates these concepts to practical actions and brings all of this complexity into an operational and scientific modus operandi. The current paper provides a brief description of the structure of SIMSDAIRY and an example of how it can be used to compare the scope for improving the overall sustainability of a dairy farm by: (i) future system changes aimed at improving genetic characteristics of plants and animals with (ii) current system structural changes aimed at improving nutrient management efficiency. In order to do this comparison, management factors and new genetic traits from plants or/and animals, acting singly or in combination, are evaluated against a baseline dairy farm scenario. Sustainability is measured in terms of targets associated with: (i) the Nitrates Directive, (ii) phosphorus (P) threshold for eutrophication, (iii) the Kyoto Protocol, (iv) the Gothenburg Protocol, (v) an adequate net farm income for standard of living and acceptable standards of (vi) quality of milk, (vii) animal welfare, (viii) level of biodiversity, (ix) landscape aesthetics and (x) soil quality. Results suggest that genetic-based changes offer greater scope than management-based ones to improve sustainability up to an acceptable level. Costs associated with management changes are often too high within current socio-economics circumstances. Optimizing nitrogen (N) mineral fertilizer rate and timing was the only management-based measure that, while improving most of the environmental and biodiversity indices, resulted in improved economic results. Some genetic-based changes offered substantial scope for reducing environmental losses while having economic benefits. However, only those decreasing the crude protein (CP) of the plant and increasing the diet N cow partition into milk seemed to result in non-significant pollution swapping and be achievable in the nearby future.
Manure production in the most livestock-intensive areas exceeds the crop demand for nutrients and legislative restrictions on application rate cause a shortage of land for manure application. Export of nutrients in the fibrous fraction of separated animal slurry has become an option for sustaining or increasing livestock production in livestock-intensive areas. The nitrogen (N) and carbon (C) losses during on-farm storage of the fibrous fraction, originating from separation of anaerobically digested pig slurry using the non-volatile elements phosphorus (P), copper (Cu) and zinc (Zn) as internal references, were calculated. In addition, the plant availability of N in fresh and stored fibrous fractions was evaluated in an incubation experiment. The losses of N and C were greater from the heap surface than from the centre, and turning the heap by reloading for transport increased the losses. The proportion of ammonium N, total N and C lost during storage of the fibrous fraction was 0.30-0.90, 0.10-0.55 and 0.35-0.70 of the initial amount, respectively. Storage reduced the plant-available N and the amount of residual organic N, thereby having long-term influence on soil fertility. The plant-available N in fresh fibrous fractions was 0.22-0.52 of total N, but decreased to 0.15-0.38 after storage due to a decrease of the N-ammonium : N-total ratio during storage. The net mineralization of manure N was negatively related to the C-total : N-organic ratio. The fibrous fraction of separated pig slurry may be characterized as a manure with a high potential for loss and a variable value as fertilizer.
Descriptions of entire lactations were investigated using six mathematical equations. comprising the differentials of four growth functions (logistic. Gompertz, Schumacher and Morgan) and two other equations (Wood and Dijkstra). The data contained monthly milk yield records from 70 first, 70 second and 75 third parity Iranian Holstein cows. Indicators of fit were model behavior, statistical evaluation and biologically meaningful parameter estimates and lactation features. Analysis of variance with equation, parity and their interaction as factors and with cows as replicates was performed to compare goodness of fit of the equations. The interaction of equation and parity was not significant for any statistics, which showed that there vas no tendency For one equation to fit a given parity better than other equations. Although model behaviour analysis showed better performance of growth functions than the Wood and Dijkstra equations in filling the individual lactation curves, statistical evaluation revealed that there was no significant difference between file goodness of fit of the different equations. Evaluation of lactation features showed that the Dijkstra equation was able to estimate the initial milk yield and peak yield more accurately than the other equations. Overall evaluation of the different equations demonstrated the potential of the differentials of simple empirical growth functions used in file Current study as equations for fitting monthly milk records of Holstein dairy cattle.
