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The total biomass of a tall fescue (Festuca arundinacea var. Fletcher) pasture was assessed by using a vehicle mounted light detection and ranging (LiDAR) unit to derive canopy height and an active optical reflectance sensor to determine the spectro-optical reflectance index, normalized difference vegetation index (NDVI). In a random plot design, measurements of NDVI and pasture height were combined to estimate biomass with a root mean square error of prediction (RMSEP) equal to ±455.28 kg green dry matter (GDM)/ha, over a range of 286 kg to 3933 kg GDM/ha. The combination of NDVI and height measurements were observed to be more accurate in assessing total biomass than just the NDVI (RMSEP ± 846.51 kg/ha) and height (RMSEP ± 708.13 kg/ha). Based on the results of the study it was concluded the use of combined LiDAR and active optical reflectance sensors can help unlock the complex interrelationship between green fraction and biomass in swards containing both green and senescent material.

\"In October and November of 2001, small numbers of soldiers from the Army Special Forces entered Afghanistan, linked up with elements of the Northern Alliance (an assortment of Afghanis opposed to the Taliban), and, in a remarkably short period of time, destroyed the Taliban regime. Trained to work with indigenous forces and personnel like the Northern Alliance, these soldiers, sometimes riding on horseback, combined modern military technology with ancient techniques of central Asian warfare in what was later described as \"the first cavalry charge of the twenty-first century.\" Special Forces--the Navy's SEALs and the Army's Rangers and Green Berets--are highly trained soldiers with four principal missions: Direct action (typically such military operations as raids and rescue attempts), unconventional warfare, psychological operations and civil affairs. In their unconventional warfare role, they are often used as \"force multipliers,\" that is, they can be brought into a combat area of operations to train and lead indigenous troops. They have played an exceptionally prominent role in America's war on terrorism and are likely to continue doing so in the coming years. This book takes as its premise that SF are much publicized and little understood. His book offers readers the first truly penetrating examination of SF roles and missions by a serious scholar.Despite longstanding and growing public fascination with special operators, these individuals and the organizations that employ them are little understood. With this book, Tucker and Lamb dispel common misconceptions and offer a penetrating analysis of how these unique and valuable forces can be employed to even better effect in the future.\"-- Provided by publisher.

The estimation of pre-harvest fruit quality and maturity is essential for growers to determine the harvest timing, storage requirements and profitability of the crop yield. In-field fruit maturity indicators are highly variable and require high spatiotemporal resolution data, which can be obtained from contemporary precision agriculture systems. Such systems exploit various state-of-the-art sensors, increasingly relying on spectrometry and imaging techniques in association with advanced Artificial Intelligence (AI) and, in particular, Machine Learning (ML) algorithms. This article presents a critical review of precision agriculture techniques for fruit maturity estimation, with a focus on destructive and non-destructive measurement approaches, and the applications of ML in the domain. A critical analysis of the advantages and disadvantages of different techniques is conducted by surveying recent articles on non-destructive methods to discern trends in performance and applicability. Advanced data-fusion methods for combining information from multiple non-destructive sensors are increasingly being used to develop more accurate representations of fruit maturity for the entire field. This is achieved by incorporating AI algorithms, such as support vector machines, k-nearest neighbour, neural networks, and clustering. Based on an extensive survey of recently published research, the review also identifies the most effective fruit maturity indices, namely: sugar content, acidity and firmness. The review concludes by highlighting the outstanding technical challenges and identifies the most promising areas for future research. Hence, this research has the potential to provide a valuable resource for the growers, allowing them to familiarize themselves with contemporary Smart Agricultural methodologies currently in use. These practices can be gradually incorporated from their perspective, taking into account the availability of non-destructive techniques and the use of efficient fruit maturity indices.

Ecological restoration and the mainstreaming of the concept of ecosystem services will be critical if global society is to move toward sustainability. Conference of the Parties 21 (COP21) of the United Nations Framework Convention on Climate Change and COP12 of the Convention on Biological Diversity should help foster support for vastly increased investment in the better management and restoration of natural capital. Large-scale restoration demonstrably improves ecological functioning to sustain both biodiversity and human well-being. However, much progress is needed to improve the effectiveness and cost efficiency of any restoration. The ecosystem services concept provides a framework for identifying the types of restorative interventions needed to target different forms and degrees of degradation, and achieve goals related to both ecosystem health and delivery of services to people. Moreover, it can strengthen the argument for, and planning of, large-scale restoration and conservation of natural capital. We use case studies from four continents to help demonstrate how the interconnection between ecological restoration and the ecosystem services concept is being utilized in land-use planning and enlightened ecosystem management. We offer ways in which this relationship can be better understood and communicated to support the scaling up of restoration activities to the landscape and regional scales across the full spectrum of land uses and ecosystem types.

