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The present investigation was undertaken in brinjal (Solanum melongena L.) to estimate combining ability and gene action following a half diallel mating design using ten parents. The ratio of genetic variance components, σ2gca/σ2sca and σ2D/σ2A, showed dominant gene action, indicating the presence of non-additive genetic variance for days to 50% flowering, fruit yield per plant, total phenol, antioxidant activity and total soluble sugar. The traits fruits per plant, fruit girth, and fruit weight showed additive genetic variance. Among the parental genotypes, AB 15-08, ABSR 2 and AB 20-13 were found to be good general combiners for fruit yield, fruits per plant, and total soluble solids. The three highest-ranking hybrids were AB 15-08 × AB 20-13, AB 15-08 × AB 20-03 and AB 20-07 × GP BRJ 224. The above hybrids would be rewarding for harnessing heterosis.

Growers may adopt a tomato hybrid if it is high yielder with good fruit quality and can withstand the bacterial wilt (BW) disease. A line × tester mating design was used to determine heterobeltiosis, combining ability and gene action for 15 characters in tomato. Most traits under study exhibited additive and non-additive gene action except days to 50% flowering, polar diameter of fruit, pH of fruit and lycopene content of fruit which were controlled by additive gene effect. Two genotypes, ‘Utkal Kumari’ and ‘CLN-2460E’ were identified as potential donors. The maximum, significant, heterobeltiosis was for disease incidence of BW followed by fruit yield per plant, fruit firmness, and fruits per plant. In the tropical tomato growing zones, two potential hybrids, ‘Utkal Kumari × CLN-2460E' and ‘Utkal Deepti × CLN-2460E', may fulfil significant horticultural requirements since they exhibited resistance against virulent biovars 3 and 6. More testing in a variety of edapho-climatic conditions is required to confirm the stability of the developed resistance and the hybrids’ resilience. Partial- to over-dominance reactions of fruit yield and other economic traits were reflected. Isolating pure lines from the segregating generation of heterotic F1s is another method to improve fruit yield and quality as well as disease resistance against bacterial wilt. [ABSTRACT FROM AUTHOR]

AbstractUnderstanding the nutritional dynamics before pruning is essential to elucidate how nutrient reserves affect the mango tree’s ability to regenerate tissues. A research project was carried out to determine the adequate range of supply for mango sprout phase (pre-pruning) in two different mango leaves (from the first and second vegetative flushes), and evaluate effect of biochemical activity on mango sprouting and correlate it with fruit yield. Two experiments with ‘Ataulfo’ and ‘Kent’ mangoes were carried out from 2021 to 2023. The experiments were arranged in randomized blocks with treatments distributed in subdivided plots referring to two N sources (NO3-, NH4+) in the plots and N doses (0, 50, 100, 150 and 200% of the recommended dose) in the subplots. The leaf nutrient concentrations, sodium, and α-amylase were evaluated in leaves of the 1st and 2nd vegetative flush, the number of shoots per pruned branch, and fruit yield. The number of shoots per pruned branch, influenced by the nutritional status prior to production pruning, varies with nutrient, and the 2nd vegetative flush after the previous pruning has a greater impact on shoot development in the current cycle. The shoot growth of the ‘Ataulfo’ after production pruning depends on leaf concentrations of phosphorus, potassium, calcium, sulfur, cooper, manganese, zinc and molybdenum, in addition to sodium, while ‘Kent’ depends only on phosphorus, cooper, iron, manganese, and zinc. The highest fruit yield indices are recorded under the average number of sprouts per pruned branch of 2.72 for ‘Ataulfo’ and 2.63 for ‘Kent’. [ABSTRACT FROM AUTHOR]

The experiment was conducted during winter (rabi) seasons of 2021–22 and 2022–23 at ICAR-Indian Institute of Vegetable Research, Varanasi, Uttar Pradesh to study the improvement in yield and quality parameters in tomato (Solanum lycopersicum L.) cultivar using brinjal (Solanum melongena L.) rootstock. Three improved cultivars of tomatoes i.e. Kashi Aman, Kashi Adarsh and Kashi Chayan were grafted over three brinjal rootstocks, IC-111056, IC- 354557, and Surya. Experimental findings revealed that brinjal rootstocks significantly affected photosynthetic traits, root architectures, fruit yields and quality traits of tomatoes. Maximum photosynthetic rate (23.8 µmol/m2/s) and stomatal conductance (492.74 mmol/m2/s) were recorded in Kashi Chayan grafted over Surya rootstock, whereas chlorophyll fluorescence yields (Fv/Fm) was significantly higher in Kashi Aman self-rooted plants (0.452–0.457). Grafting tomato onto brinjal rootstocks significantly enhanced most of the yield traits, such as fruit number, weight, size and yields. Surya + Kashi Chayan graft combination registered an enhancement in number of fruits and yields by 8.65% and 8.4%, respectively over self-rooted Kashi Chayan. Significantly higher root volumes were noticed in two graft combinations i.e. IC-354557 + Kashi Aman (28.53 cm2) and Surya + Kashi Chayan (27.98 cm2), while 63% and 44.5% higher root length density (RLD) were registered in graft combinations IC-354557 + Kashi Chayan and Surya + Kashi Chayan, respectively over self-rooted Kashi Chayan. Fruit quality such as lycopene and ascorbic acid contents were significantly affected in different rootstocks and scions, whereas fruit acidity was unaffected. From the present study it may be conclude that use of brinjal rootstock Surya significantly improved most of the physiological, yield, root architecture and fruit quality in Kashi Chayan tomato cultivars.

