Assessing carbon footprint (CF) of crop production in a whole crop life-cycle could provide insights into the contribution of crop production to climate change and help to identify possible greenhouse gas (GHG) mitigation options. In the current study, data for the major crops of China were collected from the national statistical archive on cultivation area, yield, application rates of fertilizer, pesticide, diesel, plastic film, irrigated water, etc. The CF of direct and indirect carbon emissions associated with or caused by these agricultural inputs was quantified with published emission factors. In general, paddy rice, wheat, maize and soybean of China had mean CFs of 2472, 794, 781 and 222 kg carbon equivalent (CE)/ha, and 0.37, 0.14, 0.12 and 0.10 kg CE/kg product, respectively. For dry crops (i.e. those grown without flooding the fields: wheat, maize and soybean), 0.78 of the total CFs was contributed by nitrogen (N) fertilizer use, including both direct soil nitrous oxide (N2O) emission and indirect emissions from N fertilizer manufacture. Meanwhile, direct methane (CH4) emissions contributed 0.69 on average to the total CFs of flooded paddy rice. Moreover, the difference in N fertilizer application rates explained 0.86-0.93 of the provincial variations of dry crop CFs while that in CH4 emissions could explain 0.85 of the provincial variation of paddy rice CFs. When a 30% reduction in N fertilization was considered, a potential reduction in GHGs of 60 megatonne (Mt) carbon dioxide equivalent from production of these crops was projected. The current work highlights opportunities to gain GHG emission reduction in production of crops associated with good management practices in China.
Brazil is one of the most important soybean producers in the world. Soybean is a very important crop for the country as it is used for several purposes, from food to biodiesel production. The levels of soybean yield in the different growing regions of the country vary substantially, which results in yield gaps of considerable magnitude. The present study aimed to investigate the soybean yield gaps in Brazil, their magnitude and causes, as well as possible solutions for a more sustainable production. The concepts of yield gaps were reviewed and their values for the soybean crop determined in 15 locations across Brazil. Yield gaps were determined using potential and attainable yields, estimated by a crop simulation model for the main maturity groups of each region, as well as the average actual famers' yield, obtained from national surveys provided by the Brazilian Government for a period of 32 years (1980-2011). The results showed that the main part of the yield gap was caused by water deficit, followed by sub-optimal crop management. The highest yield gaps caused by water deficit were observed mainly in the south of Brazil, with gaps higher than 1600 kg/ha, whereas the lowest were observed in Tapurah, Jatai, Santana do Araguaia and Uberaba, between 500 and 1050 kg/ha. The yield gaps caused by crop management were mainly concentrated in South-central Brazil. In the soybean locations in the mid-west, north and northeast regions, the yield gap caused by crop management was 2000 kg/ha. For reducing the present soybean yield gaps observed in Brazil, several solutions should be adopted by growers, which can be summarized as irrigation, crop rotation and precision agriculture. Improved dissemination of agricultural knowledge and the use of crop simulation models as a tool for improving crop management could further contribute to reduce the Brazilian soybean yield gap.
Sixteen Suffolk lambs with 29 +/- 2.0 kg body weight were housed in individual cages for 60 days and allotted to four treatments in a completely randomized design to determine the effect of administration of Salix babylonica (SB) extract and/or exogenous enzymes (ZADO (R)) on lamb performance. Lambs were fed with 300 g/kg concentrate (160 g crude protein (CP)/kg, 13.4 MJ metabolizable energy (ME)/kg dry matter (DM)) and 700 g/kg maize silage (80 g/kg CP, 11.7 MJ ME/kg DM) as a basal diet (control). Another three treatments were tested; the SB extract was administered at 30 ml/day (SB) and exogenous enzymes ZADO (R) (i.e. an exogenous enzyme cocktail in a powder form) directly fed at 10 g/day (EZ), while the last treatment contained ZADO (R) at 10 g/day + SB extract at 30 ml/day (EZSB). Lambs of the treatment EZSB had the greatest average daily weight gain (ADG) and feed conversion throughout the period of the experiment. However, during the first 30 days SB was more effective for ADG than EZ and vice versa during the last 30 days of the experiment. Water consumption was greater for SB, followed by EZ and EZSB compared to the control. Intakes of DMand organicmatter (OM) were the highest in EZSB followed by EZ, which had the greatest neutral detergent fibre, acid detergent fibre (ADF) and nitrogen (N) intakes. The EZSB treatment had the greatest DM and OM digestibilities compared to the other treatments; however, SB had the greatest ADF digestibility. Combination of EZ and SB had the best N balance. Allantoin, total purine derivatives (PD), allantoin : -creatinine ratio, and PD: creatinine ratio were increased in EZSB compared to the other treatments. However, EZ supplementation increased uric acid concentration, whereas the microbial N (g N/day) and metabolizable protein (g N/day) were increased in EZSB versus the other treatments. It can be concluded that addition of 10 g ZADO (R) in combination with S. babylonica extract at 30 ml/day in the diet of lambs increased feed intake, nutrient digestibility and daily gain, with a positive impact on the use of N and microbial protein synthesis.
