Bu bölüm, bitki doku kültürü alanında yapay zekâ (YZ) ve makine öğrenmesi (ML) tekniklerinin giderek artan önemini bütüncül ve disiplinler arası bir bakış açısıyla ele almaktadır. Klasik in vitro yaklaşımların çok değişkenli ve doğrusal olmayan biyolojik sistemleri açıklamada karşılaştığı sınırlılıklar, bu bölümde veri temelli ve öngörücü yapay zekâ modelleri çerçevesinde tartışılmaktadır. Yapay zekânın bitki doku kültürüne entegrasyonu; mikroçoğaltım veriminin artırılması, besin ortamı ve hormon kombinasyonlarının optimizasyonu, stres fizyolojisi analizleri, sekonder metabolit üretim tahminleri ve görüntü tabanlı morfolojik değerlendirmeler gibi temel uygulama alanları üzerinden ayrıntılı olarak sunulmaktadır. Bölümde, Yapay Sinir Ağları (ANN), Destek Vektör Makineleri (SVM), Rastgele Orman (RF), K-En Yakın Komşu (KNN) ve Genetik Algoritmalar (GA) gibi yaygın kullanılan yapay zekâ ve optimizasyon yöntemleri; teorik temelleri, güçlü yönleri, sınırlılıkları ve bitki doku kültüründeki özgül kullanım örnekleriyle birlikte karşılaştırmalı biçimde ele alınmaktadır. Ayrıca bu yöntemlerin hibrit ve karar destek sistemleriyle entegrasyonu, protokol geliştirme süreçlerinde deneme-yanılma yaklaşımını nasıl dönüştürdüğü üzerinden değerlendirilmektedir. Bölümün ilerleyen kısımlarında, yapay zekâ destekli biyoreaktör sistemleri ve dijitalleşmiş in vitro üretim altyapıları ele alınarak, bitki biyoteknolojisinde otomasyon, ölçeklenebilirlik ve sürdürülebilirlik perspektifi ortaya konulmaktadır. Bu bölüm, yapay zekâ ve makine öğrenmesini yalnızca yardımcı analiz araçları olarak değil, bitki doku kültüründe yeni bir araştırma ve üretim paradigmasının temel bileşenleri olarak konumlandırmakta; hem akademik araştırmalar hem de ticari uygulamalar için yol gösterici bir çerçeve sunmaktadır.

Drought stress is one of the most critical constraints limiting crop productivity worldwide, particularly under increasing water scarcity driven by climate change. In this study, the effects of plant growth-promoting rhizobacteria (PGPR) on green bean (Phaseolus vulgaris L.) under varying irrigation regimes were evaluated, and their responses were further analyzed using machine learning (ML) approaches. A greenhouse experiment was conducted using four irrigation levels (I100, I80, I60, and I40) and three bacterial treatments, including Stenotrophomonas rhizophila EU.2B33 (R2), Bacillus marisflavi EU.18 (R1), and their combination (R3). Severe water deficit (I40) reduced shoot and root biomass by approximately 40

