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Autumn grazing management aims to accumulate herbage for defoliation prior to a decrease in growth rates for the extension of the grazing season. The current study investigated the impact of building different target herbage masses (THMs) in autumn and imposing one of three different defoliation dates (DDs) between mid-October and late November on light transmitted to the base of the sward, free leaf lamina (FLL), leaf stage and internode elongation. Four THMs (low, medium, high and very high) and three DDs (DD1—15 October, DD2—7 November and DD3—21 November) were assigned to a 4 × 3 split plot design over two years. Light transmitted to the base of the sward was greatest in the low THM and decreased in all other THMs. Internode elongation increased in tillers in the medium to the very high THMs. Defoliation of the medium, high and, in particular, the very high THMs earlier in autumn reduced the effect of decreased light transmission on internode elongation. This study highlights that, as light transmitted to the base of the sward decreases, internode elongation increases, and this could negatively impact sward structure. [ABSTRACT FROM AUTHOR]

Aphids are major pests of cereal and pasture grasses throughout the world, vectoring disease and reducing plant production. There are few control options other than insecticides. Epichloë endophytes that produce loline alkaloids in their hosts provide a possible mechanism of control, with both meadow fescue and tall fescue naturally infected with loline-producing endophytes showing a resistance to Rhopalosiphum padi. We screened Elymus spp. naturally infected with endophytes that produced loline alkaloids at concentrations known to affect aphids on fescue but found no effect on these insects infesting Elymus. A synthetic loline-producing endophyte association with rye also had no effect on the aphids. After hypothesizing that the lolines were being translocated in the xylem in Elymus and rye rather than the phloem, we tested the rye and meadow fescue infected with loline-producing endophytes against a xylem feeding spittlebug. The endophyte in rye inhibited the feeding of the insect and reduced its survival, whereas the endophyte-infected meadow fescue had no effect on the spittlebug but reduced the number of aphids. Lolines applied to the potting medium of endophyte-free and endophyte-infected rye, ryegrass, and tall fescue resulted in a decrease in the aphid populations on the endophyte-free pasture grasses relative to the untreated controls but had no effect on aphid numbers on the rye. We tentatively conclude that lolines, produced in both natural and synthetic association with Elymus and rye, are partitioned in the xylem rather than the phloem, where they are inaccessible to aphids. [ABSTRACT FROM AUTHOR]

Simple Summary: Limited studies have been reported so far on the rumen degradability characteristic of low-quality forage. In the current study, three low-quality forages (Chinese rye grass, barley grass, and naked oat straw) were selected. Various nutritional parameters such as rumen degradation characteristics, chemical composition and feeding value of three roughages were studied in detail. Among the three roughages, the Chinese rye grass (Leymus chinensis) was superior in terms of rumen degradability characteristics, chemical composition and feeding value. The current study was designed to investigate the chemical composition, rumen degradation characteristics, and feeding value of three roughages commonly used in Asia as ruminant feed, including Chinese rye grass (CRG), barley grass (BG), and naked oat straw (NO). Four Holstein Friesian cows equipped with permanent rumen fistulas were chosen for experimental trials in the current study. The nylon bag method was carried out to measure the crude protein (CP), acid detergent fiber (ADF), ruminal degradability of dry matter (DM), and neutral detergent fiber (NDF). Our analysis revealed that the contents of CP in the CRG (9.0%) and BG (8.9%) were higher than in the NO (5.94%). The contents of NDF in the CRG (64.97%) and NO (63.83%) were lower than in the BG (67.33%), and the content of ADF in the CRG (37.03%) was lower than in the BG (37.93%) and NO (38.28%). The ED values of DM in the NO and CRG were significantly higher (p < 0.001) than in the BG. The effective degradability (ED) values of NDF were the highest in the CRG and lowest in the NO (p < 0.001). In addition, the ED values of ADF were the highest in the CRG and lowest in the BG (p < 0.001). The ED value of CP in the CRG was significantly higher than that in the BG and NO (p < 0.001). The estimated total digestible nutrients (TDN) (54.56%) and DM degradation rate (DDM) (60.06%) of the CRG were higher than those of BG and NO. In addition, the expected DM intake (DMI), estimated relative feed value (RFV), and estimated relative feed quality (RFQ) of the BG were lower than those of the CRG and NO. Altogether, based on our findings, we concluded that the nutritional quality, feeding value and effective rumen degradation rate of CRG were better than of BG and NO. [ABSTRACT FROM AUTHOR]