Twenty four French Alpine goats (39 +/- 2.0 kg) were individually housed in a completely randomized design and fed a basal diet containing 146 g crude protein and 356 g neutral detergent fibre (NDF)/kg in the absence (control - CTRL) or presence (CELL) of 2 ml of cellulase/kg dry matter intake (DMI) for 70 days, which included a 10-day adaptation period. The feed was offered three times daily at 07.00, 13.00 and 19.00 h, but the single daily dose of cellulase was only fed at 07.00 h. Goats were hand-milked daily; milk production recorded and samples taken for compositional analysis. During the last 5 days of the experimental period, goats from each group were individually housed in stainless steel metabolic cages to enable separate and total collection of faeces and urine for nutrient digestibility and ruminal fermentation determinations. Goats fed CELL had greater DMI and greater digestibility of dry matter (DM), organic matter and NDF than CTRL goats. CELL goats had greater ruminal pH, concentration of acetic acid and concentration of propionic acid than CTRL goats. However, the concentration of ruminal butyric was lower in CELL goats compared with CTRL goats. CELL goats had greater milk yield, energy corrected milk, milk energy content, milk energy output and milk density than CTRL goats and the milk content for total solids, fat, protein and lactose were also greater for CELL goats than for the CTRL goats. The milk of CELL goats had greater palmitoleic acid, cis-10-heptadecanoic acid content and mono-saturated acids than the milk of CTRL goats and lower linoleic acid, linolenic acid contents and saturated fatty acids than the milk of CTRL goats. These results suggest that addition of 2 ml cellulase/kg DM of feed in the diet of lactating French Alpine goats elevated their milk production and improved its composition probably due to improved feed utilization.
The widespread adoption by agronomists and researchers of handheld leaf chlorophyll meters stimulates enquiries on instrumental calibration issues, given the necessity, for some applications, of inferring actual chlorophyll concentrations from the readings provided. This is especially required for recently developed and more innovative devices such as the Dualex (Force-A, France), which unlike the more common SPAD-502 (Minolta, Japan) has not undergone extensive (published) calibration tests. Additionally, devices for spectral reflectance measurements are also becoming increasingly available. In the present paper, the calibration of SPAD on maize (Zea mays L.) and of Dualex on winter wheat (Triticum aestivum L.), durum wheat (Triticum durum Desf.), horse bean (Vicia faba L.) and maize, was compared to spectral reflectance indices and full spectral information (400-2500 nm) acquired by a spectroradiometer (ASD FieldSpec) equipped with a contact probe and leaf clip. Full spectral data were exploited using partial least squares regression (PLSR). The measurements were performed in the field at Maccarese (Central Italy) in 2012, gathering a specific experimental dataset. The calibration models obtained on experimental data for SPAD (on maize) and Dualex (on four crops) showed intermediate or high estimation accuracy with root-mean-square error (RMSE) values ranging between 7 and 11 mu g/cm(2) depending on the species. These results were slightly better than those achieved using spectral reflectance indices, which were inferior though to those provided by PLSR using full spectral resolution. A synthetic database, generated by the physically based PROSPECT model, simulating hemispherical leaf reflectance and transmittance, was used to compare the performances of the reflectance indices and the chlorophyll meters for a wider range of leaf properties. The results confirmed the substantial equivalence of reflectance-based and transmittance-based (i.e. simulated SPAD and Dualex) indices and the advantage of exploiting the full spectral information, e.g. through PLSR, if available.
