Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries

Background

Low cost unmanned aerial systems (UAS) have great potential for rapid proximal measurements of plants in agriculture. In the context of plant breeding and genetics, current approaches for phenotyping a large number of breeding lines under field conditions require substantial investments in time, cost, and labor. For field-based high-throughput phenotyping (HTP), UAS platforms can provide high-resolution measurements for small plot research, while enabling the rapid assessment of tens-of-thousands of field plots. The objective of this study was to complete a baseline assessment of the utility of UAS in assessment field trials as commonly implemented in wheat breeding programs. We developed a semi-automated image-processing pipeline to extract plot level data from UAS imagery. The image dataset was processed using a photogrammetric pipeline based on image orientation and radiometric calibration to produce orthomosaic images. We also examined the relationships between vegetation indices (VIs) extracted from high spatial resolution multispectral imagery collected with two different UAS systems (eBee Ag carrying MultiSpec 4C camera, and IRIS+ quadcopter carrying modified NIR Canon S100) and ground truth spectral data from hand-held spectroradiometer.

Results

We found good correlation between the VIs obtained from UAS platforms and ground-truth measurements and observed high broad-sense heritability for VIs. We determined radiometric calibration methods developed for satellite imagery significantly improved the precision of VIs from the UAS. We observed VIs extracted from calibrated images of Canon S100 had a significantly higher correlation to the spectroradiometer (r = 0.76) than VIs from the MultiSpec 4C camera (r = 0.64). Their correlation to spectroradiometer readings was as high as or higher than repeated measurements with the spectroradiometer per se.

Conclusion

The approaches described here for UAS imaging and extraction of proximal sensing data enable collection of HTP measurements on the scale and with the precision needed for powerful selection tools in plant breeding. Low-cost UAS platforms have great potential for use as a selection tool in plant breeding programs. In the scope of tools development, the pipeline developed in this study can be effectively employed for other UAS and also other crops planted in breeding nurseries.

     

Dietary roughage sources affect lactating Holstein x Zebu cows under experimental conditions in Brazil: a meta-analysis

Tropical Animal Health and Production - To reduce costs, lactating cows are often fed a higher proportion of roughage and alternative feeds; however, such protocols may not lead to optimal milk...     

Estimating nocturnal ecosystem respiration from the vertical turbulent flux and change in storage of CO2

Micrometeorological measurements of nighttime ecosystem respiration can be systematically biased when stable atmospheric conditions lead to drainage flows associated with decoupling of air flow above and within plant canopies. The associated horizontal and vertical advective fluxes cannot be measured using instrumentation on the single towers typically used at micrometeorological sites. A common approach to minimize bias is to use a threshold in friction velocity, u_*, to exclude periods when advection is assumed to be important, but this is problematic in situations when in-canopy flows are decoupled from the flow above. Using data from 25 flux stations in a wide variety of forest ecosystems globally, we examine the generality of a novel approach to estimating nocturnal respiration developed by van Gorsel et al. (van Gorsel, E., Leuning, R., Cleugh, H.A., Keith, H., Suni, T., 2007. Nocturnal carbon efflux: reconciliation of eddy covariance and chamber measurements using an alternative to the u_*-threshold filtering technique. Tellus 59B, 397–403, Tellus, 59B, 307-403). The approach is based on the assumption that advection is small relative to the vertical turbulent flux (F_C) and change in storage (F_S) of CO₂ in the few hours after sundown. The sum of F_C and F_S reach a maximum during this period which is used to derive a temperature response function for ecosystem respiration. Measured hourly soil temperatures are then used with this function to estimate respiration R_Rmax. The new approach yielded excellent agreement with (1) independent measurements using respiration chambers, (2) with estimates using ecosystem light-response curves of F_c + F_s extrapolated to zero light, R_LRC, and (3) with a detailed process-based forest ecosystem model, R_cast. At most sites respiration rates estimated using the u_*-filter, R_ust, were smaller than R_Rmax and R_LRC. Agreement of our approach with independent measurements indicates that R_Rmax provides an excellent estimate of nighttime ecosystem respiration.     

The sounds of silence: regime shifts impoverish marine soundscapes

Context

Regime shifts are well known for driving penetrating ecological change, yet we do not recognise the consequences of these shifts much beyond species diversity and productivity. Sound represents a multidimensional space that carries decision-making information needed for some dispersing species to locate resources and evaluate their quantity and quality.

Objectives

Here we assessed the effect of regime shifts on marine soundscapes, which we propose has the potential function of strengthening the positive or negative feedbacks that mediate ecosystem shifts.

Methods

We tested whether biologically relevant cues are altered by regime shifts in kelp forests and seagrass systems and how specific such shifted soundscapes are to the type of driver; i.e. local pollution (eutrophication) vs. global change (ocean acidification).