The present investigation was undertaken in brinjal (Solanum melongena L.) to estimate combining ability and gene action following a half diallel mating design using ten parents. The ratio of genetic variance components, σ² gca/σ² sca and σ² D/σ² A, showed dominant gene action, indicating the presence of non-additive genetic variance for days to 50% flowering, fruit yield per plant, total phenol, antioxidant activity and total soluble sugar. The traits fruits per plant, fruit girth, and fruit weight showed additive genetic variance. Among the parental genotypes, AB 15-08, ABSR 2 and AB 20- 13 were found to be good general combiners for fruit yield, fruits per plant, and total soluble solids. The three highestranking hybrids were AB 15-08 × AB 20-13, AB 15-08 × AB 20-03 and AB 20-07 × GP BRJ 224. The above hybrids would be rewarding for harnessing heterosis. [ABSTRACT FROM AUTHOR]

Bio-stimulants are gaining importance for elevating the stagnated yield level resulting from continuous use of chemical fertilizers (CF) in many crops, however, their use in pomegranate have not been fully explored. Two years of field experiments were conducted on a 5-years old pomegranate cv. Bhagwa orchard to investigate the effects of different combinations of commercial bio-stimulant products namely, microbial-based product A containing consortium of Rhizophagus spp. (5 kg ha−1), seaweed extract-based granular formulation D (30 kg ha−1) and liquid formulation B (625 and 1250 ml ha−1) through soil application as well as wettable granular formulation, C (1 and 2 g l−1) and liquid formulation, E (1 ml l−1) through foliar sprays along with chemical fertilizers on soil fertility, trees' nutrition, fruit yield and quality of pomegranate. Results showed that integrated use of CF and bio-stimulants significantly increased the number of bisexual flowers. However, the combination of microbial-based product A (5 kg ha−1), seaweed extract based liquid formulation B (625 ml ha−1) in soil and foliar spary of seaweed extract based wettable granular formulation C (1–2 g l−1) with CF resulted in production of the highest fruit yield (increased by 41.97–51.61%) with 23.08–33.38% increase in the exportable grade fruit and improved quality attributes viz. ascorbic acid, anthocyanin, non-reducing sugar, protein, and mineral content of fruits through enhancement in soil fertility and trees' micronutrient status compared to only CF. These doses combinations of bio-stimulants along with CF gave rise to the highest benefit–cost ratio of 2.10–2.34:1 and hence can be recommended for sustainable pomegranate cultivation. [ABSTRACT FROM AUTHOR]

The sustained higher profitability of a pomegranate orchard relies heavily on the production of a greater proportion of high-quality fruits, a goal achievable through the implementation of effective management practices. The objective of this study is to provide site-specific supplementary knowledge regarding the response of pomegranate plants to various management practices under arid conditions. With the aim of enhancing both marketable fruit yield and quality of pomegranate in arid regions, four separate and simultaneous experiments were conducted in the same orchard to evaluate (i) the response of planting materials derived from tissue culture, air layering, and cutting; (ii) the impact of crop (fruit) load; (iii) the response of crop regulation; and (iv) the application response of organo-mineral fertilizers containing potassium (OMF-K) and phosphorus (OMF-P). The results obtained for plant growth, fruit yield, and fruit quality did not exhibit significant differences among pomegranate plants raised through the three different methods of vegetative propagation. Striking results in terms of producing superior-grade fruits, higher marketable yield, and overall fruit quality were achieved with crop loads of 80 fruits per plant. Staggering the crop regulation from June to September effectively extended the harvesting season to four months, from the last week of November to March, with eventual benefit of reduced fruit cracking compared to the standard two-month harvesting period obtained from normal regulation. Soil application of the indigenously developed OMF-K in two equal splits, along with the recommended N and P through inorganic sources, significantly reduced fruit cracking (only 6.23%) compared to the recommended NPK through inorganic sources (26.9%), while maintaining similar physicochemical quality attributes. [ABSTRACT FROM AUTHOR]