The benefits of reduced and zero-tillage systems have been presented as reducing runoff, enhancing water retention and preventing soil erosion. There is also general agreement that the practice can conserve and enhance soil organic carbon (C) levels to some extent. However, their applicability in mitigating climate change has been debated extensively, especially when the whole profile of C in the soil is considered, along with a reported risk of enhanced nitrous oxide (N2O) emissions. The current paper presents a meta-analysis of existing literature to ascertain the climate change mitigation opportunities offered by minimizing tillage operations. Research suggests zero tillage is effective in sequestering C in both soil surface and sub-soil layers in tropical and temperate conditions. The C sequestration rate in tropical soils can be about five times higher than in temperate soils. In tropical soils, C accumulation is generally correlated with the duration of tillage. Reduced N2O emissions under long-term zero tillage have been reported in the literature but significant variability exists in the N2O flux information. Long-term, location-specific studies are needed urgently to determine the precise role of zero tillage in driving N2O fluxes. Considering the wide variety of crops utilized in zero-tillage studies, for example maize, barley, soybean and winter wheat, only soybean has been reported to show an increase in yield with zero tillage (77% over 10 years). In several cases yield reductions have been recorded e.g. c. 1-8% over 10 years under winter wheat and barley, respectively, suggesting zero tillage does not bring appreciable changes in yield but that the difference between the two approaches may be small. A key question that remains to be answered is: are any potential reductions in yield acceptable in the quest to mitigate climate change, given the importance of global food security?
The introduction of cover crops in the intercrop period may provide a broad range of ecosystem services derived from the multiple functions they can perform, such as erosion control, recycling of nutrients or forage source. However, the achievement of these services in a particular agrosystem is not always required at the same time or to the same degree. Thus, species selection and definition of targeted objectives is critical when growing cover crops. The goal of the current work was to describe the traits that determine the suitability of five species (barley, rye, triticale, mustard and vetch) for cover cropping. A field trial was established during two seasons (October to April) in Madrid (central Spain). Ground cover and biomass were monitored at regular intervals during each growing season. A Gompertz model characterized ground cover until the decay observed after frosts, while biomass was fitted to Gompertz, logistic and linear-exponential equations. At the end of the experiment, carbon (C), nitrogen (N), and fibre (neutral detergent, acid and lignin) contents, and the N fixed by the legume were determined. The grasses reached the highest ground cover (83-99%) and biomass (1226-1928 g/m(2)) at the end of the experiment. With the highest C:N ratio (27-39) and dietary fibre (527-600 mg/g) and the lowest residue quality (similar to 680 mg/g), grasses were suitable for erosion control, catch crop and fodder. The vetch presented the lowest N uptake (24 and 07 g N/m(2)) due to N fixation (98 and 16 g N/m(2)) and low biomass accumulation. The mustard presented high N uptake in the warm year and could act as a catch crop, but low fodder capability in both years. The thermal time before reaching 30% ground cover was a good indicator of early coverage species. Variable quantification allowed finding variability among the species and provided information for further decisions involving cover crop selection and management.
Animal slurry is separated in order to avoid excessive nitrogen, phosphorus and potassium (NPK) fertilization of crops in the field. To enhance fertilizer efficiency further, slurry and its separation products may be acidified, for instance in animal houses. The current study quantified the effects of these treatments, both individually and in combination, on fertilizer efficiency, energy production and heavy metal accumulation as a result of manure management. Acidification increased the availability of N to plants in the manure applied, and provided a better match between plant-available NPK in the manure and separation fraction applied to fields and crop need. Total biogas production was not affected by separation, whereas acidification reduced biogas production because the process was inhibited by a low pH and a high sulphur concentration. The amount of copper applied per hectare in the liquid manure to the wheat field was lower than the amount taken up and more zink and copper was applied in the solid fraction to maize field than taken up. The transportation and field application of solids and liquids did not increase management costs when compared to the transportation of slurry alone, but the investment and running costs of separators and manure acidification increased overall management costs.
A study was carried out in the rainy seasons of 2008 and 2009 in Niger to investigate the effects of fertilizer micro-dosing on root development, yield and soil nutrient exploitation of pearl millet. Different rates of diammonium phosphate (DAP) were applied to the soil at different depths and it was found that although micro-dosing with DAP increased grain yield over the unfertilized control to a similar level as broadcast DAP, doubling the micro-dosage did not increase it further. Increasing the depth of fertilizer application from 5 to 10 cm resulted in significant increases in root length density, and deep application of fertilizer resulted in higher yields, although the increases were generally not significant. It was postulated that the positive effect of micro-dosing resulted from better exploitation of soil nutrients because of the higher root volume. Levels of nutrients exported from the soil were at least as high in plants receiving micro-dosing as the unfertilized control, and plants receiving micro-dosing exported 5-10 times more phosphorus from the soil than the amount added through fertilization.
