Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat.

Unmanned aerial vehicle (UAV) based remote sensing is a promising approach for non-destructive and high-throughput assessment of crop water and nitrogen (N) efficiencies. In this study, UAV was used to evaluate two field trials using four water (T0 = 0 mm, T1 = 80 mm, T2 = 120 mm, and T3 = 160 mm), and four N (T0 = 0, T1 = 120 kg ha-1, T2 = 180 kg ha-1, and T3 = 240 kg ha-1) treatments, respectively, conducted on three wheat genotypes at two locations. Ground-based destructive data of water and N indictors such as biomass and N contents were also measured to validate the aerial surveillance results. Multispectral traits including red normalized difference vegetation index (RNDVI), green normalized difference vegetation index (GNDVI), normalized difference red-edge index (NDRE), red-edge chlorophyll index (RECI) and normalized green red difference index (NGRDI) were recorded using UAV as reliable replacement of destructive measurements by showing high r values up to 0.90. NGRDI was identified as the most efficient non-destructive indicator through strong prediction values ranged from R 2 = 0.69 to 0.89 for water use efficiencies (WUE) calculated from biomass (WUE.BM), and R 2 = 0.80 to 0.86 from grain yield (WUE.GY). RNDVI was better in predicting the phenotypic variations for N use efficiency calculated from nitrogen contents of plant samples (NUE.NC) with high R 2 values ranging from 0.72 to 0.94, while NDRE was consistent in predicting both NUE.NC and NUE.GY by 0.73 to 0.84 with low root mean square errors. UAV-based remote sensing demonstrates that treatment T2 in both water 120 mm and N 180 kg ha-1 supply trials was most appropriate dosages for optimum uptake of water and N with high GY. Among three cultivars, Zhongmai 895 was highly efficient in WUE and NUE across the water and N treatments. Conclusively, UAV can be used to predict time-series WUE and NUE across the season for selection of elite genotypes, and to monitor crop efficiency under varying N and water dosages.

Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat.

BACKGROUND: Plant height is an important selection target since it is associated with yield potential, stability and particularly with lodging resistance in various environments. Rapid and cost-effective estimation of plant height from airborne devices using a digital surface model can be integrated with academic research and practical wheat breeding programs. A bi-parental wheat population consisting of 198 doubled haploid lines was used for time-series assessments of progress in reaching final plant height and its accuracy was assessed by quantitative genomic analysis. UAV-based data were collected at the booting and mid-grain fill stages from two experimental sites and compared with conventional measurements to identify quantitative trait loci (QTL) underlying plant height. RESULTS: A significantly high correlation of R 2 = 0.96 with a 5.75 cm root mean square error was obtained between UAV-based plant height estimates and ground truth observations at mid-grain fill across both sites. Correlations for UAV and ground-based plant height data were also very high (R 2 = 0.84-0.85, and 0.80-0.83) between plant height at the booting and mid-grain fill stages, respectively. Broad sense heritabilities were 0.92 at booting and 0.90-0.91 at mid-grain fill across sites for both data sets. Two major QTL corresponding to Rht-B1 on chromosome 4B and Rht-D1 on chromosome 4D explained 61.3% and 64.5% of the total phenotypic variations for UAV and ground truth data, respectively. Two new and stable QTL on chromosome 6D seemingly associated with accelerated plant growth was identified at the booting stage using UAV-based data. Genomic prediction accuracy for UAV and ground-based data sets was significantly high, ranging from r = 0.47-0.55 using genome-wide and QTL markers for plant height. However, prediction accuracy declined to r = 0.20-0.31 after excluding markers linked to plant height QTL. CONCLUSION: This study provides a fast way to obtain time-series estimates of plant height in understanding growth dynamics in bread wheat. UAV-enabled phenotyping is an effective, high-throughput and cost-effective approach to understand the genetic basis of plant height in genetic studies and practical breeding.

Assessing the prevalence and economic significance of coccidiosis individually and in combination with concurrent infections in Pakistani commercial poultry farms.