Water and energy crises, increased greenhouse gas emissions, high labor costs, and labor shortages demand the shift from puddled transplanting to dry direct seeding. Inbred rice varieties can perform well under the dry direct-seeded rice (DDSR) system. This study aims to optimize the seed rate (SR) for rice cultivars in the DDSR system. Five SRs (S1 = 15, S2 = 20, S3 = 25, S4 = 30, and S5 = 35 kg/ha) and four inbred rice varieties include Basmati 515 (V1), PK 1121 Aromatic (V2), Super Basmati (V3), and Kisan Basmati (V4) were used as experimental treatments. The study was conducted over 2 years (2019-2020). The plant height (PH), panicle length (PL), filled-grain per panicle (FGPP), unfilled-grain per panicle (UFGPP), productive tiller per m(2) (PT), unproductive tiller per m(2) (UPT), 1000-grain weight (TGW), grain yield (GY), biomass yield (BY), harvest index (HI), average grain length (AGL), average grain width (AGW), average grain thickness (AGT), broken rice (B), brown rice (BR), head rice (HR), elongation ratio (ER), and bursting (BRUS) were the response variables. The Response Surface Methodology (RSM) was used to optimize the SRs based on the GY, BY, HI, HR, and ER. The results show that the PT, UPT, TGW, and GY were highly significant (p < 0.01) in the interaction effects of year, variety, and SR. The BY, HI, AGL, AGW, AGT, B, BR, HR, ER, and BRUS were highly significant (p < 0.01) in the interaction effect of variety and SR. In the RSM model, the optimal SRs were 27, 31, 25, and 24 kg/ha for the rice varieties V1, V2, V3, and V4, respectively. The RSM model showed higher R-2 (0.81-0.99) with lower RMSE, mean absolute error (MAE), and mean absolute percentage error (MAPE) values. The predicted and actual values of GY, BY, HI, HR, and ER at optimum SR of 25 kg/ha for V3 were 3.65 t/ha, 9.88 t/ha, 33.47%, 40.48%, 2.07 and 3.32 t/ha, 11.0 t/ha, 32%, 38.66% 1.94, respectively. The RSM model predicted results agreed with the actual results, as prediction errors were less than or equal to +/- 10%, which confirmed the model's reliability. Moreover, the GY has a positive correlation with BY (R = 0.5370). The HR showed a negative correlation with B (R = -0.8681) and AGL (R = -0.5015). Our findings imply that managing stand growth and weeds is critical in obtaining the required yield and quality in the DDSR system with lower SRs.

The search for natural antioxidants to safeguard against several diseases is expanding rapidly. Interestingly, the levels of antioxidants have been discovered to be greater in the in vitro-raised calli than the plant extracts in vivo. The aim of this research was to standardize the protocols for culturing calli of five potential medicinal herbs and determine their antioxidant and polyphenolic compounds. The calli of carnation, goji berry, harmal, bitter cucumber, and datura were developed from young leaves using Murashige and Skoog media with varied forms and concentrations of cytokinin and auxin in combination after their optimization. Goji berry, carnation, and datura initiated callus in 13 days, faster than bitter cucumber (20 days). Datura had a 28.7

Rice is recognized worldwide as a primary staple food crop which provides calories approximately half of growing world population and the maintenance of its high productivity is of utmost importance in the context of global food security. The objective of this research was to examine the variability and correlation between yield-related characteristics in rice. A total of 15 F1 crossings, in addition to five lines and three testers were subjected to evaluate in a Randomized Complete Block Design with three replications at the experimental site of the Department of Plant Breeding and Genetics, Faculty of Agriculture and Environment, Islamia University of Bahawalpur, Pakistan, during the year 2022–2023. Analysis of variance (ANOVA) showed that genotype revealed significant differences for most variables except grain length, days to maturity, panicle weight and grain yield per plant. The study found adequate spontaneous genetic diversity for rice yield parameters such as plant height, panicle length, grain per panicle, grain width, days to heading and spikelets per panicle. ANOVA also revealed significant differences among the studied traits in parents, crosses, lines, testers and their combinations. Combing ability revealed potential parents and hybrids for different studied parameters. Line 37651 had positive general combining ability (GCA) (8.888) effect for grain yield per plant and line 37481 reveled highest negative GCA among the lines (− 4.984). Tester 37500 showed significant positive GCA (4.072) effect for grain yield per plant while among the negative GCA (− 3.598) was exhibited by tester 37644. Cross 37651 × 7968 exhibited significant positive specific combining ability (SCA) (18.362) effect and among cross 37651 × 37500 showed significant negative SCA (− 13.18) effect for grain yield per plant. Grain yield per plant exhibited significant genotypic positive and negative correlation with various studied parameters. From the results it was found that diversified parents and best combiners (hybrids) may be useful in breeding high-yielding rice cultivars.