Results

Here, we not only provide the first evidence for regime-shifted soundscapes, but also reveal that the modified cues of shifted ecosystems are similar regardless of spatial scale and type of environmental driver. Importantly, biological sounds can act as functional cues for orientation by dispersing larvae, and observed shifts in soundscape loudness may alter this function.

Conclusions

These results open the question as to whether shifted soundscapes provide a functional role in mediating the positive or negative feedbacks that govern the arrival of species associated with driving change or stasis in ecosystem state.

     

The Content of Dietary Fibre and Polyphenols in Morphological Parts of Buckwheat (<Emphasis Type="Italic">Fagopyrum tataricum</Emphasis>)

In this report, we presented the profile of polyphenolic substances in flowers, leaves, stalk and roots of Fagopyrum tataricum estimated by using RP–UHPLC–ESI-MS equipment (reversed-phase ultra-high-performance liquid chromatography electrospray ionisation mass spectrometry). The neutral detergent fibre, acid detergent fibre, acid detergent lignin, cellulose and hemicellulose were also determined. Flowers, leaves, stalk and roots showed varying levels of dietary fibre and polyphenols. The highest content of neutral and acid detergent fibre were found in the roots (63.92 and 45.45% d.m., respectively) while the most rich in phenolic compounds were flowers (4.8 mg/1 g d.m.). Root and stalk contained the highest level of cellulose, 38.70 and 25.57% d.m., respectively. Among the investigated polyphenolic substances such as: 2,6-dihydroxybenzoic acid, 3,4-dihydroxybenzoic acid, 3,5-dihydroxybenzoic acid, 4-hydrobenzoic acid, caffeic acid, catechin, chlorogenic acid, fagopyrin, ferulic acid, myricetin, gallic acid, isovanilic acid, isovitexin, kaempferol, luteolin, p-coumaric acid, procyanidin B2, quercetin, quercetin 3-D galactoside, rutin, syringic acid and vitexin, we observed that the contents of rutin and chlorogenic acid were the highest. We found some correlation between dietary fibre fractions and individual phenolic substances. The levels of acid detergent fibre (ADF), cellulose and hemicellulose were negatively correlated with isovitexin, kaempferol, vitexin, fagopyrin, caffeic acid and procyanidin B2 content. In this investigation, two solvents (water and methanol) were estimated regarding their extraction efficiency of phenolic compounds. Taking these results into consideration, we recommend using methanol as the extractor to isolate chlorogenic acid, fagopyrin, kaempferol, procyanidin B2, quercetin, quercetin 3-D-galactoside, rutin, vitexin, and water for other investigated polyphenolic substances obtained from Fagopyrum tataricum.     

Rainforest litter quality and chemical controls on leaf decomposition with near‐infrared spectrometry

Plant‐litter chemical quality is an important driver of many ecosystem processes, however, what actually constitutes high‐ or low‐quality litter (chemical potential for fast and slow decomposition, respectively) is often interpreted by the indices available. Here, near‐infrared spectroscopy (NIRS) was used to explore leaf‐litter chemical quality and the controls on decomposition in the tropical rainforest region of north Queensland Australia. Leaf‐litter samples from litterfall collections and litterbag studies were used. NIRS was used to calibrate the chemical compositions of the material (N, P, C, Mg, Ca, acid detergent fiber, acid detergent lignin, α‐cellulose, and total phenolics) from a smaller sample set covering the spectral range in the full set of samples. Calibrations were compared for both separate (local) and combined models, for litterbags, and litterfall. Coefficients of determination (r²) in the local models ranged from 0.88 (litterbag Mg) to 0.99 (litterfall N), with residual prediction deviation ratios > 3 for all constituents except Mg (≈ 2.5). Mass loss in the litterbags was strongly related to the NIR spectra, with model r²'s of 0.75 (in situ leaves) and 0.76 (common control leaf). In situ decomposability was determined from modeling the initial NIR spectra prior to decomposition with litterbag exponential‐decay rates (model r² of 0.81, n = 85 initial samples). A best subset model including litter‐quality, climate, and soil variables predicted decay better than the NIR decomposability model (r² = 0.87). For litter quality alone the NIR model predicted decay rate better than all of the best predictive litter–chemical quality indices. The decomposability model was used to predict in situ decomposability in the litterfall samples. The chemical variables explaining NIR decomposability for litterfall were initial P, C, and phenolics (linear model r² = 0.80, n = 2471). NIRS is a holistic technique that is just as, if not more accurate, than litter–chemical quality indices, when predicting decomposition and decomposability, shown here in a regional field study.     

Assessment of the socio-economic impacts associated with the arrival of apple snail (Pomacea canaliculata) in Mwea irrigation scheme,Kenya

Background

In Kenya, rice (Oryza sativa L.) is mainly produced under irrigation by small-scale farmers. Mwea irrigation scheme (MIS) in Kirinyaga County accounts for 80–88% of rice production. Here, rice is the main source of livelihood and a source of revenue generation for the county. However, a recently established invasive freshwater snail, Pomacea canaliculata (Lamarck) (family: Ampullariidae), a species of apple snail, presents a serious threat to rice production.

