The ability of different germplasm to adapt to a saline–alkali environment is critical to learning about the tolerance mechanism of saline–alkali stress in plants. Flax is an important oil and fiber crop in many countries. However, its molecular tolerance mechanism under saline stress is still not clear. In this study, we studied morphological, physiological characteristics, and gene expression variation in the root and leaf in oil and fiber flax types under saline stress, respectively. Abundant differentially expressed genes (DEGs) induced by saline stress, tissue/organ specificity, and different genotypes involved in plant hormones synthesis and metabolism and transcription factors and epigenetic modifications were detected. The present report provides useful information about the mechanism of flax response to saline stress and could lead to the future elucidation of the specific functions of these genes and help to breed suitable flax varieties for saline/alkaline soil conditions.

From connected sensors in soils, on animals or crops, and on drones, to various software and services that are available, “smart” technologies are changing the way farming is carried out. These technologies allow producers to look beyond what the eye can see by collecting non-traditional data and then using analytics tools to improve both food sustainability and profitability. “Smart Agriculture/farming” (SA) or “Digital Agriculture” (DA), often used interchangeably, refer to precision agriculture that is thus connected in a network of sensing and acting. It is a concept that employs modern information technologies, precision climate information, and crop/livestock developmental information to connect production variables to increase the quantity and quality of agricultural and food products. This is achieved by measuring and analyzing variables accurately, feeding the information into the cloud from edge devices, extracting trends from the various data, and subsequently providing information back to the producer in a timely manner. Smart agriculture covers many disciplines, including biology, mechanical engineering, automation, machine learning, artificial intelligence, and information technology-digital platforms. Minimum standards have been proposed for stakeholders with the aim to move toward this highly anticipated and ever-changing revolution. These foundational standards encompass the following general categories, including precise articulation of objectives, and baseline standards for the Internet of Things (IoT), including network infrastructure (e.g., stable 4G or 5G networks or a wireless local area network (WLAN) are available to end users). To sum up, SA aims to improve production efficiency, enhance the quality and quantity of agricultural products, reduce costs, and improve the environmental footprint of the industry. SA’s ecosystem should be industry self-governed and collaboratively financed. SA stakeholders and end-users’ facilities should meet standard equipment requirements, such as sensor accuracy, end data collectors, relevant industry compliant software, and trusted data analytics. The SA user is willing to be part of the SA ecosystem. This short perspective aims to summarize digital/smart agriculture concept in plain language.

In recent years, the Sanjiang Plain has experienced drastic human activities, which have dramatically changed its ecological environment. Soil microorganisms can sensitively respond to changes in soil quality as well as ecosystem function. In this study, we investigated the changes in soil microbial community diversity and composition of three typical land use types (forest, wetland and cropland) in the Sanjiang Plain using phospholipid fatty acid analysis (PLFA) technology, and 114 different PLFA compounds were identified. The results showed that the soil physicochemical properties changed significantly (p < 0.05) among the different land use types; the microbial diversity and abundance in cropland soil were lower than those of the other two land use types. Soil pH, soil water content, total organic carbon and available nitrogen were the main soil physico-chemical properties driving the composition of the soil microbial community. Our results indicate that the soil microbial community response to the three different habitats is complex, and provide ideas for the mechanism by which land use changes in the Sanjiang Plain affect the structure of soil microbial communities, as well as a theoretical basis for the future management and sustainable use of the Sanjiang plain, in the northeast of China.

The wetlands in China’s Sanjiang Plain have experienced intensive anthropogenic disturbance recently, and this has obviously changed their environmental characteristics. Soil microorganisms play an important role in wetland ecosystems. However, the effects of different wetland types on soil microbial diversity and community composition remain largely unclear. Therefore, we assessed the effects of three typical wetland types—permanently flooded wetlands, seasonally flooded wetlands and non-flooded wetlands—on soil microbial communities in the Sanjiang Plain, using phospholipid fatty acid analysis (PLFA) technology. A total of 56 different PLFA compounds were identified, of which 10 are typically produced by uncharacterized bacteria, 15 by Gram-positive bacteria, and 11 by Gram-negative bacteria. In addition, 2 fungal groups were identified, based on four PLFAs, and four PLFAs typical for protozoa were detected. High levels were detected for 16:0 (attributed to bacteria) and i17:1ω9c (produced by Gram-positive bacteria). The latter (i17:1ω9c) was exceptionally high in non-flooded soil (8407.15 ± 2675.84 ng/g). High levels of 18:1ω7c (1939.15 ± 666.13 ng/g) and 18:1ω9c (1713.26 ± 360.65 ng/g) were detected in permanently flooded wetlands and about the same in seasonally flooded wetlands, but lower ranks were present in the drier non-flooded wetlands. The Shannon-Wiener diversity index decreased with permanently flooded wetlands (3.05) > seasonally flooded wetlands (3.02) > non-flooded wetlands (2.12). Redundancy analysis showed that the two axes could explain a total of 94.48% of soil microbial communities. Soil water content, total and available phosphorus, and total and available nitrogen correlated significantly with soil microbial communities of three wetland types. Cluster analysis of correlations between individual PLFA biomarkers and soil physiochemical properties demonstrated the complexity of the community responses to the three different habitats. This study demonstrates that microbial diversity and composition changed sensitivity among the three wetland types, and soil moisture content was the key environmental factor to affect the soil microbial communities.

N deposition is a key factor affecting the composition and function of soil microbial communities in wetland ecosystems. Previous studies mainly focused on the effects of N deposition in the soil during the growing season (summer and autumn). Here, we focused on the response of the soil microbial community structure and function in winter. Soil from the Sanjiang Plain wetland, China, that had been treated for the past 11 years by using artificial N deposition at three levels (no intervention in N0, N deposition with 4 g N m⁻² yr⁻¹ in N1, and with 8 g N m⁻² yr⁻¹ in N2). Soil characteristics were determined and the bacterial composition and function was characterized using high-throughput sequence technology. The N deposition significantly reduced the soil bacterial diversity detected in winter compared with the control N0, and it significantly changed the composition of the bacterial community. At the phylum level, the high N deposition (N2) increased the relative abundance of Acidobacteria and decreased that of Myxococcota and Gemmatimonadota compared with N0. In soil from N2, the relative abundance of the general Candidatus_Solibacter and Bryobacter was significantly increased compared with N0. Soil pH, soil organic carbon (SOC), and total nitrogen (TN) were the key factors affecting the soil bacterial diversity and composition in winter. Soil pH was correlated with soil carbon cycling, probably due to its significant correlation with aerobic_chemoheterotrophy. The results show that a long-term N deposition reduces soil nutrients in winter wetlands and decreases soil bacterial diversity, resulting in a negative impact on the Sanjiang plain wetland. This study contributes to a better understanding of the winter responses of soil microbial community composition and function to the N deposition in temperate wetland ecosystems.