Drought stress (DS) is the most damaging climatic factor that hinders the growth and ornamental quality of floricultural crops. Improving the floricultural crop's ability to withstand DS is of great importance to the ornamental plants industry. Moringa leaf extract (MLE) as a biostimulant has been reported to improve the DS tolerance in various horticultural crops. However, the potential of ocimum leaf extract (OLE) alone or in combination with MLE needs to be explored under DS conditions. Therefore, the present study aimed to explore the protective roles of OLE and MLE for inducing DS tolerance in gladiolus (Gladiolus grandiflora L.), which is a vital cut flower crop worldwide. In the first experiment, foliar application of different doses of OLE (10%, 15%, 20%, and 25%) and MLE (2%, 3%, 5%, and 7%) was used for optimization. In the second experiment, the optimized dose of biostimulant was applied to gladiolus under both normal and DS conditions. In the second experiment, plants were divided into two groups: the first group received normal irrigation, while the second group was subjected to DS (60% field capacity). Foliar applications of the biostimulant were applied twice at a 7-day interval, beginning 1 week after the imposition of DS (four-leaf stage). A marked reduction in the growth and physiological and biochemical attributes of gladiolus plants under DS was recorded in contrast to the normal condition. Under DS conditions, the best results were noticed in the application of OLE 15% which significantly improved shoot fresh weight by 28%, shoot dry weight by 17%, leaf area by 18%, relative water content by 9%, and membrane stability by 09% compared with the control. Moreover, net photosynthesis rate, transpiration rate, stomatal conductance, substomatal conductance, and water use efficiency were increased by 33%, 30%, 30%, 35%, and 28%, respectively, in DS gladiolus plants supplemented with OLE. Similarly, under DS, OLE application improved the activity of catalase by 37%, by 30%, and superoxide dismutase by 36% while decreasing the level of malondialdehyde by 40% and hydrogen peroxide by 20% compared with normal irrigated plants. The combination of OLE 15% + MLE 3% showed a synergistic effect, due to the complementary interaction of bioactive compounds, improved photosynthetic activity, and enhanced the antioxidative potential of the gladiolus plants under both conditions. These results suggest that OLE and MLE have the potential to mitigate DS in gladiolus plants by improving growth, water balance, gas exchange, and enzyme activity.

Abiotic stress is a major constraint limiting plant growth, productivity, and agricultural sustainability worldwide. Biochar, a carbon-rich material produced through biomass pyrolysis, has been proposed as an effective soil amendment to enhance plant resilience under stress conditions; however, limited information is available regarding its role in leguminous crops exposed to combined abiotic stresses. Therefore, a pot experiment was conducted to investigate the interactive effects of salt stress and water stress on pea (Pisum sativum L.) growth, phenology, leaf gas-exchange attributes, grain yield, and water use efficiency (WUE). Salt and water stress significantly disrupted pea phenology, particularly delaying flowering, and adversely affected leaf gas-exchange parameters. Salt stress reduced transpiration rate, intercellular carbon dioxide (CO2) concentration, stomatal conductance, and net photosynthetic rate by 27%, 11%, 27%, and 21%, respectively. In contrast, biochar incorporation significantly increased pea grain yield by 3-15%. Water stress and biochar application enhanced yield-based water use efficiency (WUE-yield) by 28% and 16%, respectively, whereas salt stress reduced WUE-yield by 24%. These findings demonstrate that salt and water stress substantially limit pea productivity, while biochar application can partially mitigate their negative impacts. Evaluating the interactive effects of multiple abiotic stressors is essential for developing sustainable crop management strategies.

This study investigated the effects of gibberellic acid (GA₃) treatments and salinity stress on germination and seedling development in Festulolium cultivars. Seeds were exposed to salinity levels of 0, 5, 10, 15, and 20 dS/m and treated with distilled water, 100 ppm, or 200 ppm GA₃ for 12 h. Germination percentage (GR), mean germination time (MGT), shoot height (SH), root length (RL), seedling fresh weight (FW), dry weight (DW), seedling vigor index (SVI), and proline content were assessed. Salinity stress markedly reduced GR, SH, RL, and SVI, while increasing MGT and proline. Severe reductions in germination and seedling growth were observed at 15–20 dS/m. At 20 dS/m, SVI was higher in Lofa (9.63) than in Hostyn (7.96). GA₃ at 200 ppm improved GR, SH, and SVI at 0–10 dS/m and enhanced proline accumulation under high salinity. To complement experimental findings, four machine learning algorithms—k-Nearest Neighbors (kNN), Multilayer Perceptron (MLP), Random Forest (RF), and XGBoost—were evaluated for predictive modeling of seven traits. The MLP model outperformed others, achieving the highest accuracy (R² = 0.66–0.97; NRMSE = 0.04–0.14), with near-perfect predictions for SH and RL (R² = 0.97; CCC = 0.98–0.99). kNN performed well for SH, RL, and MGT (R² = 0.83–0.90) but poorly for GR and proline. RF and XGBoost showed moderate accuracy (R² ≈ 0.85–0.92 for morphological traits) but weak predictability for biochemical parameters (R² = 0.29–0.54). Overall, morphological traits were predicted more accurately than biochemical ones, highlighting the superior generalization ability of MLP in capturing nonlinear responses to salinity and GA₃ treatments. In conclusion, 200 ppm GA₃ improved seedling performance under salt stress, and machine learning, particularly MLP, proved to be a powerful tool for predicting cultivar responses, offering a reliable framework for stress physiology studies in Festulolium.