Findings from multi-year, multi-site field trial experiments measuring maize yield response to inoculation with the phosphorus-solubilizing fungus, Penicillium bilaiae Chalabuda are presented. The main objective was to evaluate representative data on crop response to the inoculant across a broad set of different soil, agronomic management and climate conditions. A statistical analysis of crop yield response and its variability was conducted to guide further implementation of a stratified trial and sampling plan. Field trials, analysed in the present study, were conducted across the major maize producing agricultural cropland of the United States (2005-11) comprising 92 small (with sampling replication) and 369 large (without replication) trials. The multi-plot design enabled both a determination of how sampling area affects the estimation of maize yield and yield variance and an estimation of the ability of inoculation with P. bilaiae to increase maize yield. Inoculation increased maize yield in 66 of the 92 small and 295 of the 369 large field trials (within the small plots, yield increased significantly at the 95% confidence level, by 0.17 +/- 0.044 t/ha or 1.8%, while in the larger plots, yield increases were higher and less variable (i.e., 0.33 +/- 0.026 t/ha or 3.5%). There was considerable inter-annual variability in maize yield response attributed to inoculation compared to the un-inoculated control, with yield increases varying from 0.7 +/- 0.75 up to 3.7 +/- 0.73%. No significant correlation between yield response and soil acidity (i.e., pH) was detected, and it appears that pH reduction (through organic acid or proton efflux) was unlikely to be the primary pathway for better phosphorus availability measured as increased yield. Seed treatment and granular or dribble band formulations of the inoculant were found to be equally effective. Inoculation was most effective at increasing maize yield in fields that had low or very low soil phosphorus status for both small and large plots. At higher levels of soil phosphorus, yield in the large plots increased more with inoculation than in the small plots, which could be explained by phosphorus fertilization histories for the different field locations, as well as transient (e.g., rainfall) and topographic effects.
The latest Common Agricultural Policy (CAP) reforms could bring substantial changes to Scottish farming communities. Two major components of this reform package, an introduction of environmental measures into the Pillar 1 payments and a move away from historical farm payments towards regionalized area payments, would have a significant effect on altering existing support structures for Scottish farmers, as it would for similar farm types elsewhere in Europe where historic payments are used. An optimizing farm-level model was developed to explore how Scottish beef and sheep farms might be affected by the greening and flat rate payments under the current CAP reforms. Nine different types of beef and sheep farms were identified and detailed biophysical and financial farm-level data for these farm types were used to parameterize the model. Results showed that the greening measures of the CAP did not have much impact on net margins of most of the beef and sheep farm businesses, except for 'Beef Finisher' farm types where the net margins decreased by 3%. However, all farm types were better off adopting the greening measures than not qualifying for the greening payments through non-compliance with the measures. The move to regionalized farm payments increased the negative financial impact of greening on most of the farms but it was still substantially lower than the financial sacrifice of not adopting greening measures. Results of maximizing farm net margin, under a hypothetical assumption of excluding farm payments, showed that in most of the mixed (sheep and cattle) and beef suckler cattle farms the optimum stock numbers predicted by the model were lower than actual figures on farm. When the regionalized support payments were allocated to each farm, the proportion of the mixed farms that would increase their stock numbers increased whereas this proportion decreased for beef suckler farms and no impact was predicted in sheep farms. Also under the regionalized support payments, improvements in profitability were found in mixed farms and sheep farms. Some of the specialized beef suckler farms also returned a profit when CAP support was added.
