Expression Profiles and Biochemical Analysis of Chemosensory Protein 3 from Nilaparvata lugens (Hemiptera: Delphacidae).

Insects have evolved highly sensitive olfactory sensory systems to detect plant hosts and mates, with plant volatiles playing an important role in informing insect behavior. Chemosensory proteins (CSPs) are thought to play a key role in this process, but in this respect, there is limited information on brown planthopper Nilaparvata lugens, one of the most destructive pests of rice. To expand our understanding of CSP function in N. lugens we explored expression profiles and binding characteristics of NlugCSP3. The ligands with higher binding affinity were also validated by molecular docking and behavioral assays. NlugCSP3 mRNA was expressed at relatively higher levels in antennae and abdomen of 3-day-old unmated macropterous males as well as in antennae of 3-day mated macropterous and brachypterous females. Fluorescence competitive binding assays revealed that 5 out of 25 candidate volatiles are strong binders (Ki < 10 µM). Behavioral assays revealed that nonadecane and 2-tridecanone, which have high binding affinities in fluorescence competition-binding assays, displayed strong attractiveness to N. lugens. Pursuing this further, molecular docking analysis identified key amino acid residues involved in binding volatile compounds. Overall, our data provide a base for further investigation of the potential physiological functions of CSP3 in Nilaparvata lugens, and extend the function of NlugCSP3 in chemoreception of N. lugens.

High-throughput phenotyping of nutritional quality components in sweet potato roots by near-infrared spectroscopy and chemometrics methods.

The lack of an efficient approach for quality evaluation of sweet potatoes significantly hinders progress in quality breeding. Therefore, this study aimed to establish a near-infrared spectroscopy (NIRS) assay for high-throughput analysis of sweet potato root quality, including total starch, amylose, amylopectin, the ratio of amylopectin to amylose, soluble sugar, crude protein, total flavonoid content, and total phenolic content. A total of 125 representative samples were utilized and a dual-optimized strategy (optimization of sample subset partitioning and variable selection) was applied to NIRS modeling. Eight optimal equations were developed with an excellent coefficient of determination for the calibration (R2C) at 0.95-0.99, cross-validation (R2CV) at 0.93-0.98, external validation (R2V) at 0.89-0.96, and the ratio of prediction to deviation (RPD) at 6.33-11.35. Overall, these NIRS models provide a feasible approach for high-throughput analysis of root quality and permit large-scale screening of elite germplasm in future sweet potato breeding.

Evaluation of Different Shallow Groundwater Tables and Alfalfa Cultivars for Forage Yield and Nutritional Value in Coastal Saline Soil of North China.

Freshwater shortage and soil salinization are the major constraints for alfalfa (Medicago sativa L.) growth in coastal salt-alkali soil of North China. In this study, we analyzed the effects of shallow groundwater tables and alfalfa cultivars on forage yield and nutritional value. A field simulation experiment was conducted during the growing season of 2019-2021 with three groundwater depths (80, 100, and 120 cm) and five alfalfa cultivars (Magnum 551, Phabulous, Zhongmu No. 1, Zhongmu No. 3, and WL525HQ) under subsurface pipe systems. Alfalfa forage was harvested six times in total during the growing season. Results revealed significant variation among alfalfa cultivars for forage yield at each shallow groundwater depth. The greatest forage yield was recorded in cultivar Phabulous (32.2 and 35.9 t ha-1 in 2020 and 2021) when planted at 100 cm shallow groundwater depth. Forage yield during the first harvest was 24.6-25.7%, exhibiting the highest ratio of the total annual yield. The effects of shallow groundwater depth, cultivar, and their interaction were significant (p < 0.01) on the turn-green ratio of alfalfa. Cultivar Zhongmu No. 1 had the highest turn-green ratio at the 100 cm groundwater depth, while cultivar WL525HQ showed the lowest turn-green ratio at each groundwater depth. Moreover, crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF) content were also significantly affected by shallow groundwater depth, cultivars, and their interaction at different harvests. Cultivars Magnum551, Zhongmu No. 1, Zhongmu No. 3, and Phabulous furnished the highest CP, while cultivar WL525HQ performed the poorest in terms of CP in this study. These results propose that planting the cultivar Phabulous at a groundwater depth of 100 cm could be a suitable agronomic practice for alfalfa forage production in the coastal salt-alkali area of North China.