Increasing level of lead (Pb)-polluted agricultural soils jeopardizes chia (Salvia hispanica L.) sustainable cultivation. A pot trial was carried out to explore impact of MXene on the growth and Pb uptake of S. hispanica seedlings, aiming to reduce Pb buildup in S. hispanica. Pb treatment resulted in the reduction of photosynthetic pigment levels and biomass of S. hispanica seedlings, in addition to an elevation in the antioxidant enzyme activities. Under Pb stress, MXene treatment enhanced photosynthetic pigments, biomass, and activity of antioxidant enzyme in S. hispanica seedlings. MXene application reduced root and shoot Pb levelsas well as translocation factor (TF) in S. hispanica seedlings under Pb stress. In contrast to Pb treatment, MXene diminished root Pb concentration by 15%. The TF, carotenoid level, total Chl (a + b), and Chl-a exhibited strong correlation with shoot Pb under Pb stress. Consequently, MXene utilization can enhance growth, impede Pb uptake in roots of S. hispanica seedlings under Pb stress.

The short vase life (VL) of gladiolus cut flowers reduces their commercial importance. Trehalose (Tre), a phyto-product that plays a unique role in plant functioning and environmental safety, can be used to improve VL. This work assessed a preharvest spray of Tre to mitigate postharvest (PHV) oxidative stress in "White Prosperity" gladiolus cut flowers and its physiological and PHV-related mechanisms. The treatments were 1 g L-1 (Tre1), 2 g L-1 (Tre2), and 3 g L-1 (Tre3), and a distilled water control. Foliar applied Tre3 (3 g L-1) improved VL. Trehalose spray improved ornamental traits, VL, and number of opened florets. Tre reduced oxidative injury to the membrane structure, as depicted by lower accumulation of hydrogen peroxide (H2O2) and malondialdehyde (MDA), by increasing antioxidant defense system activities. Tre also influenced total soluble proteins, sugars, phenols, and proline contents as well as floral hormonal levels, including salicylic acid, abscisic acid, and ascorbic acid. Tre could improve plant health by influencing photosynthesis and increasing VL by enhancing sugars, osmoprotectants, and antioxidant capacity.

Citrus is a genetically diverse genus widely cultivated across tropical and subtropical regions, yet its varieties often exhibit overlapping morphological traits that complicate accurate identification. In this study, the genetic diversity of nine Citrus varieties was assessed using 36 Simple Sequence Repeats (SSR) markers in combination with key morphological and biochemical traits. The CTAB method was employed to extract genomic DNA, followed by polymerase chain reaction (PCR) using a specific set of primers. Gel documentation was performed to score the bands obtained. This study aimed to utilize 36 SSR markers to characterize the genetic diversity of nine Citrus varieties collected from the Citrus Research Institute (CRI), Sargodha. Polymorphic information content (PIC) values ranged from 0.20 to 0.50, averaging 0.27, indicating moderate genetic variability among the varieties. Principal component analysis explained 68.7% of the total variation across the first two components, and cluster analysis grouped the varieties into two major clusters, demonstrating clear genetic differentiation. The integration of molecular and morphological data revealed distinct similarity groups, providing valuable insights for selecting superior parental lines. These findings support the development of improved Citrus varieties and the establishment of DNA-certified true-to-type nursery plants for enhanced orchard productivity.

