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.

Rice-fish cultivation, also known as Manipadi in Indonesia, is one of the many integrated farming systems where fish are grown concurrently with rice. However, this integrated system needs to be optimized by organic fertilizer. The application of organic fertilizers, such as compost and local biofertilizers, when implemented into this integrated system, can optimize the yield per land for both rice and fish. However, this combination must be evaluated systematically by multiple evaluation criteria and statistical analyses. Therefore, this study aimed to identify the combination of compost doses and/or local liquid organic fertilizer concentrations, based on multiple evaluation criteria, that supports the productivity of rice-fish integration agriculture. The experiment was carried out in the Wanuae farmer group of the Barebbo District, Bone Regency, Indonesia, between September 2018 and January 2019. The experiment employed a split plot design with a randomized complete block design (RCBD). The main plot consisted of compost (four levels), and the subplot was the local biofertilizer source (four levels). The results demonstrated that the number of fill grains was significantly affected by the compost treatment and the type of local biofiller. The effect of the compost dosing was more dominant in comparison with the local liquid organic fertilizer character and its interactions. A compost dosage of four tons ha⁻¹ and a local liquid organic fertilizer, sourced from soaked coconut fiber with cow urine, has been recommended as the combination treatment to optimize the rice and fish yield potential. The Minapadi (rice fish) with additional high composting effectively increased the farmer’s outcome with a 2-point R/C ratio, more so than those without composting. Moreover, the compost dosage in this Minapadi study requires further exploration for a better understanding.

The development of cultivation technology is crucial for increasing corn (Zea mays L.) production in many parts of the world, including Indonesia. Combination of variety, planting systems, chemical fertilizers, and biofertilizers were developed in a previous study. However, such combinations must be more sustainable by including fertilizer to compost. A practical and systematic approach such as multivariate analysis is needed to increase the effectiveness of the evaluation of cultivation technology. Therefore, the study aimed to identify the best combination of compost rates with previously developed cultivation packages based on multivariate analysis. A split-plot design was used with a randomized complete group design as an environmental design. The main plot consisted of eight Farid cultivation packages (FP); each plot had eight levels (combination of variety, chemical fertilizer, and biofertilizer). Meanwhile, the subplots were four compost (C) rates, namely C0: 0 t ha^-1, C1: 2 t ha^-1, C2: 4 t ha^-1, and C3: 6 t ha^-1. Results showed that ear length (coefficient of evaluation index (CEI) = 0.164), number of kernel rows per ear (CEI = 0.067), and 1000-grain weight (CEI = 0.014) can be recommended as supporting characteristics or yield correction factors (CEI = 0.442), in which yield is the main characteristic. This study recommends combining the Farid package consisting of NK variety + fertilizer rate N:P:K = 200:100:50 + 25 kg KNO₃ + Ecofarming 5 cm³ L^-1 with 2, 4, and 6 t ha^-1 compost rates as an alternative technology for corn cultivation.

Padjung R, Farid M, Musa Y, Anshori MF, Nur A, Masnenong A. 2021. Drought-adapted maize line based on morphophysiological selection index. Biodiversitas 22: 4028-4035. Synthetic line formation is an effort to increase maize productivity in drought-stressed areas. This process requires systematic selection in determining adaptability levels involving important secondary characters formulated in the selection index. Furthermore, the principal component index had been widely reported, both in normal and stressed conditions. The selection index development on morpho-physiological characters based on multivariate analysis was expected to increase drought stress tolerance and maize lines selection precision. Therefore, the purpose of this research was to form a selection index based on morpho-physiological characters and selecting synthetic lines adaptive under drought stress. This research was designed using a split-plot with 3 replications, where the main plot consisted of normal and stressed irrigation, while the subplot was genotype consisting of 6 lines and 3 check varieties namely Bisma, Lamuru, and Sukamarga. Observations were performed on 18 morphological and 4 physiological characters, and the results showed that the selection index was formed based on multivariate analysis from 9 characters. Through index selection, Syn_2-2 (0.79), Syn_2-15 (0.85) and Syn_2-16 (0.97) were considered as drought stress adaptive lines. Therefore, the 3 lines can be recommended in the synthetic variety release process.

Akfindarwan AK, Farid M, Syaiful SA, Anshori MF, Nur A. 2023. Selection criteria and index analysis for the S2 maize lines of double-crosses. Biodiversitas 24: 192-199. This study aimed to determine the selection criteria and the selection index for the S2 maize lineage from double cross crosses and to select the potential lines that could be continued in the S3 generation. The research was carried out in the field from July to November 2020 at the Experimental Farm of the Agriculture Faculty, Hasanuddin University, Tamalanrea District, Makassar City, South Sulawesi. The maize lines used were derived from 4 double cross populations of S1 generation, namely: DC1 (P36/B9//NK7328/JH2) with 19 genotypes, DC2 (B9)/HJ28/NK728), DC3 (B18/B2/B2/N29), and DC4 (JH45/B19/N29/B2). The results of this study revealed that the selection criteria suitable for this population were the weight of seeds per cob, peel cob weight, and weight of 100 seeds. Furthermore, the selection index analysis showed that there were 61 promising lines for F2 double cross maize that had a positive index value, while based on the Z value, there were 44 lines that had a better index value than the best parents. Therefore, it is recommended that the 61 S2 Maize lines from double crosses be further tested on to the S3 generation.