Dairy Systems Research Articles

Animal factors that affect enteric methane production measured using the GreenFeed monitoring system in grazing dairy cows

Similar to all dairy systems internationally, pasture-based dairy systems are under increasing pressure to reduce their greenhouse gas (GHG) emissions. Ireland and New Zealand are 2 countries operating predominantly pasture-based dairy production systems where enteric CH4 contributes 23% and 36% of total national emissions, respectively. Ireland currently has a national commitment to reduce 51% of total GHG emissions by 2030 and 25% from agriculture by 2030, as well as striving to achieve climate neutrality by 2050. New Zealand's national commitment is to reduce 10% of methane emissions by 2030 and between 24% and 47% reduction in methane emissions by 2050. To achieve these reductions, factors that affect enteric methane (CH4) production in a pasture-based system need to be investigated. The objective of this study was to assess the relationship between enteric CH4 and other animal traits (feed intake, metabolic liveweight, energy corrected milk yield, milk urea concentration, and body condition score [BCS]) in a grazing dairy system. Enteric CH4 emissions were measured on 45 late lactation (213.8 ± 29 d after calving) grazing Holstein-Friesian and Holstein-Friesian × Jersey crossbred cows (lactation number 3.01 ± 1.65, 538.64 ± 59.37 kg live weight, and 3.14 ± 0.26 BCS) using GreenFeed monitoring equipment for 10 wk. There was a training period for the cows to use the GreenFeed of 3 wk before the 10-wk study period. The average enteric CH4 produced in the study was 352 g ± 45.7 g per day with an animal to animal coefficient of variation of 13%. Dry matter intake averaged 16.6 kg ± 2.23 kg per day, while milk solids (fat plus protein) averaged 1.62 kg ± 0.29 kg per day. A multiple linear regression model indicated that each one unit increase in energy corrected milk yield, metabolic liveweight and milk urea concentration, resulted in an increase in enteric CH4 production per day by 3.9, 1.74, and 1.38 g, respectively. Although each one unit increase in BCS resulted in a decrease in 39.03 g CH4 produced per day. When combined, these factors explained 47% of the variation in CH4 production, indicating that there is a large proportion of variation not included in the model. The repeatability of the CH4 measurements was 0.66 indicating that cows are relatively consistently exhibiting the same level of CH4 throughout the study. Therefore, enteric CH4 production is suitable for phenotyping.

Marginal increase in nitrate leaching under grass–clover leys by slurry and mineral fertilizer

AbstractOn dairy farms, fertilization of grass-clover swards ensures stable grass yields but may increase the potential for nitrate leaching on light-textured soils. The aim of this study was to quantify the N use efficiency and nitrate leaching under fertilized grass-clover leys. The study was conducted over 2 years at two sites, with increasing applications of mineral fertilizer (0–480 kg available N ha−1) alone or in combination with a basic application of cattle slurry. For plots fertilized with mineral N, the N soil surface balance was independent of the application rate and in the same range as for unfertilized plots (− 11 to 51 kg N ha−1). However, when plots were fertilized with slurry N (+ mineral N), the surplus was substantially increased owing to the fraction of organic N applied in slurry (95–100 kg N ha−1) and higher biological N2 fixation inputs (55–228 kg N ha−1). The type of fertilizer had no effect on nitrate leaching across the full range of application rates. Nitrate leaching increased quadratically as a function of application rate, with a range of 3–117 kg N ha−1 (0.33–17 mg l−1 in soil solution sampled with suction cups) in the first year and less in the second year, when clover proportion was lower due to the self-regulatory nature of grass-clover mixtures. Importantly, the rate of marginal leaching increased with fertilization level: below 150 kg N ha−1 there was no additional leaching from fertilization and at 200 kg N ha−1 around 5% of additional fertilizer-N was leached. This is less than generally found for arable crops and thus even in intensive dairy systems, grass-clover leys are an environmentally favorable crop.

