Taisuke Yasuda

Monitoring of forage conditions with MODIS imagery in the Xilingol steppe, Inner Mongolia

A study was conducted to determine the potential suitability of Terra/MODIS imagery for monitoring short‐term phenological changes in forage conditions in a semi‐arid region. The study sites included four meadow steppes and six typical steppes in the Xilingol steppe in central Inner Mongolia, China. The live biomass, dead standing biomass, total biomass, crude protein (CP) concentration and standing CP were estimated from early April to late October using the Enhanced Vegetation Index (EVI) values from Terra imagery (500 m pixels). Applying regression models, the EVI accounted for 80% of the variation in live biomass, 42% of the dead biomass, 77% of the total biomass, 11% of the CP concentration and 74% of the standing CP. MODIS/EVI is superior to AVHRR/NDVI when estimating forage quantity. Applying these results, the seasonal changes in live biomass and the standing CP could be described in the selected four sites with different degrees of grazing intensity. Generally, the increase in grazing intensity tended to decrease live biomass and standing CP. It was suggested that the EVI obtained from Terra imagery was an available predictor of the forage condition as measured by live biomass and standing CP. The MODIS/EVI values could provide information on the suitable timing of cutting for hay‐making and nutritive value to range managers.

Spatial heterogeneity in a grassland community: Use of power law

A new regression analysis was proposed to evaluate the degree of spatial heterogeneity for individual species comprising a plant grassland community. The weighted average of the heterogeneity value of all the species comprising the community provides a measure of community-level heterogeneity. A field survey was carried out, as an example, in order to analyze the spatial heterogeneity of a pasture with grazing cows, using 100 quadrats 50 cm × 50 cm, each of which was divided into four smaller quadrats 25 cm × 25 cm, on a 50 m long line-transect. The frequency of occurrence for all the species in each small quadrat was recorded. The regression associated with the ratio of the theoretical and observed variances of occurence counts was used to analyse the frequency distribution of species in a pasture community. A good fit to the regression for the whole community was obtained. These results indicate that (i) each species in the example was distributed more heterogeneously than a random pattern; and (ii) the regression could well describe the spatial heterogeneity of the grassland plant community. In most of the observed species, spatial heterogeneity is often characterized by species-specific propagation traits and the architecture of plant bodies. Thus, the spatial patterns of a grassland community can be evaluated in detail by this power-law approach. This measure is suitable for field surveys and comparative studies of grassland communities, and for other plant communities that are generally short in height.

A preliminarily study for predicting body weight and milk properties in lactating Holstein cows using a three-dimensional camera system

Digital imaging has been applied to assess body weight and fatness in livestock.We examine low priced 3D camera for estimating cow body weight and milk properties.Six geodesic line (GL) lengths were computed using back posture 3D object of cow.A similar determination of body condition with standard method is possible. Since manual body condition scoring has been widely utilized as an indirect and subjective method to estimate energy reserves of dairy cattle, image analysis has been increasingly researched for use on large farms as an objective and effective measuring instrument for the estimation of body condition score (BCS) and body weight (BW). Recent advances in the technological development of the three-dimensional (3D) cameras may provide innovative feed management tools for dairy farms. The objective of the present study was to evaluate the feasibility of a 3D camera systems in measuring the back posture of lactating Holstein dairy cows to predict the BCS, BW, milk yield (MY), milk fat (MF) and milk protein (MP). The BCSs for eight cows were recorded by two trained observers using a 5-point scale, and other variables were obtained using an automatic milking system during the lactation. Back posture measurements of dairy cows were conducted using the ASUS Xtion Pro sensor. Six geodesic line (GL) lengths were computed using the 3D objects of each cow based on the positions of the right and left hook bones (GLhh), right and left thurl bones (GLtt), right and left pin bones (GLpp), hook and thurl bones (GLht), hook and pin bones (GLhp), and coccygeal ligament (GLcl). In the principal component analysis (PCA), GL, GLpp, and GLcl had the greatest contribution to principal component values (PCV) 1, 2, and 3, respectively, and these three PCVs described 0.887 of the cumulative contribution ratio. Good correlations were found between the observed and predicted values of BCS (R2=0.74), BW (0.80), MY (0.62), MF (0.62), and MP (0.53) based on linear regression equations using the GLs as explanatory variables and parity (1, 2, and >3) as a fixed effect. These results demonstrate that the 3D cameras could represent an innovative tool for estimating body condition and milk properties.

Nurse-Plant Effects of a Dwarf Shrub on the Establishment of Tree Seedlings in a Volcanic Desert on Mt. Fuji, Central Japan

ABSTRACT We investigated vegetation structure and microenvironments on bare volcanic soil covered by scoria above the forest limit on Mt. Fuji, central Japan, to evaluate the effects of patches of a pioneer dwarf shrub (Salix reinii) on the establishment of early successional tree seedlings (Larix kaempferi). We analyzed species distribution patterns and the associations among them, and compared the performance (growth and survivorship) of Larix seedlings and the local environment (temperature, solar radiation, soil surface stability, soil moisture, and nitrogen) inside and outside Salix patches. Larix displayed significantly clumped distribution, and the clumping was apparently associated with the preferential occurrence of Larix in Salix patches. Salix patches moderated severe microenvironmental factors, such as drought, high temperature, and movement of the soil surface. Salix patches promoted increased height and decreased root∶shoot ratio, but not higher rate of biomass accumulation in Larix seedlings. Survival rate of L. kaempferi inside Salix patches was higher than that outside patches at the younger stage, but it was lower at the older stage after L. kaempferi emerged from the Salix crown. The results indicate S. reinii enhances seedling establishment and survival of young L. kaempferi, but may compete with it at later stages. The overall net effect of Salix patches on L. kaempferi is positive, and therefore S. reinii appears to accelerate succession from scoria bare land to pioneer woodland.

A simple visible and near-infrared (V-NIR) camera system for monitoring the leaf area index and growth stage of Italian ryegrass

Abstract Crop growth stage is critical for making decisions in nutrient management and for evaluating crop productivity. In this study, a simple visible and near-infrared (V-NIR) camera system was developed for monitoring the leaf area index (LAI) and quantifying the quick growth stage (QGS) of Italian ryegrass. RAW format images in the red, green and NIR channels over two growing seasons of 2014–15 and 2015–16 were captured hourly each day by the V-NIR camera system installed in three Italian ryegrass fields at the farm of Hiroshima University. Multiple linear regression (MLR) models that predict the forage LAI from the imagery data were calibrated and validated, with high coefficient of determination ( R 2 = 0.79 ) and low root-mean-square error ( RMSE = 1.09 ) between the measured and predicted LAIs. The predicted LAI to which three vegetation indices were compared was fitted against a logistic model to extract forage QGS from smoothed time-series data under various micro-meteorological and nutrient conditions. The result shows the time-series data of LAI can be applied for monitoring seasonal changes regardless of the environmental conditions. The RMSE of the predicted phenology dates against the field-measured LAI was 0.58 and 5.2 days for the start- and end-QGS, respectively, under the high-yield condition in season 1. However, in season 2, only the start-QGS was identifiable, with an RMSE of 2.65 days under the nutritional stress condition. The forage LAI and QGS were predicted and identified with acceptable accuracy and reliability, which suggests that the V-NIR camera system can be employed as a cost-effective approach for monitoring seasonal changes in crop growth, aiding in better personalized crop and nutrient management.