The high environmental costs of raising livestock are now widely appreciated, yet consumption of animal-based food items continues and is expanding throughout the world. Consumers' ability to distinguish among, and rank, various interchangeable animal-based items is crucial to reducing environmental costs of diets. However, the individual environmental burdens exerted by the five dominant livestock categories - beef, dairy, poultry, pork and eggs - are not fully known. Quantifying those burdens requires splitting livestock's relatively well-known total environmental costs (e.g. land and fertilizer use for feed production) into partial categorical costs. Because such partitioning quantifies the relative environmental desirability of various animal-based food items, it is essential for environmental impact minimization efforts to be made. Yet to date, no such partitioning method exists. The present paper presents such a partitioning method for feed production-related environmental burdens. This approach treated each of the main feed classes individually - concentrates (grain, soy, by-products; supporting production of all livestock), processed roughage (mostly hay and silage) and pasture - which is key given these classes' widely disparate environmental costs. It was found that for the current US food system and national diet, concentrates are partitioned as follows: beef 0.21 +/- 0.112, poultry 0.27 +/- 0.046, dairy 0.24 +/- 0.041, pork 0.23 +/- 0.093 and eggs 0.04 +/- 0.018. Pasture and processed roughage, consumed only by cattle, are 0.92 +/- 0.034 and 0.87 +/- 0.031 due to beef, with the remainder due to dairy. In a follow-up paper, the devised methodology will be employed to partition total land, irrigated water, greenhouse gases and reactive nitrogen burdens incurred by feed production among the five edible livestock categories.
The prenatal period is of critical importance in defining how individuals respond to their environment throughout life. Stress experienced by pregnant females has been shown to have detrimental effects on offspring behaviour, health and productivity. The sheep has been used extensively as a model species to inform human studies. However, in the farmed environment, the consequences for the lamb of the imposition of prenatal stresses upon the ewe have received much less attention. The stressors that pregnant ewes are most frequently exposed to include sub-optimal nutrition and those related to housing, husbandry and environment which may be either acute or chronic. A systematic review of the literature was adopted to identify material which had production-relevant maternal stressors and lamb outcomes. The current review focussed upon the lamb up to weaning around the age of 100 days and the results clearly demonstrate that stressors imposed upon the ewe have implications for offspring welfare and performance. Maternal under-nutrition (UN) in the last third of pregnancy consistently impaired lamb birth-weight and subsequent vigour and performance, while earlier UN had a variable effect on performance. Feeding the ewe above requirements did not have positive effects on lamb performance and welfare. Social and husbandry stressors such as transport, shearing, mixing and physiological treatments designed to mimic acute stress which would be considered disadvantageous for the ewe had positive or neutral effects for the lamb, highlighting a potential conflict between the welfare of the ewe and her lamb. This review also identified considerable gaps in knowledge, particularly in respect of the impact of disease upon the ewe during pregnancy and interactions between different stressors and the responses of ewe and lamb.
Selenium (Se) is an essential micronutrient for human and animal health. Globally, more than one billion people are Se deficient due to low dietary Se. Low dietary intake of Se can be improved by Se supplementation, food fortification and biofortification of crops. Lentil (Lens culinaris Medikus subsp. culinaris) is a popular cool-season food legume in many parts of the world; it is naturally rich in Se and therefore has potential for Se biofortification. An Se foliar application experiment at two locations and a multi-location trial of 12 genotypes at seven locations were conducted from April to December 2011 in South Australia and Victoria, Australia. Foliar application of a total of 40 g/ha of Se as potassium selenate (K2SeO4) - 10 g/ha during full bloom and 30 g/ha during the flat pod stage - increased seed Se concentration from 201 to 2772 mu g/kg, but had no effect on seed size or seed yield. Consumption of 20 g of biofortified lentil can supply all of the recommended daily allowance of Se. After Se foliar application, cultivars PBA Herald XT (3327 mu g/kg), PBA bolt (3212) and PBA Ace (2957 mu g/kg) had high seed Se concentrations. These cultivars may be used in lentil biofortification. In the genotypic evaluation trial, significant genotype and location variation was observed for seed Se concentration, but the interaction was not significant. In conclusion, foliar application of Se as K2SeO4 is an efficient agronomic approach to improve seed Se concentration for lentil consumers and there is also scope for genetic biofortification in lentil.