Incorporating plantain into ryegrass-white clover mixed sward for an economically and environmentally sustainable dairy system: Year one of a farm system study

The objective of this replicated farm system study was to investigate the effect of increasing proportion of plantain (Plantago lanceolata L. cv. Ecotain) in a perennial ryegrass/white clover (RGWC) mixed sward on farm productivity, profitability and environmental footprint over the 2021/22 production season. A total of 108 dairy cows were blocked into nine herds of 12 cows.The herds were randomly allocated into one of three replicated pasture treatments sown with an increasing plantain seed rate: (i) RGWC with nil plantain (PL0); (ii) RGWC+3 kg/ha plantain seed rate (PL3) or (iii) RGWC+6 kg/ha plantain seed rate (PL6). Farmlet milkand pasture production were measured, and data was used to estimate farm profitability and environmental footprint using FARMAX and OverseerEd software, respectively. Increasing plantain seed rate from 3 to 6 kg/ha increased sward content of plantain from24% to 34% of DM in PL3 and PL6, respectively. Pasture production (average 12,988±473 kg DM/ha), total milksolids production (1,356±40 kg/ha) and farm profitability (4,347±354 NZ$/ha) were similar amongst treatments. Compared to PL0, estimated annual nitrogen leaching and nitrous oxide emissions were reduced by 21% and 30%, (P<0.001) and 4.3% and 6.0% (P<0.01) in PL3 and PL6, respectively. Results suggest that incorporation of plantain into dairy systems could be used as a strategy to reduce predictedenvironmental footprint while maintaining profitability. However, these results need to be confirmed over multiple production seasons.

Stacking nitrogen leaching mitigations in a Canterbury dairy system whilst minimising profitability losses.

The aim of this project was to model combinations (“stacks”) of cost-effective nitrogen (N) leaching mitigations within a dairy system that could reduce N leaching by 40-60%, whilst minimising losses in profitability. A FARMAX and OverseerFM combination was used to model a baseline farm representing a typical Canterbury system, and seven sequentially “stacked” mitigated systems. The mitigations were combined and stacked in the following order based on mechanism(s) of action, practicality, and cost-effectiveness: 1) reduced synthetic N fertiliser input (from 190 to 100 kg N/ha/year); 2) including Italian ryegrass in the pasture sward; 3) including plantain in the pasture sward; 4) earlier calving and drying off (by 10 days); 5) wintering on pasture and baleage; 6) standing cows off-pasture;7) using new-generation nitrification inhibitors. The most cost-effective stack combined mitigations 1 to 5. We estimated that N leaching was reduced by 57% relative to baseline, with an 8% reduction in operating profit. Greenhouse gas emissions were reduced by 8%. The largest single reduction in N leaching was from stack #5, and it coincided with no/little change in milk production pasture eaten and had no capital cost. A careful selection of complementary mitigations could achieve significant reductions in N leaching without compromising greenhouse gas emissions and, to any great extent, profitability.

Fodder beet: know what you are feeding for a nutritionally balanced diet for dairy cattle

Fodder beet’s (FB) high soluble sugar and low crude protein content provide environmental benefits but also nutritional challenges, making it a unique crop in New Zealand dairy systems. Knowledge of dietary nutrient content is important to inform both mineralsupplementation and type of supplementary feed to offer. This will help ensure nutritional requirements for dairy cows are met, maximising the likelihood of positive outcomes for animal health and production. A database containing 694 samples of FB leaf andbulb tissue was compiled from monitor farm data, research projects, and cultivar evaluation trials with the objective of determining the variability in nutritional content. Descriptive statistics were used to highlight the range and variability in FB leaf and bulb nutritional composition between regions and cultivars. Our results reinforce that FB bulbs (which usually make up 70- 90% of the crop DM) are typically low in crude protein, fibre, phosphorus, calcium, and sulphur, but are high in soluble sugars. The variation in nutrient content between cultivars, and within cultivars both between and within regions shown in this study highlights the importance of paddock-specific feed analyses, and the limitations of textbook values, particularly whole crop values which do not differentiate between bulb and the more nutritionally valuable leaf.