Results

Household surveys, focus group discussions and key informant interviews highlight apple snail as a serious problem in MIS. Households that observed at least a moderate level of infestation (>20% of cultivated area) experienced significant reductions in rice yield (~14%) and net rice income (~60%). Farmers reported increased use of chemical pesticides for management of apple snail. In addition, the cost of hired labor for physical removal of egg masses and snails is resulting in substantial negative effects on net income. Farmer age, area of land owned, responsibility for decision-making, receipt of extension advice, training, and membership of a farmer organization, were all statistically significant variables to explain farmers awareness of the need for area-wide apple snail management.

Conclusion

Strategies to limit the spread of apple snail are urgently needed. A Multi-Institutional Technical Team (MITT) has been established to spearhead management efforts and consolidate advice to farmers on how to manage apple snail. However, without action to mitigate spread, the consequences could be disastrous for rice production and food security in Kenya, and for other rice growing regions across Africa. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Classification of gilthead sea bream (Sparus aurata) from 1H NMR lipid profiling combined with principal component and linear discriminant analysis

The combination of (1)H NMR fingerprinting of lipids from gilthead sea bream (Sparus aurata) with nonsupervised and supervised multivariate analysis was applied to differentiate wild and farmed fish and to classify farmed specimen according to their areas of production belonging to the Mediterranean basin. Principal component analysis (PCA) applied on processed (1)H NMR profiles made a clear distinction between wild and farmed samples. Linear discriminant analysis (LDA) allowed classification of samples according to the geographic origin, as well as for the wild and farmed status using both PCA scores and NMR data as variables. Variable selection for LDA was achieved with forward selection (stepwise) with a predefined 5% error level. The methods allowed the classification of 100% of the samples according to their wild and farmed status and 85-97% to geographic origin. Probabilistic neural network (PNN) analyses provided complementary means for the successful discrimination among classes investigated.     

Risk factors for stillbirths in two swine farms in the south of Brazil

We evaluated stillbirth risk factors in two commercial swine farms of the Rio Grande do Sul State (south of Brazil). The study was conducted during 1 month in Farm A and during 2 months in Farm B, both during 1999. Data for all farrowings that occurred during the study period were recorded (101 for Farm A and 373 for Farm B), without interference in the farm management. In Farm A, 39% of all litters born during the period of interest had stillborn piglets and the stillborn risk for piglets was 12%. In Farm B, 25% of all litters had stillborn piglets whereas the stillborn risk was 2%. Variables considered as potential risk factors for stillbirths were: parity (1, 2–3, 4+); breed (purebred or crossbred); sow body-condition (normal or fat); use of oxytocin during parturition (yes or no); obstetric intervention through vaginal palpation (yes or no); farrowing duration (<4 or ≥4 h); mummified fetuses (yes or no); total litter size (<12 or ≥12 piglets); and litter birth weight (<11 or ≥11 kg). All stillborn piglets had their classification validated by necropsy. In multivariable logistic-regressions, the cases were the litters having at least one stillborn piglet. In Farm A, litters having at least 12 pigs and in which oxytocin was used during the parturition had 20.8-times-higher odds of stillborn occurrence. In Farm B, litters from sows having parity ≥4 had 2.2-times-higher odds of stillborn occurrence than litters from parity 2 to 3 females, litters having ≥12 pigs had 2.0-times-higher odds of a stillborn piglet than smaller litters and farrowings in which vaginal palpation was performed had 8.0-times-higher odds. Farrowing room management to minimize stillborn risk should target higher-parity females, large litters and optimization of practices of obstetric interventions.     

Evaluation of PCR,IEF and ELISA techniques for the detection and identification of potato cyst nematodes from field soil samples in England and Wales

Effective management of potato cyst nematodes (PCNs) requires simple, rapid and accurate identification and quantification of field populations. Soil samples from a survey of 484 fields in potato rotations in England and Wales were used to compare the identification and quantification of PCNs using IEF, PCR, ELISA and bait plant tests. The cyst counts and bait plant test revealed that 64.3% of field samples contained PCNs. Bait plant tests increased the detection rate of PCNs in field samples by 4–6.4%. This means that some infestations are cryptic and would not normally be detected by standard counts. IEF, PCR and ELISA methods distinguished between Globodera rostochiensis and G pallida and were able to register mixed populations; however they were not in full agreement. All methods suggested that G pallida is the dominant species in the field samples tested. The PCR results indicated that 66% of field samples contained pure G pallida, 8% contained pure G rostochiensis and 26% contained mixtures of the two species. Estimates of the relative process times taken per sample in the PCR, IEF and ELISA techniques are given. © 2001 Society of Chemical Industry