Dynamics of Spring Regrowth and Comparative Production Performance of 50 Autumn-Sown Alfalfa Cultivars in the Coastal Saline Soil of North China.

Alfalfa (Medicago sativa L.) production is affected by many factors, including management practices, soil conditions, and the environmental elements of the target area. Varietal differences, in terms of agronomic performance and forage yield, among 50 alfalfa cultivars under six harvest systems following regrowth were evaluated during the growing season of 2019-2020 under non-irrigated rainfed conditions in a coastal saline-alkali soil region of North China. Days to harvesting, plant height, canopy area, growth rate, and forage yield were assessed to rank the cultivars. Furthermore, the key factor influencing the regrowth of the second year after over-wintering was identified based on the growth status before over-wintering by using the Boston Matrix method. Results showed significant (p < 0.05) differences among cultivars and harvests regarding plant height, canopy area, and forage yield. Alfalfa forage yield ranged between 24.2 t ha-1 yr-1 and 32.7 t ha-1 yr-1. The highest forage yield was obtained in cultivar Guochan No.1, and was lowest in cultivar Magnum 601. Forage yield reached the greatest values for the first harvest, and then decreased gradually and changed stably. The forage yield of the third, fourth, fifth, and sixth harvest ranged from 3.4 t ha-1 to 4.3 t ha-1 (averaged across 50 cultivars), which represented 10.8% to 15.2% of the annual total forage production. We also observed that forage yield correlated strongly, but negatively, with the growth rate. According to subordinate function value analysis, Womu No.1, WL440HQ, Weston, Surprise, and WL354HQ proved optimum cultivars for general cultivation in this coastal area. In future, development of alfalfa cultivars with improved regrowth and tolerance to heavy saline-alkali soil and early spring drought would be necessary to increase forage yield under rainfed conditions in coastal saline-alkali areas of North China.

Silencing of Chemosensory Protein Gene NlugCSP8 by RNAi Induces Declining Behavioral Responses of Nilaparvata lugens.

Chemosensory proteins (CSPs) play imperative functions in chemical and biochemical signaling of insects, as they distinguish and transfer ecological chemical indications to a sensory system in order to initiate behavioral responses. The brown planthopper (BPH), Nilaparvata lugens Stål (Hemiptera: Delphacidae), has emerged as the most destructive pest, causing serious damage to rice in extensive areas throughout Asia. Biotic characteristics like monophagy, dual wing forms, and annual long-distance migration imply a critical role of chemoreception in N. lugens. In this study, we cloned the full-length CSP8 gene from N. lugens. Protein sequence analysis indicated that NlugCSP8 shared high sequence resemblance with the CSPs of other insect family members and had the typical four-cysteine signature. Analysis of gene expression indicated that NlugCSP8 mRNA was specifically expressed in the wings of mated 3-day brachypterous females with a 175-fold difference compare to unmated 3-day brachypterous females. The NlugCSP8 mRNA was also highly expressed in the abdomen of unmated 5-day brachypterous males and correlated to the age, gender, adult wing form, and mating status. A competitive ligand-binding assay demonstrated that ligands with long chain carbon atoms, nerolidol, hexanal, and trans-2-hexenal were able to bind to NlugCSP8 in declining order of affinity. By using bioinformatics techniques, three-dimensional protein structure modeling and molecular docking, the binding sites of NlugCSP8 to the volatiles which had high binding affinity were predicted. In addition, behavioral experiments using the compounds displaying the high binding affinity for the NlugCSP8, revealed four compounds able to elicit significant behavioral responses from N. lugens. The in vivo functions of NlugCSP8 were further confirmed through the testing of RNAi and post-RNAi behavioral experiments. The results revealed that reduction in NlugCSP8 transcript abundance caused a decrease in behavioral response to representative attractants. An enhanced understanding of the NlugCSP8 is expected to contribute in the improvement of more effective and eco-friendly control strategies of BPH.