Co-benefits and trade-offs of water quality mitigation measures on greenhouse gas emissions from New Zealand dairy systems

As part of government climate change policy, New Zealand dairy farmers will be encouraged to reduce their greenhouse gas (GHG) emissions through a proposed pricing mechanism. With integrated farm plans on the horizon, farmers need information on how mitigations for water quality will impact GHG emissions. Using a typology approach that captured the main production attributes and drivers of nitrogen (N) and phosphorus (P) losses to water we assessed the impact of 12 current N and P contaminant mitigations on GHG co-benefits or trade-offs. Four of the mitigations had a co-benefit effect, with most of these being N mitigation measures.Trade-offs were detected for two water quality mitigations (stand-off pads and deferring effluent application), resulting in an increase in estimated GHG emissions. The remaining six water quality mitigations tested, either had a minimal impact, or had both a tradeoffand co-benefit. Our data provides pastoral farmers and rural professionals with information to guide initial conversations on options to reduce losses to water and air for developing integrated farm plans

Trade-offs between higher productivity and lower environmental impacts for biodiversity-friendly and conventional cattle-oriented systems

CONTEXTBiodiversity loss caused by livestock production is a key environmental issue. Biodiversity-friendly livestock systems aim to favour biodiversity mainly for its own sake. Environmental impacts of biodiversity-friendly livestock systems have not been studied, nor have trade-offs between higher productivity and lower environmental impacts of these systems. OBJECTIVEThis study aimed to (i) assess the productivity and environmental impacts of a sample of cattle-oriented production systems representing a wide range of external inputs, productivity and consideration of biodiversity; (ii) identify trade-offs among the objectives of lower input use, higher productivity, lower environmental impacts and higher energy return on investment (EROI); (iii) relate the systems' production strategies to the trade-offs identified and (iv) identify perspectives for biodiversity-friendly livestock systems. METHODSThis study assessed the productivity and environmental impacts of a sample of seven cattle-oriented production systems: an agricultural rewilding system (biodiversity-friendly, in England), three suckler beef systems (two of them considered biodiversity-friendly, in France) and three dairy systems (one biodiversity-friendly and one conventional, in France). Life cycle assessment (LCA) was applied to assess six environmental impacts (i.e. terrestrial acidification, freshwater eutrophication, marine eutrophication, land occupation, and in particular, climate change and energy demand) and was combined with calculation of EROI. RESULTS AND CONCLUSIONSPer hectare of land occupied to produce livestock and their feed, production of human-edible animal protein and environmental impacts of these systems increased as energy demand (i.e. input use) increased. Per hectare, human-edible animal protein production, energy demand and climate change impact (considering carbon dynamics) ranged from 5 kg, 90 MJ and −5.5 t CO2-eq., respectively, for the agricultural rewilding system to 239 kg, 20,496 MJ and 8.3 t CO2-eq., respectively, for the conventional French dairy farm. Patterns of trade-offs varied among the production strategies of the farms. The four biodiversity-friendly farms in the sample had low productivity but also low environmental impacts per ha, especially for climate change and energy demand, due to being extensive systems with relatively high self-sufficiency. Biodiversity-friendly farms also had higher EROI than other farms that produced the same products. Using LCA to assess biodiversity-friendly systems, in particular agricultural rewilding, challenges its ability to consider natural baseline emissions and non-provisioning ecosystem services. SIGNIFICANCEThese results emphasise the need to consider the multiple functions of these systems and their overall environmental performances and sustainability. Current economic and social trends may provide opportunities for biodiversity-friendly livestock systems as a possible future for livestock systems.

Prevalence of lameness on pasture-based New Zealand dairy farms: An observational study.

To understand the current impact of lameness on a system, it is important to define lameness prevalence across a range of dairy farms in that system. Prevalence estimates from dairy systems where cows are permanently managed at pasture are uncommon, although the limited data suggest that they have a lower lameness prevalence than housed cattle. One hundred and 20 farms from eight of the major dairying regions of New Zealand were randomly enrolled into a cross-sectional lameness prevalence study. On each of the farms, trained observers lameness scored cattle on two occasions, between October-December (spring, coinciding with peak lactation for most farms) and between January-March (summer, late lactation for most farms). At each visit, all lactating animals were scored using a four-point 0-3 scoring system, and included animals that had previously been identified as lame by the farmer. Animals with a lameness score (LS) ≥2 were defined as lame. Mixed logistic regression models assessed the interaction between region and season and island and season, respectively, and differences between the lameness prevalence within farm across the two seasons reported descriptively. A total of 116,317 locomotion scores over two events were conducted across the 120 farms. At the spring scoring event, 2128/60,007 (3.5 %) cows had a LS ≥2 and 1868/56,310 (3.3 %) cows had a LS ≥2 at the summer scoring event. At the farm level, across both scoring events, median lameness prevalence was 2.8 (interquartile range 1.5 - 4.5) %, with a range of 0.0-17.0 %. The median farm-level prevalence of LS=3 was 0.5 % with a range of 0-4.6 %. The effect of timing of scoring was modified by region (p<0.001), and island (p=0.006) and at the individual farm level, differences between spring and summer farm level lameness prevalence were generally small (interquartile range: -1.8 to 1.0 %) but potentially large on individual farms (range from-12.3 % to 7.6 %). The median farm-level lameness prevalence estimate of 2.8 % across a random representative sample of New Zealand dairy farms give confidence that the overall prevalence of cattle lameness on New Zealand dairy farms is low. This adds to the growing evidence that pasture is a good management system with respect to hoof health. The evidence of strong seasonality of lameness was lacking. Instead of using lameness scoring to identify farms with large lameness problems, lameness scoring should be encouraged to farmers as a tool to improve the identification of lame animals.

