Plant growth and development are controlled by a delicate balance of hormonal cues. Growth-promoting hormones and growth-inhibiting counterparts often antagonize each other in their action, but the molecular mechanisms underlying these events remain largely unknown. Here, we report a cross-talk mechanism that enables a receptor-like kinase, FERONIA ( FER ), a positive regulator of auxin-promoted growth, to suppress the abscisic acid (ABA) response through activation of ABI2 , a negative regulator of ABA signaling. The FER pathway consists of a FER kinase interacting with guanine exchange factors GEF1, GEF4, and GEF10 that, in turn, activate GTPase ROP11/ARAC10. Arabidopsis mutants disrupted in any step of the FER pathway, including fer, gef1gef4gef10 , or rop11/arac10 , all displayed an ABA-hypersensitive response, implicating the FER pathway in the suppression mechanism. In search of the target for the FER pathway, we found that the ROP11/ARAC10 protein physically interacted with the ABI2 phosphatase and enhanced its activity, thereby linking the FER pathway with the inhibition of ABA signaling.

Although abscisic acid (ABA) is an important hormone that regulates seed dormancy, stomatal closure, plant development, as well as responses to environmental stimuli, the physiological mechanisms of ABA response to multiple stress in rice remain poorly understood. In the ABA biosynthetic pathway, 9-cis-epoxycarotenoid dioxygenase (NCED) is the key rate-limiting enzyme. Here, we report important functions of OsNCED3 in multi-abiotic stress tolerance in rice. The OsNCED3 is constitutively expressed in various tissues under normal condition, Its expression is highly induced by NaCl, PEG, and H₂O₂ stress, suggesting the roles for OsNCED3 in response to the multi-abiotic stress tolerance in rice. Compared with wild-type plants, nced3 mutants had earlier seed germination, longer post-germination seedling growth, increased sensitivity to water stress and H₂O₂ stress and increased stomata aperture under water stress and delayed leaf senescence. Further analysis found that nced3 mutants contained lower ABA content compared with wild-type plants, overexpression of OsNCED3 in transgenic plants could enhance water stress tolerance, promote leaf senescence and increase ABA content. We conclude that OsNCED3 mediates seed dormancy, plant growth, abiotic stress tolerance, and leaf senescence by regulating ABA biosynthesis in rice; and may provide a new strategy for improving the quality of crop.

Excessive cadmium (Cd) accumulation in grains of rice (Oryza sativa L.) is a risk to food security. The transporters in the nodes of rice are involved in the distribution of mineral elements including toxic elements to different tissues such as grains. However, the mechanism of Cd accumulation in grains is largely unknown. Here, we report a node-expressed transporter gene, OsCCX2, a putative cation/calcium (Ca) exchanger, mediating Cd accumulation in the grains of rice. Knockout of OsCCX2 caused a remarkable reduction of Cd content in the grains. Further study showed that disruption of this gene led to a reduced root-to-shoot translocation ratio of Cd. Moreover, Cd distribution was also disturbed in different levels of internode and leaf. OsCCX2 is localized to plasma membrane, and OsCCX2 is mainly expressed in xylem region of vascular tissues at the nodes. OsCCX2 might function as an efflux transporter, responsible for Cd loading into xylem vessels. Therefore, our finding revealed a novel Cd transporter involved in grain Cd accumulation, possibly via a Ca transport pathway in the nodes of rice.

The decisions made regarding traditional fish feeding systems mainly depend on experience and simple time control. Most previous works have focused on image-based analysis of the leftover feed at the bottom of the pond to determine whether to continue or to stop feeding. However, the feasibility of such a method in an actual outdoor aquaculture pond is low. The main reason for this is that real outdoor aquaculture ponds have turbid water quality, small feed targets, interference from intense fish activity, overlapping images of fish and feed, etc. Therefore, image-based recognition is not easy to implement in actual outdoor aquaculture. To overcome this problem, this article proposes an automatic fish feeding system based on deep learning computer vision technology. In contrast to traditional computer-vision-based systems for recognizing fish feed underwater, the proposed system uses deep learning technology to recognize the size of the waves caused by fish eating feed to determine whether to continue or to stop feeding. Furthermore, several water quality sensors are adopted to assist in feeding decisions. As a result, the proposed system uses deep learning technology to recognize the size of the water waves caused by fish eating feed to determine whether to continue to cast feed or to stop feeding. Experimental results show that an accuracy of up to 93.2% can be achieved.