Due to the potential impact of climate change and climate variability on rainfed production systems, both farmers and policy makers will have to rely more on short- and long-term yield projections. The goal of this study was to develop a procedure for calibrating the Cropping System Model (CSM)-CROPGRO-Soybean model for six cultivars, to determine the potential impact of climate change on rainfed soybean for five locations in Georgia, USA, and to provide recommendations for potential adaptation strategies for soybean production in Georgia and other south-eastern states. The Genotype Coefficient Calculator (GENCALC) software package was applied for calibration of the soybean cultivar coefficients using variety trial data. The root mean square error (RMSE) between observed and simulated grain yield ranged from 201 to 413 kg/ha for the six cultivars. Generally, the future climate scenarios showed an increase in temperature which caused a decrease in the number of days to maturity for all varieties and for all locations. This will benefit late-planted soybean production slightly, while the increase in precipitation and carbon dioxide (CO2) concentration will result in a yield increase. This was the highest for Calhoun and Williamson and ranged from 31 to 49% for the climate change projections for 2050. However, a large reduction in precipitation caused a decrease in yield for Midville, especially based on the climate scenarios of the Global Climate Models (GCMs) Commonwealth Scientific and Industrial Research Organisation's model CSIRO-Mk3.0 and Geophysical Fluid Dynamics Laboratory's model GFDL-CM2.1. Overall, Calhoun, Williamson, Plains and Tifton will probably be more suitable for rainfed soybean production over the next 40 years than Midville. Farmers might shift to a later planting date, around 5 June, for the locations that were evaluated in the present study to avoid potential heat and drought stress during the summer months. The cultivars AG6702, AGS758RR and S80-P2 could be selected for rainfed soybean production since they had the highest rainfed yields among the six cultivars. In general, the present study showed that there are crop management options for soybean production in Georgia and the south-eastern USA that are adapted for the potential projected climate change conditions.
Climate risk assessment in cropping is generally undertaken in a top-down approach using climate records while critical farmer experience is often not accounted for. In the present study, set in south India, farmer experience of climate risk is integrated in a bottom-up participatory approach with climate data analysis. Crop calendars are used as a boundary object to identify and rank climate and weather risks faced by smallhold farmers. A semi-structured survey was conducted with experienced farmers whose income is predominantly from farming. Interviews were based on a crop calendar to indicate the timing of key weather and climate risks. The simple definition of risk as consequence x likelihood was used to establish the impact on yield as consequence and chance of occurrence in a 10-year period as likelihood. Farmers' risk experience matches well with climate records and risk analysis. Farmers' rankings of 'good' and 'poor' seasons also matched up well with their independently reported yield data. On average, a 'good' season yield was 1.5-1.65 times higher than a 'poor' season. The main risks for paddy rice were excess rains at harvesting and flowering and deficit rains at transplanting. For cotton, farmers identified excess rain at harvest, delayed rains at sowing and excess rain at flowering stages as events that impacted crop yield and quality. The risk assessment elicited from farmers complements climate analysis and provides some indication of thresholds for studies on climate change and seasonal forecasts. The methods and analysis presented in the present study provide an experiential bottom-up perspective and a methodology on farming in a risky rainfed climate. The methods developed in the present study provide a model for end-user engagement by meteorological agencies that strive to better target their climate information delivery.
There is little empirical evidence to indicate that dairy cow live weight affects the extent of soil damage at the hoof-soil interface during grazing on poorly drained permanent grassland. In the present study the impact of Holstein-Friesian (HF) dairy cows with a mean (+/- standard deviation) live weight of 570 (+/- 61) kg were compared with Jersey x Holstein-Friesian (JX) with a mean live weight of 499 (+/- 52) kg each at two stocking densities: mean 2.42 +/- (0.062) and 2.66 (+/- 0.079) cows/ha. Soil physical properties (bulk density, macroporosity, gravimetric water content, air-filled porosity, penetration resistance and shear strength), poaching damage (post-grazing soil surface deformation and hoof-print depth), herbage yield and milk production were measured throughout 2011 and 2012. Soil physical properties, post-grazing soil surface deformation and herbage production were not affected by dairy cow breed or by interactions between breed and stocking density. Hoof-print depth was higher in the HF treatments (39 v. 37 mm, S.E. 0.5 mm). Loading pressure imposed at the soil surface was the same for both breeds due to a direct correlation between live weight and hoof size. Poaching damage was greater at higher stocking density. Using the lighter JX cow offered little advantage in terms of lowering the negative impact of treading on soil physical properties or reducing poaching damage and no advantage in terms of herbage or milk production compared with the heavier HF cow.
