Sweetpotato, Ipomoea batatas (L.) Lam., is an important food crop worldwide.  Large scale evaluation of sweetpotato germplasm for genetic diversity is necessary to determine the genetic relationships between them and effectively use them in the genetic improvement.  In this study, the genetic diversity of 617 sweetpotato accessions, including 376 landraces and 162 bred varieties from China and 79 introduced varieties from 11 other countries, was assessed using 30 simple sequence repeat (SSR) primer pairs with high polymorphism.  Based on the population structure analysis, these sweetpotato accessions were divided into three groups, Group 1, Group 2 and Group 3, which included 228, 136 and 253 accessions, respectively.  Consistent results were obtained by phylogenic analysis and principal coordinate analysis (PCoA).  Of the three groups, Group 2 showed the highest level of genetic diversity and its accessions were mainly distributed in low-latitude regions.  The accessions from South China exhibited the highest level of genetic diversity, which supports the hypothesis that Fujian and Guangdong were the first regions where sweetpotato was introduced to China.  Analysis of molecular variance (AMOVA) indicated significant genetic differentiations between the different groups, but low levels of genetic differentiation existed between the different origins and accession types.  These results provide valuable information for the better utilization of these accessions in sweetpotato breeding.

This paper examined consumers’ experiences in and preferences for plant-based meat (PBM) food and their respective correlates, based on data from an online survey of 579 consumers in four major cities in China in early 2021.  We first described consumers’ experiences in consuming and purchasing PBM food and their correlates, and then analyzed consumer preferences using hypothetical choice experiment.  The experiment offered consumers various options to purchase burgers made from PBM or animal-based meat (ABM), combined with different countries of origin (COO), taste labels, and prices.  Our data showed that respondents hold overall positive attitudes toward PBM food; 85 and 82% of respondents reported experience in eating and purchasing PBM food, respectively.  More than half of them ate PBM food because they wanted to try new food (58%), or were interested in healthy food (56%).  Income, religion, and dietary restrictions were significantly correlated with consumers’ experiences in PBM food consumption.  Results from the Random Parameter Logit Model based on the hypothetical choice experiment data showed that 79% of respondents chose PBM burgers and were willing to pay an average of 88 CNY for a PBM burger.  We also found that 99.8 and 83% of respondents are willing to buy burgers made in China and those with a taste label, with a willingness to pay (WTP) of 208 and 120 CNY, respectively.  The heterogeneity test revealed that females and those with at least a bachelor’s degree, higher income, religious beliefs, and dietary restrictions are more likely to buy PBM burgers than their counterparts

Both the additive and multiplicative models of crop yield and water supply are polynomial equations, and the number of parameters increases linearly when the growing period is specified.  However, interactions among multiple parameters occasionally lead to unreasonable estimations of certain parameters, which were water sensitivity coefficients but with negative value.  Additionally, evapotranspiration must be measured as a model input.  To facilitate the application of these models and overcome the aforementioned shortcomings, a simple model with only three parameters was derived in this paper based on certain general quantitative relations of crop yield (Y) and water supply (W).  The new model, Y/Y_m–W^k/(W^k+w_h^k), fits an S or a saturated curve of crop yield with the cumulative amount of water.  Three parameters are related to biological factors: the yield potential (Y_m), the water requirement to achieve half of the yield potential (half-yield water requirement, w_h), and the water sensitivity coefficient (k).  The model was validated with data from 24 maize lines obtained in the present study and 17 maize hybrids published by other authors.  The results showed that the model was well fit to the data, and the normal root of the mean square error (NRMSE) values were 2.8 to 17.8% (average 7.2%) for the 24 maize lines and 2.7 to 12.7% (average 7.4%) for the 17 maize varieties.  According to the present model, the maize water-sensitive stages in descending order were pollen shedding and silking, tasselling, jointing, initial grain ?lling, germination, middle grain ?lling, late grain ?lling, and end of grain ?lling.  This sequence was consistent with actual observations in the maize field.  The present model may be easily used to analyse the water use efficiency and drought tolerance of maize at specific stages.

The normalization of quantitative real-time PCR (qPCR) is important to obtain accurate gene expression data, and the most common method for qPCR normalization is to use reference genes. However, reference genes can be regulated under different conditions. qPCR has recently been used for gene expression study in Laodelphax striatellus, but there is no study on validation of the reference genes. In this study, five new housekeeping genes (LstrTUB1, LstrTUB2, LstrTUB3, LstrARF and LstrRPL9) in L. striatellus were cloned and deposited in the GenBank with accession numbers of JF728809, JF728810, JF728811, JF728807 and JF728806, respectively. Furthermore, mRNA expressions of the five genes and β-actin were measured by qPCR with insect samples of different instar at nymph stage, and the expression stabilities were determined by the software geNorm and NormFinder. As a result, ARF and RPL9 were consistently more stable than β-actin, while three TUB genes were less stable than β-actin. To determine the optimal number of reference genes used in qPCR, a pairwise variations analysis by geNorm indicated that two references ARF and RPL9 were required to obtain the accurate quantification. These results were further confirmed by the validation qPCR experiment with chitinase gene as the target gene, in which the standard error of the mRNA quantification by using binary reference ARF-RPL9 was much lower than those by ARF, RPL9 or β-actin alone. Taken together, our study suggested that the combination of ARF-RPL9 could replace β-actin as the reference genes for qPCR in L. striatellus.

Salt stress is a global constraint on agricultural production.  Therefore, the development of salt tolerant plants has become a current research hotspot. Salt tolerance evolves more frequently in C₄ grass lineages.  However, few studies have been carried out to explore the molecular bases underlying salt stress tolerance in C₄ crop foxtail millet.  In this study, we performed a multi-pronged approach spanning the omics analyses of transcriptomes and physiological analysis of C₃ crop rice and C₄ model crop foxtail millet in response to salt stress.  Our results revealed specifically compared to C₃ rice, C₄ foxtail millet has upregulated ABA and notably reduced CK biosynthesis and signaling transduction under salt stress.  Salt stress in C₃ rice plants triggered rapid downregulation of photosynthesis related genes, which was coupled by severely decreased net photosynthetic rates.  In the salt-threatened C₃ rice and C₄ foxtail millet, some stress responsive transcription factors (TFs), such as AP2/ERF, WRKY and MYB underwent strong and distinct transcriptional changes.  Based on weighted gene co-expression network analysis (WGCNA), an AP2/ERF transcription factor Rice Starch Regulator1 SiRSR1 (Seita.3G044600) was identified as a key regulator of salt stress response.  To confirmed its function, we generated OsRSR1-knockout lines with CRISPR/Cas9 genome editing in rice and its upstream repressor SiMIR172a-overexpressing (172a-OE) transgenic plants in foxtail millet, which increased salt tolerance.  Overall, our study not only provided new insights into the convergent regulation of salt stress responses of foxtail millet and rice, but also shed light on the divergent signaling networks between them in response to salt stress.