High-throughput field phenotyping using close remote sensing platforms and sensors for non-destructive assessment of plant traits can support the objective evaluation of yield predictions of large breeding trials. The main objective of this study was to examine the potential of unmanned aerial vehicle (UAV)-based structural and spectral features and their combination in herbage yield predictions across diploid and tetraploid varieties and breeding populations of perennial ryegrass (Lolium perenne L.). Canopy structural (i.e., canopy height) and spectral (i.e., vegetation indices) information were derived from data gathered with two sensors: a consumer-grade RGB and a 10-band multispectral (MS) camera system, which were compared in the analysis. A total of 468 field plots comprising 115 diploid and 112 tetraploid varieties and populations were considered in this study. A modelling framework established to predict dry matter yield (DMY), was used to test three machine learning algorithms, including Partial Least Squares Regression (PLSR), Random Forest (RF), and Support Vector Machines (SVM). The results of the nested cross-validation revealed: (a) the fusion of structural and spectral features achieved better DMY estimates as compared to models fitted with structural or spectral data only, irrespective of the sensor, ploidy level or machine learning algorithm applied; (b) models built with MS-based predictor variables, despite their lower spatial resolution, slightly outperformed the RGB-based models, as lower mean relative root mean square error (rRMSE) values were delivered; and (c) on average, the RF technique reported the best model performances among tested algorithms, regardless of the dataset used. The approach introduced in this study can provide accurate yield estimates (up to an RMSE = 308 kg ha−1) and useful information for breeders and practical farm-scale applications. [ABSTRACT FROM AUTHOR]

Accumulating herbage mass to facilitate the extension of the grazing season in autumn is commonly practised. The objective of the current study was to investigate the effect of accumulating varying target herbage masses (THM) in autumn and imposing different defoliation dates (DD), on herbage mass, sward quality and water-soluble carbohydrates in autumn and the subsequent spring. A 4 × 3 factorial split plot design was assigned with four THM (Low ≈ 500 kg·DM·ha−1, Medium ≈ 1500 kg·DM·ha−1, High ≈ 2000 kg·DM·ha−1 and Very high ≈ 3000 kg·DM·ha−1) and three DD (DD1—15 October, DD2—7 November and DD3—21 November), across two years. Measurements were carried out at each DD and in spring. Differences in sward quality were found between each THM on different DD. Sward quality reduced from DD2 to DD3 in the high THM (−13 g·kg−1 DM CP, p < 0.001). The very high THM had the lowest sward quality from DD1 (206 g·kg−1 DM CP, p < 0.001 and 787 g·kg−1 DM DMD, p < 0.05). This study has identified the defoliation date of THM in autumn as key to improving autumn management strategies for increased utilisation and sward quality. [ABSTRACT FROM AUTHOR]

This study examines the effectiveness of a model called LINGRA-N-Plus to simulate the interaction of climate, soil and management on the green leaf and total dry matter yields of ryegrass in England and Wales. The LINGRA-N-Plus model includes modifications of the LINGRA-N model such as temperature- and moisture-dependent soil nitrogen mineralization and differential partitioning to leaves and stems with thermal time from the last harvest. The resulting model was calibrated against the green leaf and total grass yields from a harvest interval x nitrogen application experiment described by Wilman et al. (1976). When the LINGRA-N-Plus model was validated against total grass yields from nitrogen experiments at ten sites described by Morrison et al. (1980), its modelling efficiency improved greatly compared to the original LINGRA-N. High predicted yields, at zero nitrogen application, were related to soils with a high initial nitrogen content. The lowest predicted yields occurred at sites with low rainfall and shallow rooting depth; mitigating the effect of drought at such sites increased yields by up to 4 t ha−1. The results highlight the usefulness of grass models, such as LINGRA-N-Plus, to explore the combined effects of climate, soil, and management, like nitrogen application, and harvest intervals on grass productivity. [ABSTRACT FROM AUTHOR]