The TROG 96.01 trial assessed whether 3-month and 6-month short-term neoadjuvant androgen deprivation therapy (NADT) decreases clinical progression and mortality after radiotherapy for locally advanced prostate cancer. Here we report the 10-year results. Between June, 1996, and February, 2000, 818 men with T2b, T2c, T3, and T4 N0 M0 prostate cancers were randomly assigned to receive radiotherapy alone, 3 months of NADT plus radiotherapy, or 6 months of NADT plus radiotherapy. The radiotherapy dose for all groups was 66 Gy, delivered to the prostate and seminal vesicles (excluding pelvic nodes) in 33 fractions of 2 Gy per day (excluding weekends) over 6·5–7·0 weeks. NADT consisted of 3·6 mg goserelin given subcutaneously every month and 250 mg flutamide given orally three times a day. NADT began 2 months before radiotherapy for the 3-month NADT group and 5 months before radiotherapy for the 6-month NADT group. Primary endpoints were prostate-cancer-specific mortality and all-cause mortality. Treatment allocation was open label and randomisation was done with a minimisation technique according to age, clinical stage, tumour grade, and initial prostate-specific antigen concentration (PSA). Analysis was by intention-to-treat. The trial has been closed to follow-up and all main endpoint analyses are completed. The trial is registered with the Australian New Zealand Clinical Trials Registry, number ACTRN12607000237482. 802 men were eligible for analysis (270 in the radiotherapy alone group, 265 in the 3-month NADT group, and 267 in the 6-month NADT group) after a median follow-up of 10·6 years (IQR 6·9–11·6). Compared with radiotherapy alone, 3 months of NADT decreased the cumulative incidence of PSA progression (adjusted hazard ratio 0·72, 95% CI 0·57–0·90; p=0·003) and local progression (0·49, 0·33–0·73; p=0·0005), and improved event-free survival (0·63, 0·52–0·77; p<0·0001). 6 months of NADT further reduced PSA progression (0·57, 0·46–0·72; p<0·0001) and local progression (0·45, 0·30–0·66; p=0·0001), and led to a greater improvement in event-free survival (0·51, 0·42–0·61, p<0·0001), compared with radiotherapy alone. 3-month NADT had no effect on distant progression (0·89, 0·60–1·31; p=0·550), prostate cancer-specific mortality (0·86, 0·60–1·23; p=0·398), or all-cause mortality (0·84, 0·65–1·08; p=0·180), compared with radiotherapy alone. By contrast, 6-month NADT decreased distant progression (0·49, 0·31–0·76; p=0·001), prostate cancer-specific mortality (0·49, 0·32–0·74; p=0·0008), and all-cause mortality (0·63, 0·48–0·83; p=0·0008), compared with radiotherapy alone. Treatment-related morbidity was not increased with NADT within the first 5 years after randomisation. 6 months of neoadjuvant androgen deprivation combined radiotherapy is an effective treatment option for locally advanced prostate cancer, particularly in men without nodal metastases or pre-existing metabolic comorbidities that could be exacerbated by prolonged androgen deprivation. Australian Government National Health and Medical Research Council, Hunter Medical Research Institute, AstraZeneca, and Schering-Plough.

The determination of key phenological growth stages of banana plantations, such as flower emergence and plant establishment, is difficult due to the asynchronous growth habit of banana plants. Identifying phenological events assists growers in determining plant maturity, and harvest timing and guides the application of time-specific crop inputs. Currently, phenological monitoring requires repeated manual observations of individual plants’ growth stages, which is highly laborious, time-inefficient, and requires the handling and integration of large field-based data sets. The ability of growers to accurately forecast yield is also compounded by the asynchronous growth of banana plants. Satellite remote sensing has proved effective in monitoring spatial and temporal crop phenology in many broadacre crops. However, for banana crops, very high spatial and temporal resolution imagery is required to enable individual plant level monitoring. Unoccupied aerial vehicle (UAV)-based sensing technologies provide a cost-effective solution, with the potential to derive information on health, yield, and growth in a timely, consistent, and quantifiable manner. Our research explores the ability of UAV-derived data to track temporal phenological changes of individual banana plants from follower establishment to harvest. Individual plant crowns were delineated using object-based image analysis, with calculations of canopy height and canopy area producing strong correlations against corresponding ground-based measures of these parameters (R2 of 0.77 and 0.69 respectively). A temporal profile of canopy reflectance and plant morphology for 15 selected banana plants were derived from UAV-captured multispectral data over 21 UAV campaigns. The temporal profile was validated against ground-based determinations of key phenological growth stages. Derived measures of minimum plant height provided the strongest correlations to plant establishment and harvest, whilst interpolated maxima of normalised difference vegetation index (NDVI) best indicated flower emergence. For pre-harvest yield forecasting, the Enhanced Vegetation Index 2 provided the strongest relationship (R2 = 0.77) from imagery captured near flower emergence. These findings demonstrate that UAV-based multitemporal crop monitoring of individual banana plants can be used to determine key growing stages of banana plants and offer pre-harvest yield forecasts.