Coccidiosis is one of the most economically important diseases of the poultry, around the globe. In order to assess seasonal and age-wise prevalence of coccidiosis individually and with concurrent infections, this study was conducted on commercial poultry farms in and around Multan division, province of Punjab, Pakistan. A total of 28,126 boilers, 4,052 layers and 7,699 golden bird samples, provided by regional farmers and consultants, were examined by microscopy for the diagnosis of coccidiosis. Based on postmortem lesions, several infections including coccidiosis, viral, and miscellaneous diseases were catalogued, whereas samples were cultured to identify concurrent bacterial diseases. Cumulative analysis of this large set of samples revealed a prevalence of 14.16, 11.01, and 19.57% in broiler, layer and golden birds, respectively. Ascaridia galli (A. galli) showed a higher prevalence in layer (2.47%) compared to golden (0.21%) birds (P < 0.01). Amongst all concurrent infections investigated, bacterial infections were identified in highest percentage of samples (59.24%; P < 0.05). The age-wise and season-wise prevalence of coccidiosis and A. galli was found to be significant (P < 0.05). During the study period, an estimated of 10.69 (coccidiosis) and 0.29 (A. galli) million poultry birds were treated or provided prophylaxis and supportive therapy at Pakistani commercial poultry farms. Depending upon the prevailing market conditions, the total economic losses (treatment, prophylaxis, and supportive therapy) from coccidiosis and A. galli were estimated to be US $45,405.00 and 2,638.50, respectively, while production (weight and eggs) losses for broiler (US$ 2,750,779.00), layer and golden, young (US$ 13,974.98 and 50,228.76) and adult (US$ 104.74 and 203.77) were estimated. Unit loss of coccidiosis with concurrent diseases and intestinal worm was estimated to be US$ 0.005 and 0.01, respectively. These results highlight the potential impact of coccidiosis individually and with concurrent infections on the poultry productivity and will inform farmers, policy makers, and other governmental and non-governmental stakeholders on the use of control and management measures in containing these infections.

A systematic review on modelling approaches for economic losses studies caused by parasites and their associated diseases in cattle.

Parasites reside inside or outside their hosts and get host nutrition and blood. Here, we have emphasized economic losses in cattle caused by parasitic diseases due to ecto- and endo- parasites (flies, ticks, mites and helminths). We have outlined different methods/models including economic evaluation techniques and dynamic analysis as a major class, used for the calculation of economic losses caused by parasites in cattle. According to already conducted studies, a decrease in production is mentioned in quantity and percentage while financial losses are expressed in the form of account with respect to per head, herd or for the specific study area. The parasites cause the reduced production and financial losses due to control, treatment and mortality costs. We calculated the average decrease in milk production and organ condemnation as 1.16 L animal-1 day-1 and 12.95%, respectively, from overall cattle parasitic infections. Moreover, the average calculated financial and percentage losses were US$ 50.67 animal-1 year-1 and 17.94%, respectively. Economically important parasitic diseases mentioned here are caused by specific spp. of protozoans and helminths according to data collected from the literature. Protozoan diseases include tick-borne diseases, coccidiosis, neosporosis, trypanosomiasis and cryptosporidiosis. Losses due to tick-borne infections were encountered for decreased milk production, mortality, treatment and control. Losses from coccidiosis were due to decreased weight gain, treatment costs and mortality. While abortion losses were encountered in neosporosis. Trypanosomiasis caused losses due to a decrease in milk yield. Moreover, only diagnostic (conventional or molecular techniques) cost was taken into account for cryptosporidiosis. Economically important nematode parasites are Oesophagostomum spp., Cooperia spp., Trichostrongylus spp., Strongyloides spp., Ostertagia spp. and Haemonchus placei. Due to the zoonotic importance of echinococcosis, Echinococcus granulosus is the most economically important cestode parasite. Losses caused by echinococcosis were due to organ condemnation, carcass weight loss and decreases hide value, milk production and fecundity. While, fascioliasis is one of the most economically important trematodal disease, which causes cirrhosis of the liver due to parasite migration, and thus, the organ becomes inedible. So, it would be helpful for farmers and researchers to approach these methods/models for calculation of parasitic losses and should adopt suitable measures to avoid long-term economic losses.