Water deficit stress (WDS) causes massive losses in cut flower production. Various sustainable protectants are reported to improve the WDS tolerance in ornamentals. The physio-chemical and ornamental aspects in response to foliarly applied chitosan (Ci) for the amelioration of WDS induced oxidative stress in geophyte cut flowers still need to be explored. Hence, in this study, the effect of foliar application of Ci was tested on the said attributes of Gladiolus under WDS conditions. Initially, different levels of Ci were foliarly applied on potted Gladiolus plants under normal (100

Application of melatonin and lipopeptides (LPs) derived from Bacillus strains is considered an efficient strategy to control plant diseases at both pre and postharvest stages. However, the combined application of melatonin and LPs has not been studied yet. Therefore, the present study presents the synergistic effect of melatonin and LPs produced by Bacillus atrophaeus strain MCM61 against gray mold disease and its impact on quality parameters and vase life of cut roses. The stems of cut roses along with flowers were dipped in the melatonin solution at concentration (0, 0.2, 0.4, 0.6, and 0.8 mM) and the results indicated that the vase life of flowers treated with the melatonin was enhanced compared to control. Melatonin at 0.6 mM concentration showed the highest vase life of cut roses at day 8. Synergistic treatment with melatonin and LPs of B. atrophaeus MCM61 revealed that MDA and H2O2 content showed the highest decrease in cut roses. Similarly, relative water content, total phenol content, GSH content, and defense enzymes i.e., APX, SOD, PPO, POD, and CAT activities were increased in cut roses treated with co-application of B. atrophaeus MCM61 LPs and melatonin compared to single treatments and control treatment. Furthermore, the longevity of cut roses was also improved in flowers treated with a combined application of MCM61 and melatonin compared to other treatments.

Using organic manures appears to be a promising strategy to promote plant performance and improve soil health in arid and semi-arid regions under the threat of changing climate. The objective of the current field-based study was to investigate the beneficial effects of cow dung manure (CDM) fermented at different days, including 7, 14, and 21 days, on cotton crop growth and soil health compared with synthetic fertilization. It was noticed that chemical fertilizer application showed the lowest values for cotton seedling growth, physio-biochemical attributes, and soil organic matter content. Results regarding CDM also showed that under all applied treatments, treatment in which 21 days of fermented manure was applied performed better in terms of cotton plant growth and soil properties, as evidenced by the cotton plant's higher biomass, chlorophyll, and water contents, activities of antioxidant enzymes, lower soil pH, increased organic matter contents, and higher amounts of moisture and essential plant nutrient retention in soil. In summary, our study suggests that using CDM could be an efficient practice to improve the growth and development of crop plants and soil health.

Tanacetum balsamita L. is a medicinal and aromatic plant of high economic value, yet its tissue culture and micropropagation protocols remain poorly developed. This study evaluated and compared two in vitro culture systems, semisolid medium (SS) and Temporary Immersion System (TIS), for enhancing biomass production and growth performance, in terms of relative growth rate (RGR), photosynthetic activity, chlorophyll content, antiradical capacity, and anatomical development. The results demonstrated that the TIS significantly improved RGR, photosynthetic performance, and antiradical activity, and promoted the anatomical development that facilitated greenhouse acclimatization. Machine learning (ML) models, including Multilayer Perceptron (MLP) and Random Forest (RF), were employed to predict morphological and biochemical traits. MLP achieved the highest predictive accuracy (R2 > 0.95) and lowest error metrics for complex, nonlinear traits such as chlorophyll content and antiradical activity, whereas RF excelled in predicting morphological traits with more uniform variance, such as leaf number and shoot length. Overall, this study demonstrates that the TIS provides a high-yield, economically crucial strategy for the micropropagation of T. balsamita, and that integrating ML-based predictive modeling can enhance parameter optimization and phenotyping precision. This combined approach offers a valuable framework for advancing tissue culture research in medicinal and aromatic plants through both production efficiency and data-driven decision-making.

