Improving the tolerance of crop species to abiotic stresses that limit plant growth and productivity is essential for mitigating the emerging problems of global warming. In this context, imaged data analysis represents an effective method in the 4.0 technology era, where this method has the non-destructive and recursive characterization of plant phenotypic traits as selection criteria. So, the plant breeders are helped in the development of adapted and climate-resilient crop varieties. Although image-based phenotyping has recently resulted in remarkable improvements for identifying the crop status under a range of growing conditions, the topic of its application for assessing the plant behavioral responses to abiotic stressors has not yet been extensively reviewed. For such a purpose, bibliometric analysis is an ideal analytical concept to analyze the evolution and interplay of image-based phenotyping to abiotic stresses by objectively reviewing the literature in light of existing database. Bibliometricy, a bibliometric analysis was applied using a systematic methodology which involved data mining, mining data improvement and analysis, and manuscript construction. The obtained results indicate that there are 554 documents related to image-based phenotyping to abiotic stress until 5 January 2023. All document showed the future development trends of image-based phenotyping will be mainly centered in the United States, European continent and China. The keywords analysis major focus to the application of 4.0 technology and machine learning in plant breeding, especially to create the tolerant variety under abiotic stresses. Drought and saline become an abiotic stress often using image-based phenotyping. Besides that, the rice, wheat and maize as the main commodities in this topic. In conclusion, the present work provides information on resolutive interactions in developing image-based phenotyping to abiotic stress, especially optimizing high-throughput sensors in image-based phenotyping for the future development.

Agroforestry is often seen as a sustainable land-use system for agricultural production providing ecosystem services. Intercropping with food crops leads to equal or higher productivity than monoculture and results in food production for industry and subsistence. Low rubber price and low labor productivity in smallholdings have led to a dramatic conversion of rubber plantations to more profitable crops. The literature analysis performed in this paper aimed at better understanding the ins and outs that could make rubber-based agroforestry more attractive for farmers. A comprehensive search of references was conducted in March 2023 using several international databases and search engines. A Zotero library was set up consisting of 415 scientific references. Each reference was carefully read and tagged in several categories: cropping system, country, main tree species, intercrop type, intercrop product, level of product use, discipline of the study, research topic, and intercrop species. Of the 232 journal articles, 141 studies were carried out on rubber agroforestry. Since 2011, the number of studies per year has increased. Studies on rubber-based agroforestry systems are performed in most rubber-producing countries, in particular in Indonesia, Thailand, China, and Brazil. These studies focus more or less equally on perennials (forest species and fruit trees), annual intercrops, and mixed plantations. Of the 47 annual crops associated with rubber in the literature, 20 studies dealt with rice, maize, banana, and cassava. Agronomy is the main discipline in the literature followed by socio-economy and then ecology. Only four papers are devoted to plant physiology and breeding. The Discussion Section has attempted to analyze the evolution of rubber agroforestry research, progress in the selection of food crop varieties adapted to agroforestry systems, and to draw some recommendations for rubber-based agroforestry systems associated with food crops.

Background: Soybean productivity in Indonesia remains low yield due to the occurrence of pests and diseases. Here, our study aimed to determine the number of soybean rows and varieties in the soybean-corn intercropping system and the damage level, pest and predator populations. Methods: The study used a split-plot design with three replications. The main plot was soybean varieties (Dena-1, Detap-1 and Deja-1) and the subplots consisted of monoculture (soybean); three rows of soybeans and two rows of corn; four rows of soybean and two rows of corn; six rows of soybean and two rows of corn. Result: The six rows of soybeans and two rows of corn showed the lowest attack rate of Spodoptera litura and Etiella zinckenella, the lowest population of Aphis glycines and Riptortus linearis, the highest predatory population of Crocothemis servilia and Coccinella sp. and the highest predator populations of Euborellia annulata. The highest attack rate of S.litura was in Dena-1. In contrast, the highest intensity of E.zinckenella pest damage was in Dena-1 and Deja-1. The corn-soybean intercropping was recommended as the best practice for sustainable agriculture production due to facilitating in the increase of growth of predator population and reducing the level of crop damage due to pest attacks.