Below Ground Benefits of Cactus \u3ci\u3eOpuntia stricta\u3c/i\u3e Under Rangeland Conditions in Laikipia, Kenya

Cactus Opuntia stricta primarily invades arid and semi-arid lands (ASALs), which form more than 80% of Kenya’s landmass. The ability of the plant to tolerate poor soils and accumulate biomass under low precipitation has resulted in studies into its potential use by pastoral communities for biofuel and livestock feed. However, few studies have assessed the below-ground benefits associated with cactus under rangeland conditions. In this study, we evaluated the root contributions of the invasives cactus Opuntia stricta under rangeland conditions in Laikipia, Kenya. The experiment was laid out in a randomized complete block design with ten (10) replicates, each measuring 30 × 30 m. Each block was further subdivided into three plots of 10 x 30m Three clusters were randomly selected from each plot for roots and soil samples starting from the center of the cluster (C) to the outside in a gradient of three radii, R1, R2 and R3. Data was collected for root (dry root biomass, % carbon and % nitrogen) and soil (pH, bulk density, % moisture and % nitrogen) characteristics. Significant differences in total root mass, root carbon, and root nitrogen were observed under varying cluster gradients. Root mass ranged from 4527.0 to 9242.0 kg/ha for the outermost radius (R3) and the cluster’s center, respectively. Similarly, except for the soil nitrogen, statistical differences were observed for soil bulk density, percent soil moisture and percent nitrogen along the different cluster gradients. The soil bulk density ranged from 1.2±0.02 (center) to 1.5±0.01 g cm3 (radius 2). Findings from this study demonstrate the important contribution of the invasive cactus species in sustaining the ecological functions of rangeland soils such as those found in Laikipia, Kenya

A Novel Technique to Label Cover Crop Biomass Using Stable Isotopes

Stable isotopes can be used as tracers for carbon and nitrogen pathways being a great tool to track nutrients in integrated systems. The objective of this experiment was to understand the partitioning of 15N and 13C within cover crop plants when they were labeled with stable isotopes, using chambers under field conditions. Cover crops were planted at the University of Florida, North Florida Research and Education Center-Marianna, located in Marianna, FL. Treatments were four cover crops, in which one was considered a typical cover crop system and the other three consisted of an integrated crop-livestock system with or without the inclusion of legume or different nitrogen fertilizer rates grazed every two weeks. All treatments were replicated three times in a randomized complete block design. Two chambers were built and placed in each plot to label the cover crop plants. For the 15N labeling, 15N2-labeled urea (98 atom% 15N) was applied at a rate of 0.5 kg N ha-1 only once. The target amount of 13CO2 (99 atom% 13C) was determined considering a 20% enrichment of the CO2 concentration present inside the chamber’s volume. The 13CO2 labeling was performed for 28 consecutive days. The labeling technique using chambers and stable isotopes to enrich cover crop species worked under field conditions for both, grass and legume species. Moving forward, this labeling technique can be a useful tool to track nutrient pathways, especially litter decomposition in diversified integrated crop and livestock systems under different management practices

Prediction of aboveground biomass and dry-matter content in brachiaria pastures by combining meteorological data and satellite imagery.

Aboveground biomass (AGB) data are important for profitable and sustainable pasture management. In this study, we hypothesized that vegetation indexes (VIs) obtained through analysis of moderate spatial resolution satellite data (Landsat-8 and Sentinel-2) and meteorological data can accurately predict the AGB of Brachiaria (syn. Urochloa) pastures in Brazil. We used AGB field data obtained from pastures between 2015 and 2019 in four distinct regions of Brazil to evaluate (i) the relationship between three different VIs?normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2) and optimized soil adjusted vegetation index (OSAVI)?and meteorological data with pasture aboveground fresh biomass (AFB), aboveground dry biomass (ADB) and dry-matter content (DMC); and (ii) the performance of simple linear regression (SLR), multiple linear regression (MLR) and random forest (RF) algorithms for the prediction of pasture AGB based on VIs obtained through satellite imagery combined with meteorological data. The results highlight a strong correlation (r) between VIs and AGB, particularly NDVI (r = 0.52 to 0.84). The MLR and RF algorithms demonstrated high potential to predict AFB (R2 = 0.76 to 0.85) and DMC (R2 = 0.78 to 0.85). We conclude that both MLR and RF algorithms improved the biomass prediction accuracy using satellite imagery combined with meteorological data to determine AFB and DMC, and can be used for Brachiaria (syn. Urochloa) AGB prediction. Additional research on tropical grasses is needed to evaluate different VIs to improve the accuracy of ADB prediction, thereby supporting pasture management in Brazil

Evaluation of a long-established silvopastoral Brachiaria decumbens system: plant characteristics and feeding value for cattle.

Abstract One of the main challenges of using a silvopastoral system (SPS) is maintaining pasture and animal productivity over time. Our objective was to compare the productive characteristics and nutritive value of signal grass (Brachiaria decumbens cv. Basilisk) and the liveweight gain of dairy heifers in a SPS and open pasture (OP, signal grass under full sunlight) during the rainy seasons of four experiments between 2003 and 2016, which characterised systems from their 6th to 19th years after establishment in south-eastern Brazil when analysed together. The experimental design was a randomised complete block in a 2 4 factorial scheme (two production systems (SPS and OP) and four experiments (2003?2004, 2004?2007, 2011?2014 and 2014?2016)). From the 7th year onwards, the progressive reduction of photosynthetically active radiation negatively impacted the productive characteristics of the SPS pasture. Total forage mass was reduced by 19% in SPS compared with the OP in 2004?2007, 38% in 2011?2014 and 31% in 2014?2016. Crude protein content was 23%and30%higher in theSPSthan in theOPin 2011?2014 and 2014?2016, respectively. However, during the study period (until the 19th year), the liveweight gain of heifers was similar between systems since the higher crude protein content available in SPS contributed to improved forage nutritional value. From the 17th to the 19th year, weight gain per area was lower in the SPS compared with the OP (169 vs 199 kg ha?1), although the difference between systems was small. Signal grass presents a high degree of phenotypic plasticity in response to changes in shade levels, which gives this species a high potential for use in SPS