Exploring policy options to transform traditional dairy system in Ethiopia: A system dynamics approach

Despite having a larger herd size and a favourable climate, Ethiopia generally lags behind developing nations in terms of both production and consumption of dairy products. For the purpose of finding and assessing ways to increase milk production by the traditional dairy system in Ethiopia's West Shewa zone, we integrated system dynamics (SD) modelling with a participatory model building approach. The main objective of the research was to develop SD model for West Shewa dairy value chain and apply it to assess ex-ante milk production and dairy household profit impacts of various interventions. The interventions evaluated in the study include enhanced urea treatment of crops residue, increased production of improved feed, and investment in more dairy cows. Analysis reveals that policies targeting feed development can boost milk production and household profits above the baseline. They also lead to a higher seasonal variability in milk production. Through the feed development strategy producers can achieve a 70 % and 735 % increase in milk production and household profit, respectively. However, the implementation of improved feed policy still leaves a gap in the average feed protein requirement of a dairy cattle in the study area. On the other hand, policy of increasing cow herd is not profitable. In addition, improved feed policy in drought results in reduced herd size, yet it leads to a higher milk output and household profit. Hence, with the feed development options explored in this study, increasing herd size is not a recommended course of action for improvement of the West Shewa dairy value chain. Therefore, future research should explore for further enhancement of the supply as well as quality of feed resources and the potential of investment in improved breeds.

On the Deadliness of Specialized Dairy Production – The Case of Jersey Herds in Switzerland

Abstract The jointness of milk and beef production is still the dominant system but is challenged by the trend toward vegetarian diets that skip meat but not milk consumption. Specialized dairy production raises issues regarding the management of male animals that are better known from the case of egg production but which are yet to be explored for dairy herds. In a first step, the problem of male chicklets is presented; similarities and differences to dairy systems are highlighted. A dataset of Swiss cattle is used to show that specialized dairy production as indicated by Jersey cows leads to a shorter life expectancy of both newborn calves and dairy cows compared to the joint production of milk and meat. In a qualitative part, the unsolved problem of economic waste through all male animals and the female animals not needed for milk production is illustrated by using the method of objective hermeneutics. It can be concluded that specialized dairy production does not benefit farm animals.

Optimal Age at First Calving in Pasture-Based Dairy Systems

The age at first calving (AFC) is one of the most used indicators to evaluate the efficiency of rearing systems in dairy herds. The objective of the present study was to evaluate the association between AFC and different parameters of productive and reproductive efficiency in dairy cows of Holstein and Jersey breeds and their crosses, reared under pasture-based conditions. A retrospective longitudinal study was carried out with information on the performance of 77,311 cows with birth and culling dates between 1990 and 2016 from 654 specialized dairy herds located in mid and high-altitude regions of Costa Rica. Cows were classified into five classes according to their age in months at first calving (≤24, 25–27, 28–30, 31–33, ≥34). A generalized linear mixed model was used to assess the effect of AFC and breed factors on milk production (first lactation, lifetime total, and per day of life), open period (first calving and lifetime total), and herd life. The mean AFC was 29.5, 29.1, and 28.0 months for Holstein, Holstein × Jersey, and Jersey, respectively. The AFC was significantly associated (p &lt; 0.01) with all the variables evaluated. Cows with AFC ≤ 24 presented a higher (p &lt; 0.01) milk production (total lifetime and per day of life), as well as a longer herd life, compared to cows in classes of AFC &gt; 28 m. The reduction in AFC contributes to a significant increase in the production and reproduction efficiency of pasture-based dairy herds. This effect was consistent across the three breed groups.