There is an increasing interest in pasture-based dairy systems in Europe, mainly because of increasing production costs for intensive dairying. Milk is a matrix of compounds that influence nutritional and manufacturing properties, many dependent on husbandry linked to pasture-based systems (increase in pasture intake, forage : concentrate ratio, clover inclusion in swards/silages and use of alternative dairy breeds). The present study investigated the impact of three grazing-based dairy systems with contrasting feeding intensity or reliance on pasture intakes (conventional high-intensity, low pasture intake [CH], organic medium-intensity, medium pasture intake [OM], conventional low-intensity, high pasture intake [CL]) on milk fatty acid (FA) profiles, protein composition and alpha-tocopherol and antioxidants concentrations. The proportion of animals of alternative breeds (e.g. Jersey) and crossbred cows in the herd increased with decreasing production intensity (CH < OM< CL). Milk constituents known to be beneficial for human health, such as vaccenic acid, rumenic acid, monounsaturated FA, polyunsaturated FA, antioxidants and caseins, were elevated with decreasing production intensity (CH < OM< CL), while less desirable saturated FA were lower, although not all differences between OM and CL were significant. Omega-3 FA were maximized under OM practices, primarily as a result of higher clover intake. Increases in pasture intake may explain the higher concentrations of desirable FA while increased use of crossbreed cows is likely to be responsible for higher total protein and casein content of milk; a combination of these two factors may explain increased antioxidant levels. The higher concentrations of vaccenic acid, rumenic acid, omega-3 FA, lutein, zeaxanthin, protein and casein in OM and CL milk were found over most sampling months and in both years, reinforcing the higher nutritional quality and manufacturing properties associated with milk from these systems. A switch to pasture-based dairy products would increase the intake of milk's beneficial compounds and reduce consumption of less desirable saturated FA.
The extent to which markers have been used in chickpea breeding programmes has not been clearly determined. In the current study, phenotypic and marker-assisted selection (MAS) were employed to select blight resistant genotypes, comparing the effectiveness of both methods. The phenotypic evaluation showed that the resistance could be recessive in the material employed. However, the high distorted segregation towards the susceptible parent detected on linkage group four (LG4) could also explain the phenotype distribution of resistance. Phenotypic selection in F-2:4 and F-2:5 generations lead to an increase in the frequency of the allele associated with the resistance of the markers CaETR and GAA47, indicating the usefulness of these markers for MAS. The markers TA72 and SCY17 could be also useful for MAS but the high distorted segregation towards the susceptible parent in the region where these markers are located could explain their low effectiveness. The costs associated with phenotypic selection and MAS for ascochyta blight resistance during three cycles of selection are presented in the current study, showing that MAS was more expensive than phenotypic selection. Nevertheless, the use of markers reduced the time taken to select resistant lines. The markers analysed in the current study were useful to select genotypes resistant to ascochyta blight in chickpea breeding programmes, allowing pyramiding genes or quantitative trait loci (QTL) related to different pathotypes. It is recommended that MAS should be employed in early generations of chickpea breeding programmes for the four QTL analysed because this makes it possible to develop populations with a high frequency of the favourable alleles conferring resistance to blight.
Most crop models make use of a nutrient-balance approach for modelling crop response to soil fertility. To counter the vast input data requirements that are typical of these models, the crop water productivity model AquaCrop adopts a semi-quantitative approach. Instead of providing nutrient levels, users of the model provide the soil fertility level as a model input. This level is expressed in terms of the expected impact on crop biomass production, which can be observed in the field or obtained from statistics of agricultural production. The present study is the first to describe extensively, and to calibrate and evaluate, the semi-quantitative approach of the AquaCrop model, which simulates the effect of soil fertility stress on crop production as a combination of slower canopy expansion, reduced maximum canopy cover, early decline in canopy cover and lower biomass water productivity. AquaCrop's fertility response algorithms are evaluated here against field experiments with tef (Eragrostis tef (Zucc.) Trotter) in Ethiopia, with maize (Zea mays L.) and wheat (Triticum aestivum L.) in Nepal, and with quinoa (Chenopodium quinoa Willd.) in Bolivia. It is demonstrated that AquaCrop is able to simulate the soil water content in the root zone, and the crop's canopy development, dry above-ground biomass development, final biomass and grain yield, under different soil fertility levels, for all four crops. Under combined soil water stress and soil fertility stress, the model predicts final grain yield with a relative root-mean-square error of only 11-13% for maize, wheat and quinoa, and 34% for tef. The present study shows that the semi-quantitative soil fertility approach of the AquaCrop model performs well and that the model can be applied, after case-specific calibration, to the simulation of crop production under different levels of soil fertility stress for various environmental conditions, without requiring detailed field observations on soil nutrient content.