Natural and synthetic estrogens in leafy vegetable and their risk associated to human health.

Since the inception of global industrialization, the growth of steroid estrogens becomes a matter of emerging serious concern for the rapid population. Steroidal estrogens are potent endocrine-upsetting chemicals that are excreted naturally by vertebrates (e.g., humans and fish) and can enter natural waters through the discharge of treated and raw sewage. Steroidal estrogens in plants may enter the food web and become a serious threat to human health. We evaluated the uptake and accumulation of ethinylestradiol (EE2) and 17ß-estradiol (17ß-E2) in lettuce plants (Lactuca sativa) grown under controlled environmental condition over 21 days growth period. An effective analytical method based on ultrasonic liquid extraction (ULE) for solid samples and solid phase extraction (SPE) for liquid samples with gas chromatography-mass spectrometry (GC/MS) has been developed to determine the steroid estrogens in lettuce plants. The extent of uptake and accumulation was observed in a dose-dependent manner and roots were major organs for estrogen deposition. Unlike the 17ß-E2, EE2 was less accumulated and translocated from root to leaves. For 17ß-E2, the distribution in lettuce was primarily to roots after the second week (13%), whereas in leaves it was (10%) over the entire study period. The distribution of EE2 at 2000 µg L-1 in roots and leaves was very low (3.07% and 0.54%) during the first week and then was highest (12% in roots and 8% in leaves) in last week. Bioaccumulation factor values of 17ß-E2 and EE2 in roots were 0.33 and 0.29 at 50 µg L-1 concentration as maximum values were found at 50 µg L-1 rather than 500 and 2000 in all observed plant tissues. Similar trend was noticed in roots than leaves for bioconcentration factor as the highest bioconcentration values were observed at 50 µg L-1 concentration instead of 500 and 2000 µg L-1 spiked concentration. These findings mainly indicate the potential for uptake and bioaccumulation of estrogens in lettuce plants. Overall, the estrogen contents in lettuce were compared to the FAO/WHO recommended toxic level and were found to be higher than the toxic level which is of serious concern to the public health. This analytical procedure may aid in future studies on risks associated with uptake of endocrine-disrupting chemicals in lettuce plants.

Optimizing the phosphorus use in cotton by using CSM-CROPGRO-cotton model for semi-arid climate of Vehari-Punjab, Pakistan.

Crop nutrient management is an essential component of any cropping system. With increasing concerns over environmental protection, improvement in fertilizer use efficiencies has become a prime goal in global agriculture system. Phosphorus (P) is one of the most important nutrients, and strategies are required to optimize its use in important arable crops like cotton (Gossypium hirsutum L.) that has great significance. Sustainable P use in crop production could significantly avoid environmental hazards resulting from over-P fertilization. Crop growth modeling has emerged as an effective tool to assess and predict the optimal nutrient requirements for different crops. In present study, Decision Support System for Agro-technology Transfer (DSSAT) sub-model CSM-CROPGRO-Cotton-P was evaluated to estimate the observed and simulated P use in two cotton cultivars grown at three P application rates under the semi-arid climate of southern Punjab, Pakistan. The results revealed that both the cultivars performed best at medium rate of P application (57 kg ha-1) in terms of days to anthesis, days to maturity, seed cotton yield, total dry matter production, and harvest index during 2013 and 2014. Cultivar FH-142 performed better than MNH-886 in terms of different yield components. There was a good agreement between observed and simulated days to anthesis (0 to 1 day), days to maturity (0 to 2 days), seed cotton yield, total dry matter, and harvest index with an error of -4.4 to 15%, 12-7.5%, and 13-9.5% in MNH-886 and for FH-142, 4-16%, 19-11%, and 16-8.3% for growing years 2013 and 2014, respectively. CROPGRO-Cotton-P would be a useful tool to forecast cotton yield under different levels of P in cotton production system of the semi-arid climate of Southern Punjab.