Can the inclusion of ribwort plantain or chicory increase the seasonal and annual dry matter production of intensive dairy grazing swards?

Pasture species complementarity leading to increased dry matter (DM) production has been observed in multispecies (MS) swards which include legumes and forage herbs along with grasses. This effect has been measured in mechanically defoliated plots with little data available from grazing scenarios. There is a scarcity of data available regarding individual forage herb species contribution to increased sward DM production where only plant functional group has been monitored previously. The objective of this three year study was to assess the DM production, N fertiliser response and change of botanical composition in grazed plots across nine MS sward mixtures compared to a PRG monoculture. Multispecies swards included various combinations of species from the three plant functional groups; N fertiliser treatments of 0, 100, 150 and 200 kg N/ha/year were applied. While year influenced the effect of sward mixture on annual DM production, swards that included white clover (Trifolium repens. L.) produced an average of 1688 kg DM/ha/year more than those which did not (P < 0.05); including forage herbs did not increase either annual or seasonal sward DM production. In the final year of the study sward chicory (Chicorium intybus. L.) content was 5% in mixtures including three plant functional groups while ribwort plantain (Plantago lanceolate. L.; PL) content was 37% in the same sward types. Although PL did not increase grazed sward DM production in the current study it did persist well under grazing and may provide other beneficial ecosystem services in dairy grazing systems.

New Zealand dairy farm system solutions that balance reductions in nitrogen leaching with profitability – a case study

ABSTRACT This study tested prescribed management practices to reduce nitrogen (N) leaching by 20% while maintaining or improving profitability relative to an existing farm management baseline (Control). N leaching and profitability were estimated for a South Canterbury case study dairy farm using Overseer® Nutrient Budgets and FARMAX Dairy. Three practices were used: (1) reducing N in cows’ diets through low-N feed (fodder beet), (2) recapturing N from soils through catch crops (oats) and (3) diluting urinary N by including plantain in cows’ diet. While most treatments reduced N leaching, significant management inputs were required to achieve a 20% reduction from the Control. Plantain was identified as the key forage for reducing N leaching from the milking platform. Fodder beet and oats had little impact, due to the small area cropped on the milking platform and low dietary substitution. However, they increased profitability relative to the Control. Only one scenario, employing all three forages with biannual direct drilling of plantain, achieved the target, reducing N leaching by 27% and increasing profitability by 2% compared with the Control. The implications of this modelling study for real-life application are that a combination of measures will be needed to achieve large environmental and economic targets.

A Monoblock Light-Scattering Milk Fat Percentage and Somatic Cell Count Sensor for Use in Milking Systems.

A monoblock light-scattering sensor, which is capable of measuring the fat content of milk and indicating the excess by which the somatic cell count (SCC) is over the permissible level, has been developed for installation in dairy systems. In order for the sensor to perform measurements when the milking machine is working in the "milk plug" mode, a flow-through unit is designed in the form of a pipe with a lateral cylindrical branch, in which milk accumulates so as to eliminate large bubbles and achieve continuity of the milk flow. The operation of the sensor is based on the registration of the angular intensity distribution of light scattered in the transparent cylindrical segment of the tube branch. A semiconductor laser with a wavelength of 650 nm is used as a light source for determining scattering in milk. The angular distribution of the scattered light intensity (scattering indicatrix) is recorded using an axial photodiode array. The fat content is determined by the average slope of the measured scattering indicatrix in the range of scattering angles 72-162°. The SCC level is estimated from the relative deviation of the forward scatter intensity normalized to the backscatter intensity with respect to uninfected milk. The sensor has been tested on a Yolochka-type milking machine.

Interactive Dairy Goat Image Segmentation for Precision Livestock Farming.