Drought and temperature extremes are major abiotic stressors limiting legume productivity worldwide. This study investigates the germination and early seedling responses of six cultivars belonging to three Vicia species (V. sativa, V. pannonica, and V. narbonensis) under varying levels of polyethylene glycol (PEG)-induced drought and temperature conditions (12 °C, 18 °C, and 24 °C) in vitro. Significant cultivar-dependent differences were observed in the germination rate (GR), shoot and root length (SL and RL), fresh and dry weight (FW and DW), and vigor index (VI). The Ayaz cultivar exhibited superior performance, particularly under severe drought (10% PEG) and optimal temperature (24 °C), while Özgen and Balkan were most sensitive to stress. Principal component and correlation analyses revealed strong associations between the vigor index, shoot height, and fresh and dry weight, particularly in high-performing genotypes. To further model and predict stress responses, four machine learning (ML) algorithms—Random Forest (RF), k-Nearest Neighbors (k-NNs), Multilayer Perceptron (MLP), and Support Vector Machines (SVMs)—were employed. Based on model performance metrics, and considering high R2 values along with low RMSE and MAE values, the MLP model demonstrated the most accurate predictions for the GR (R2 = 0.95, RMSE = 0.06, MAE = 0.05) and VI (R2 = 0.99, RMSE = 0.02, MAE = 0.01) parameters. In contrast, the RF model yielded the best results for the SL (R2 = 0.98, RMSE = 0.02, MAE = 0.02) and DW (R2 = 0.93, RMSE = 0.06, MAE = 0.04) parameters, while the highest prediction accuracy for the RL (R2 = 0.83, RMSE = 0.09, MAE = 0.07) and FW (R2 = 0.97, RMSE = 0.05, MAE = 0.03) parameters was achieved using the SVM model. Comparative analysis with recent studies confirmed the applicability of ML in stress physiology and genotype screening. This integrative approach offers a robust framework for genotype selection and stress tolerance modeling in legumes, contributing to developing climate-resilient crops.

Water scarcity is a major environmental stress that negatively affects the soil traits, growth of plants, and yield of crops. This research assessed the impact of vermicompost, oak tree biochar, apple tree biochar, and the combined impact of vermicompost and both biochars on the growth, water use efficiency (WUE), and yield of eggplant under conditions of limited irrigation. The main purpose of the study was deficit irrigation, which involved 3 levels of water supply: 50%, 75%, and 100% PWR (plant water requirement). The second focus was on the application of vermicompost, with two levels: 0 and 2000gm(-2), as well as biochar, with two levels: 0, 400gm(-2) of oak-tree biochar, and 400gm(-2) of apple tree biochar. The findings revealed that the combination of apple-tree biochar and vermicompost at a level of 100% PWR, delivered the most positive results in terms of plant growth and functioning. The early harvest yield was greatest when apple-tree biochar was applied alone at a level of 50% PWR. However, the total yield of the plant was highest when apple-tree biochar and vermicompost combined were applied at a level of 100% PWR. The plant's WUE reached its highest level after the combined application of apple-tree biochar and vermicompost at a level of 50% PWR. The maximum leaf levels of N, P, K, Fe, and Mg were observed when both vermicompost and apple-tree biochar were applied at a level of 100% PWR. The treatments without amendments or with vermicompost only at a level of 50% PWR exhibited the highest values of physiologically significant stress metabolites.

This paper delves into the multifaceted role of sustainable agricultural practices in addressing current environmental challenges and advancing global food security. We critically examine the impact of various sustainable farming techniques, including precision agriculture, organic farming, and agroforestry, and their contribution to environmental stewardship and ecological resilience. Technology integration in agriculture, particularly precision agriculture, is explored, highlighting its role in enhancing productivity, sustainability, and efficiency. The paper also addresses the pivotal role of genetic engineering in developing drought-resistant crops, offering solutions to global water scarcity challenges. The importance of climate-smart agriculture (CSA) is discussed, underscoring its significance in enhancing the resilience of agricultural systems to climate change. Additionally, the paper examines the role of sustainable supply chains and community engagement in promoting sustainable agricultural practices, with a special focus on the impact of agricultural education on fostering environmentally responsible and economically viable farming methods. Through this comprehensive analysis, the paper contributes to a deeper understanding of the complexities and opportunities in sustainable agriculture, emphasizing the need for integrated approaches to ensure long-term environmental sustainability and food security.