Studies estimating canopy volume are mostly based on laborious and time-consuming field measurements; hence, there is a need for easier and convenient means of estimation. Accordingly, this study investigated the use of remotely sensed data (WorldView-2 and LiDAR) for estimating tree height, canopy height and crown diameter, which were then used to infer the canopy volume of remnant eucalypt trees at the Newholme/Kirby ‘SMART’ farm in north-east New South Wales. A regression model was developed with field measurements, which was then applied to remote-sensing-based measurements. LiDAR estimates of tree dimensions were generally lower than the field measurements (e.g., 6.5% for tree height) although some of the parameters (such as tree height) may also be overestimated by the clinometer/rangefinder protocols used. The WorldView-2 results showed both crown projected area and crown diameter to be strongly correlated to canopy volume, and that crown diameter yielded better results (Root Mean Square Error RMSE 31%) than crown projected area (RMSE 42%). Although the better performance of LiDAR in the vertical dimension cannot be dismissed, as suggested by results obtained from this study and also similar studies conducted with LiDAR data for tree parameter measurements, the high price and complexity associated with the acquisition and processing of LiDAR datasets mean that the technology is beyond the reach of many applications. Therefore, given the need for easier and convenient means of tree parameters estimation, this study filled a gap and successfully used 2D multispectral WorldView-2 data for 3D canopy volume estimation with satisfactory results compared to LiDAR-based estimation. The result obtained from this study highlights the usefulness of high resolution data for canopy volume estimations at different locations as a possible alternative to existing methods.

Unoccupied aerial vehicles (UAVs) have become increasingly commonplace in aiding planning and management decisions in agricultural and horticultural crop production. The ability of UAV-based sensing technologies to provide high spatial (<1 m) and temporal (on-demand) resolution data facilitates monitoring of individual plants over time and can provide essential information about health, yield, and growth in a timely and quantifiable manner. Such applications would be beneficial for cropped banana plants due to their distinctive growth characteristics. Limited studies have employed UAV data for mapping banana crops and to our knowledge only one other investigation features multi-temporal detection of banana crowns. The purpose of this study was to determine the suitability of multiple-date UAV-captured multi-spectral data for the automated detection of individual plants using convolutional neural network (CNN), template matching (TM), and local maximum filter (LMF) methods in a geographic object-based image analysis (GEOBIA) software framework coupled with basic classification refinement. The results indicate that CNN returns the highest plant detection accuracies, with the developed rule set and model providing greater transferability between dates (F-score ranging between 0.93 and 0.85) than TM (0.86–0.74) and LMF (0.86–0.73) approaches. The findings provide a foundation for UAV-based individual banana plant counting and crop monitoring, which may be used for precision agricultural applications to monitor health, estimate yield, and to inform on fertilizer, pesticide, and other input requirements for optimized farm management.

During the early years of cytochrome P450 research, a picture of conserved properties arose from studies of mammalian forms of these monooxygenases. They included the protohaem prosthetic group, the cysteine residue that coordinates to the haem iron and the reduced CO difference spectrum. Alternatively, the most variable feature of P450s was the enzymatic activities, which led to the conclusion that there are a large number of these enzymes, most of which have yet to be discovered. More recently, studies of these enzymes in other eukaryotes and in prokaryotes have led to the discovery of unexpected P450 properties. Many are variations of the original properties, whereas others are difficult to explain because of their unique nature relative to the rest of the known members of the superfamily. These novel properties expand our appreciation of the broad view of P450 structure and function, and generate curiosity concerning the evolution of P450s. In some cases, structural properties, previously not found in P450s, can lead to enzymatic activities impacting the biological function of organisms containing these enzymes; whereas, in other cases, the biological reason for the variations are not easily understood. Herein, we present particularly interesting examples in detail rather than cataloguing them all.