Semantic segmentation and instance segmentation based on deep learning play a significant role in intelligent dairy goat farming. However, these algorithms require a large amount of pixel-level dairy goat image annotations for model training. At present, users mainly use Labelme for pixel-level annotation of images, which makes it quite inefficient and time-consuming to obtain a high-quality annotation result. To reduce the annotation workload of dairy goat images, we propose a novel interactive segmentation model called UA-MHFF-DeepLabv3+, which employs layer-by-layer multi-head feature fusion (MHFF) and upsampling attention (UA) to improve the segmentation accuracy of the DeepLabv3+ on object boundaries and small objects. Experimental results show that our proposed model achieved state-of-the-art segmentation accuracy on the validation set of DGImgs compared with four previous state-of-the-art interactive segmentation models, and obtained 1.87 and 4.11 on mNoC@85 and mNoC@90, which are significantly lower than the best performance of the previous models of 3 and 5. Furthermore, to promote the implementation of our proposed algorithm, we design and develop a dairy goat image-annotation system named DGAnnotation for pixel-level annotation of dairy goat images. After the test, we found that it just takes 7.12 s to annotate a dairy goat instance with our developed DGAnnotation, which is five times faster than Labelme.

Different manure management methods impact on nitrogen use efficiency - comparison of four dairy farms in Hokkaido Japan

Different manure management methods impact on nitrogen use efficiency - comparison of four dairy farms in Hokkaido Japan

Chemical, Physical, and Degradation Characteristics of Ryegrass Cultivars Grown in Autumn and Winter for Dairy Cows.

During winter and early spring, pasture supply is usually lower than the demand in New Zealand dairy farming systems and thus the 'autumn saved pastures' (stockpiling) are introduced to fill the gap. This study aimed to investigate the chemical, physical, and degradation characteristics of ryegrass pastures, the predominant forage in New Zealand, grown in autumn and winter. To serve as 'autumn saved pasture', nine ryegrass cultivars, comprising three types (three perennial, three hybrid, and three Italian), were grown in late autumn (Autumn) and early winter (Winter) and harvested after 7 and 9 weeks of regrowth, respectively. The experiment had two experimental factors: ryegrass type (or cultivar) and harvest season. These experimental factors were in a randomised block design with the forage plot as the experimental unit. The degradation characteristics were assessed in the rumen of fistulated cows using the in situ incubation technique. Perennial ryegrass had a greater neutral detergent fibre (NDF) concentration (468 g/kg dry matter (DM)) than the hybrid (435 g/kg DM) or Italian (414 g/kg DM) ryegrasses. Italian ryegrasses had the greatest soluble fraction of DM (64.2% vs. 46.7% and 40.7%) and the greatest degradation rate of an insoluble but degradable fraction of DM (0.221 vs. 0.189 and 0.145/h) than the hybrid and perennial ryegrasses. Compared with the Winter ryegrass, the Autumn ryegrass had a greater crude protein concentration (246 vs. 208 g/kg DM) and a greater NDF concentration (486 vs. 392 g/kg DM) but a lower calculated soluble carbohydrate concentration (152 vs. 263 g/kg DM). It is concluded that there are notable variations among the cultivars, highlighting distinctions in parameters, such as NDF concentration, soluble fractions, degradation rates, and nutrient content among the perennial, hybrid, and Italian ryegrasses, as well as the seasonal variations observed between autumn and winter growth. These findings will not only facilitate enhanced nutrition for dairy cows as they undergo the transition phase but also have practical implications for future research and dairy cow nutrition.

Концентрированные молочные модельные системы: изменение качества в процессе низкотемпературного хранения

One of the ways to solve the problem of low storability of raw milk is the use of frozen milk concentrates. A comprehensive understanding of the impact of negative temperatures on the stability and properties of dairy systems during long-term storage and further processing is necessary to assess the potential of their use. The effect of long-term low-temperature storage on the organoleptic, physico-chemical and technological properties of concentrated model milk systems has been studied. Stability of milk systems samples was kept for 3 months, further significant stratification of consistence and formation of protein flakes were registered. Mass fractions of protein, fat, lactose, as well as titratable and active acidity did not change significantly. On the alcohol and heat samples significant changes were noted only after 6 months of storage. Based on the data obtained, the duration of storage after freezing milk systems should not exceed 3 months.