This study focuses on calibrating and validating models for hyperspectral canopy reflectance data that are useful to predict the nutritive value of ryegrass-white clover mixed herbage available to the grazing cow. Hyperspectral measurements and herbage cuts were collected from 286 sampling plots from a dairy farm from July 2017 to May 2018. Hyperspectral data were pre-treated by applying a Savitzky-Golay filter followed by a Gap-segment derivative algorithm. Herbage samples were analyzed for determination of herbage nutritive value traits, digestible organic matter in dry matter (DOMD), metabolizable energy (ME), crude protein (CP), neutral detergent fiber (NDF) and acid detergent fiber (ADF). Partial least squares regression was performed to calibrate the spectra against the five nutritive value traits. Results indicate that accuracy was moderately high for the CP model (R2 = 0.78) and moderate for the DOMD, ME, NDF and ADF models (0.54 < R2 < 0.67). The possibility of being able to use proximal sensing for the estimation of herbage nutritive value in the field could potentially contribute to more efficient grazing management with potential economic benefits for the farm business. [ABSTRACT FROM AUTHOR]

Sabah snake grass or Clinacanthus nutans has drawn public interest having significant economic benefits attributable to the presence of phytochemicals and several interesting bioactive constituents that may differ according to harvesting age and harvesting frequency. The current study was aimed to evaluate the effect of harvesting age and harvesting frequency towards herbal yield, antioxidant activities, phytochemicals synthesis, and bioactive compounds of C. nutans. A factorial randomized completely block design with five replications was used to illustrate the relationship between herbal yield, DPPH (2, 2-diphenyl-1-picrylhydrazyl) and ferric reducing antioxidant power (FRAP) assays, total phenolic and flavonoid content affected by harvesting age (week 8, 12, and 16 after transplanting), and harvesting frequency (harvest 1, 2, and 3). The bioactive compounds by HPLC were also determined to describe the interaction effect between both harvesting age and harvesting frequency. The yield, antioxidant activities, and phytochemical contents were gradually increased as the plant grew, with the highest recorded during week 16. However, the synthesis and activities of phytochemicals were reduced in subsequent harvests despite the increment of the herbal yield. All bioactive compounds were found to be influenced insignificantly and significantly by harvesting age and harvesting frequency, respectively, specifically to shaftoside, iso-orientin, and orientin. Among all constituents, shaftoside was the main compound at various harvesting ages and harvesting frequencies. These results indicated that harvesting at week 16 with 1st harvest frequency might enhance the yield while sustaining the high synthesis of polyphenols and antioxidant activities of C. nutans. [ABSTRACT FROM AUTHOR]

Increasing the rate of genetic gain for dry matter (DM) yield in perennial ryegrass (Lolium perenne L.), which is a key source of nutrition for ruminants in temperate environments, is an important goal for breeders. Genomic selection (GS) is a strategy used to improve genetic gain by using molecular marker information to predict breeding values in selection candidates. An empirical assessment of GS for herbage accumulation (HA; proxy for DM yield) and days-to-heading (DTH) was completed by using existing genomic prediction models to conduct one cycle of divergent GS in four selection populations (Pop I G1 and G3; Pop III G1 and G3), for each trait. G1 populations were the offspring of the training set and G3 populations were two generations further on from that. The HA of the High GEBV selection group (SG) progenies, averaged across all four populations, was 28% higher (p < 0.05) than Low GEBV SGs when assessed in the target environment, while it did not differ significantly in a second environment. Divergence was greater in Pop I (43%–65%) than Pop III (10%–16%) and the selection response was higher in G1 than in G3. Divergent GS for DTH also produced significant (p < 0.05) differences between High and Low GEBV SGs in G1 populations (+6.3 to 9.1 days; 31%–61%) and smaller, non-significant (p > 0.05) responses in G3. This study shows that genomic prediction models, trained from a small, composite reference set, can be used to improve traits with contrasting genetic architectures in perennial ryegrass. The results highlight the importance of target environment selection for training models, as well as the influence of relatedness between the training set and selection populations. [ABSTRACT FROM AUTHOR]