A model of reproductive performance was developed to study the influences of breeding management decisions and animal characteristics on the reproductive performance and the calving distribution in a beef herd. In the model, reproductive performance is formalized as a sequence of events (parturition, ovulation, conception), each of which modifies the reproductive status of the simulated cow. With respect to reproduction, a cow can be in one of three possible states: open-not-cycling, open-cycling or pregnant. The length of the different intervals that are included between two successive reproductive events (calving to first cycle interval, length of oestrous cycles, calving-conception and calving intervals) is formalized using stochastic or empirical laws that may be influenced by numerous animal or environmental factors or by management decisions (feeding strategy, breeding season and length of the breeding period). Within the herd, cows are considered to differ from each other by their parity, calving date, body condition at calving and their bull exposure. Calving to first oestrous interval (postpartum anoestrous interval (PPAI)) is expressed as the SLIM of three equations which formalize the respective effects of calving date, body condition score at calving (BCScalving) and the response to early bull exposure in interaction with BCScalving. The influences of these variables on reproductive performance were quantified by analysing data sets (three bibliographical and two experimental) or by expertise. Special attention was paid to the influence of calving date on PPAI and a biological interpretation of this effect is proposed. Probabilities of natural insemination success were estimated according to the number of oestrus and the number of matings. The model was fitted to data from primiparous Charolais cows (n = 139) bred at the experimental station Laqueuille (French National Institute for Agricultural Research (INRA)). Its ability to simulate PPAI was tested using an independent data set of primiparous Charolais cows (n = 188) from the experimental farm Le Pin. The model only accounts for 39% of the observed inter-individual variability. However, the analysis of the mean square deviation components led to validation of the structure of the model. In particular, the assumption that the influence of calving date on PPAI can be attributed to a sensitivity of the reproductive function to the variation of the photoperiod during the month preceding parturition was confirmed. Simulations also revealed that fat cows could have similar anoestrus to thin cows when they are exposed early to a bull. Such a result emphasized the necessity to investigate further and better calibrate the combined effects of BCS at calving and bull exposure on PPAI.
The objective of the present paper was to propose a statistical approach to support selection of the most promising genotypes in a breeding programme. The approach is based on applying two state-of-the-art statistical methodologies, likelihood-based path analysis and model-based cluster analysis. The first method is applied to find a causal mechanism lying behind a biological process of development of final crop yield. These results are then used for weighting traits to be used in cluster analysis, which helps select genotypes possessing a desirable level of yield and yield-contributing traits. An application of the approach is presented for a 2-year study on 22 grasspea genotypes, two cultivars (Derek and Krab) and 20 mutants from those cultivars. Seed yield/plant and seven yield-related traits were studied. Among these, plant height, number of branches/plant, pod length and number of seeds/plant determined seed yield; number of pods/plant influenced seed yield only for 2002. These results were used for appropriate weighting in cluster analysis, which indicated that cultivar Krab and its two mutants, K3 and K64, had the best level of the traits and were the most stable genotypes.
Previous work has shown that the national average quality of the UK wheat crop from 1974 to 1999 was associated with the preceding winter North Atlantic Oscillation (NAO). The association of the winter NAO with the grain quality measure, specific weight, was shown to be mediated by Sunshine duration during grain filling and unconditional wet day probability during grain ripening (the probability of a wet day following either a dry or a wet day), The present study tests the hypothesis that the association between specific weight and the winter NAO can be detected in data from 158 years of the Broadbalk Wheat Experiment at Rothamsted in south-east England. Specific weight from the Broadbalk Experiment responded to sunshine duration during grain filling and unconditional wet day probability during grain ripening in a similar way to the national average data. An association with the winter NAO was found in the Broadbalk data from 1956 to 2001, but not in the previous 112 years (1844-1955). This finding is consistent with other work showing significant correlations between the winter NAO and summer climate only in recent decades. It is concluded that the association between wheat quality and the NAO is a recent phenomenon.
The impact of genotype and of frequency and timing of shearing, on mohair attributes and production of modern Angora goats was studied. Goats in the southern hemisphere grazed pastures between February 2004 and 2006. There were seven shearing treatments by three genetic strains with four or eight replicates of individual goats. Treatments were: three different 6-month shearing intervals and two of 12-month shearing intervals with different months of shearing, a 7-month winter shearing interval and a 3-month shearing interval. Genetic strain was based on sire line: 1.0 South African; 1.0 Texan; and Mixed 0.5 South African and 0-5 Texan. Annual greasy mohair production was 5.08 kg, and average clean fleece production was 4.37 kg. The Angora goats produced an annual clean fleece equivalent to 0.122 of their mean fleece-free live weight which was equal to 0.34 g/kg/day. Measurements were analysed over the period of spring 2004 shearing to spring 2005 shearing, excluding the June-December shearing treatment. Increased frequency of shearing increased fleece growth and affected 13 objective and subjective attributes of mohair that were evaluated including clean washing yield, fibre diameter and fibre diameter variation, incidence of medullated fibres, staple length, fibre curvature, crimp frequency, style, staple definition, staple fibre entanglement and staple tip shape. The direction of these effects were generally favourable and for most attributes the magnitude of the response was linear and commercially important. Each additional shearing resulted in an additional 149 g of clean mohair representing 0.034 of the annual clean mohair production. This increase was associated with a 0.6 cm increase in staple length and 0.32 mu m increase in mean fibre diameter. In conclusion, Angora goats shorn less frequently grew less mohair that was more likely to be entangled in spring. Managers of Angora goats should take note of these findings.