Comparing the predictive ability of Sentinel-2 multispectral imagery and a proximal hyperspectral sensor for the estimation of pasture nutritive characteristics in an intensive rotational grazing system

Using remote sensing to estimate the nutritive characteristics of pasture in livestock systems is a rapidly developing area that has the potential to improve pasture management and utilisation and in turn improve livestock productivity. The Copernicus Sentinel-2 paired satellites have shown promise in predicting pasture nutritive characteristics and have a pixel size small enough to be able to identify intra-paddock nutrient variation in rotational dairy grazing systems where paddock sizes are small. This study sought to develop nutrient prediction models using a dataset of nine Sentinel-2A and -2B satellite images, by linking imagery to perennial ryegrass dairy pasture samples cut within known pixels of the images in the days directly after each cloud-free overpass. Just before destructive pasture sampling, a handheld, proximal, hyperspectral sensor was used to gather spectral signatures (400–2500 nm) from areas to be sampled. Pasture samples (n = 200) were analysed using wet chemistry techniques for seven nutritive characteristics. The dry matter concentration of the samples was also measured, creating eight variates to be modelled in total. The Sentinel-2 data from within the selected pixels was extracted and used to create input features for Random Forest prediction models. Input features included the raw multispectral bands, common vegetation indices, and independent variables ‘season’ and ‘month’. Predictive models were also developed from the hyperspectral sensor data using Partial Least Squares Regression. For both modelling types, variable selection was used to reduce model inputs to only those sensitive to each nutrient. Results comparing the final models in an independent validation test showed similar predictive performance of the Sentinel-2 satellite and the proximal hyperspectral sensor for all variates of interest, shown by mean absolute errors that were not significantly different. In each case, the dry matter concentration was the best predicted variable (Lin’s concordance correlation coefficient (LCCC) > 0.90) with excellent potential to be quantified by Sentinel-2 satellites. Crude protein, metabolisable energy, neutral detergent fibre, non-fibre carbohydrate, and water-soluble carbohydrate concentrations were also predicted with good to moderate accuracy by both sensors (LCCC between 0.50 and 0.80). These models would be sufficiently accurate for making qualitative predictions (e.g., grouping into high to low categories). Ash and acid detergent fibre concentrations were poorly predicted (LCCC < 0.50) and these models would not be recommended for further use. It was concluded that multispectral data from Sentinel-2 has great potential to estimate pasture nutrient concentrations for intensively grazed pastures such as those used in dairy systems in temperate regions.

Nitrogen balance in dairy cows fed low-nitrogen diets based on various proportions of fresh grass and maize silage.

To ensure sustainable and efficient production, dairy farms must reduce their environmental impacts and nitrogen losses, which are sources of pollution, while increasing their feed self-sufficiency. Grass-based dairy systems, frequently combine fresh grass with maize silage when grass is scarce or during dietary transitions. However, the effects of combining fresh grass and maize silage on cow performance and N excretion are poorly known. This study aimed to quantify the effects of increasing the proportion of maize silage in a fresh grass diet on cow N flows and metabolism, in the context of grass-based dairy systems. Four proportions of maize silage in a fresh grass diet (objectives of 0, 17, 34 and 51% DM of maize silage) were investigated. The experiment was performed in a 4×3 Latin square design using eight lactating cows during three 3-week periods. DM intake (DMI), milk yield, faeces and urine outputs, and their N concentrations were measured for each cow. The fresh grass CP concentration was lower than planned (106±13.0g/kg DM). This resulted in very low dietary CP concentration, which decreased from 108 to 86g/kg DM when maize silage in the diet increased from 0 to 51% DM, respectively. DM intake and milk yield both decreased linearly by 3.3kg/day from 0 to 51% DM of maize silage in the diet. Thus, N intake decreased linearly by 100g/day from 0 to 51% DM of maize silage in the diet. The N concentration of milk was highest for the diet with 0% DM of maize silage. Nitrogen excreted in faeces and urine decreased linearly by 29 and 23g/day, respectively, from 0 to 51% DM of maize silage in the diet. The low dietary N concentration resulted in low ruminal NH3-N concentrations (8mg/L, on average) and urinary urea excretion (down to 8% urea N in urinary N). Increasing the proportion of maize silage in an unusually low-N grass diet, without protein-rich concentrates, induced highly N-deficient diets with minimal N losses in faeces and urine but large and unsustainable decreases in DMI and milk yield.