Sensor-based phenotyping technologies may offer a non-destructive, high-throughput and efficient assessment of herbage yield (HY) to replace current inefficient phenotyping methods. This paper assesses the feasibility of combining normalised difference vegetative index (NDVI) from multispectral imaging and ultrasonic sonar estimates of plant height to estimate HY of single plants in a large perennial ryegrass breeding program. For sensor calibration, fresh HY (FHY) and dry HY (DHY) were acquired destructively, and plant height was measured at four dates each in 2017 and 2018 from a selected subset of 480 plants. Global multiple linear regression models based on K-fold and random split cross-validation methods were used to evaluate the relationship between observed vs. predicted HY. The coefficient of determination (R2) = 0.67–0.68 and a root mean square error (RMSE) between 5.43–7.60 g was obtained for the validation of predicted vs. observed DHY. The mean absolute error (MAE) and mean percentage error (MPE) ranged between 3.59–5.44 g and 22–28%, respectively. For the FHY, R2 values ranged from 0.63 to 0.70, with an RMSE between 23.50 and 33 g, MAE between 15.11 and 24.34 g and MPE between ~22% and 31%. Combining NDVI and plant height is a robust method to enable high-throughput phenotyping of herbage yield in perennial ryegrass breeding programs. [ABSTRACT FROM AUTHOR]

Simple Summary: Increasing soluble sugars in pasture species can lead to an improved nutrient use efficiency in the rumen and a greater digestibility of forage, which in turn might increase pasture intake. However, this improvement in nutritional value must not be at the expense of pasture productivity; the amount of nutrients harvested is a relevant factor in ruminant grazing systems' efficiency. Therefore, we tested four different cultivars of perennial ryegrass (two selected for greater soluble sugar content and two standard cultivars) submitted to two contrasting managements (one aimed at improving sugar content and one with the opposite intended effect) for their effects on pasture productivity (by cutting herbage every time the plots reached the target number of leaves per tiller, i.e., two or three) and the grazing preference of dairy cows (six cows grazed for up to 5 hours, in an experimental area with three plots for each of the eight treatments) in spring, summer and autumn. We found that high sugar grasses had lower annual dry matter productivity and no preference was shown by cows, although the agronomic management aimed at reducing sugar concentration enhanced crude protein concentration and increased the herbage harvested (greater preference) in the three seasons, and the time spent grazing in autumn. The objective of this study was to evaluate the pasture performance of different cultivars of perennial ryegrass, two "high sugar" and two standard cultivars, under two contrasting agronomic managements (aimed at either decreasing or increasing water soluble carbohydrates concentration), and their effects on the grazing preference of dairy cows. Eight treatments arising from the factorial combination of four cultivars and two managements were randomly applied to 31-m2 plots in three blocks. Pasture dry matter production and growth rate were measured for one year. Three grazing assessments were performed to establish the grazing preferences of six dairy cows in spring, summer and autumn. High sugar cultivars produced less dry matter per hectare than the standard cultivars. Cows consumed more grass and harvested a greater proportion of the pasture under the agronomic management aimed at decreasing sugar concentration, i.e., with a greater nitrogen fertilization rate and under a more frequent defoliation regime, which could be explained by the greater crude protein concentration achieved under this management. The results suggest that the genetic selection for greater levels of sugars was at the expense of herbage yield, and that cows preferred to graze herbage with a greater crude protein level instead of a greater sugar concentration. [ABSTRACT FROM AUTHOR]