In the current work, the effects of foliar application of two commercial fertilizers [CalfalB (containing calcium and boron) and Rice (containing macro- and micronutrients)] on leaf minerals, chlorophyll content, yield, and fruit quality, as well as some phytochemical characteristics of mandarins ‘Page’ was investigated for two consecutive years. The solutions were applied three times: mid-June and two more sprays at intervals of 18 days. Based on the results, leaves of fertilized mandarin plants with Rice and CalfalB accumulated higher N, P K, Ca, Mg, Zn, Mn, and Fe concentrations than unfertilized plants. Application of fertilizers, especially Rice, increased significantly the content of chlorophyll a (p < 0.001) and total chlorophyll (p = 0.0013) in the leaves. Trees fertilized with Rice showed a higher percentage of fruit yield, juice, pulp, and rind. Moreover, mandarins treated with fertilizers, especially Rice, had a higher level of TSS (total soluble solids), TSS/TA (titratable acidity), color parameters of the rind [L* (lightness), a* (redness), and b* (yellowness)], vitamin C, phenol compounds, carotenoid, and antioxidant activity. The results of our research work showed that an application of fertilizers containing macro- and microelements by spraying can considerably improve fruit yield and quality of the mandarin ‘Page’, especially in areas with poor soils.

Abstract High-quality red/dry chilli for spice, pharmaceutical and medicinal purposes is a major goal in chilli breeding. The male sterile lines have greater potential for the exploitation of heterosis in chilli to achieve this objective. Genetic male sterile lines with special traits like destalking and ability to withstand high rainfall were involved in heterosis breeding to identify hybrids for commercial and industrial purposes. Forty F1 hybrids were developed by crossing 4 diverse GMS lines with 10 testers using Line × Tester mating design to estimate heterosis, combing ability and gene action. The experiment involving 14 parents and 40 F1s, along with standard variety ‘CH-27’ was laid out in α-lattice square design in three replications during summer 2020 and 2021. The GMS lines MS 9-2 and MS 26-1 along with testers DPCh 10, VVG, DPCh 40 and Him Palam Mirch-2 showed significant GCA for marketable red/dry fruit yield and majority of their component traits. Ten F1 hybrids were identified with superiority for fruit yield based on mean performance, significant heterosis and SCA effects, providing an opportunity to utilize them in value-added products and dried spice purposes viz., MS 9-2 × HPM-2, MS 11-2 × DPCh 40, MS 9-2 × DPCh 40 and MS 9-2 × DPCh 101 with erect fruiting habit and that of MS 9-2 × DPCh 10, MS 26-1 × DPCh 10, MS 9-2 × PBC 535, MS 26-1 × VVG, MS 29-2 × DPCh 10 and MS 26-1 × DPCh 22- C with pendent fruits. The non-additive gene action was predominant in the expression of fruit yield, total red fruits/plant, oleoresin and capsanthin. A significant positive correlation among SCA, economic heterosis and per se performance is an indicative to identify superior hybrids. Multi-location testing of these hybrids shall pave way to exploit them commercially by making them available to the farmers.

The article proposes an assessment of the quantitative parameters of the crop using the analysis of mechanical vibrations. A demonstration of the investigation is shown for a situation where a support system in the field helps cucumbers grow vertically. The study was carried out by modeling the yield of cucumbers. The greatest attention was paid to the frequencies of natural oscillations. A developed numerical model of the support design is proposed and its natural oscillation frequencies are calculated using the finite element method (FEM). The results were confirmed by a physical experiment that actually simulates a numerical model. [ABSTRACT FROM AUTHOR]

Strawberry (Fragaria x ananassa) is a popular fruit consumed for its desirable flavour, aroma and colour and is considered a functional food due to its antioxidant properties. Noting the need for farmers to increase productivity to meet increasing consumer demands, this study aimed to explore the potential of biostimulants to enhance strawberry cultivation. Herein, a field trial was conducted on a commercial strawberry farm, wherein 1944 strawberry plants received fertigation supplementation with either a control solution (nutrients only) or nutrients combined with one of two biostimulant complexes (BCs). Biostimulant complex 1 (BC1) was composed of molasses, Aloe vera extract and fish-hydrolysate, and biostimulant complex 2 (BC2) was composed of potassium silicate and potassium phosphite. Results indicated that BC1 maintained total yields but increased the sellable proportion and decreased the proportion of waste. In contrast, BC2 increased total yields with both sellable yields and waste increased. No significant changes were observed for indicators of consumer preference (flavour, aroma and fruit colour), however, on-average large increases were observed to indicators of fruit antioxidant properties (phenolic and flavonoid content). Accordingly, these results support the utilisation of biostimulants as a strategy to improve strawberry on-farm productivity without compromising consumer quality measures. [ABSTRACT FROM AUTHOR]

The Fruit Harvest Helper, a mobile application developed by Northwest Nazarene University's (NNU) Robotics Vision Lab, aims to assist farmers in estimating fruit yield for apple orchards. Currently, farmers manually estimate the fruit yield for an orchard, which is a laborious task. The Fruit Harvest Helper seeks to simplify their process by detecting apples on images of apple trees. Once the number of apples is detected, a correlation can then be applied to this value to obtain a usable yield estimate for an apple tree. While prior research efforts at NNU concentrated on developing an iOS app for blossom detection, this current research aims to adapt that smart farming application for apple detection across multiple platforms, iOS and Android. Borrowing ideas from the former iOS app, the new application was designed with an intuitive user interface that is easy for farmers to use, allowing for quick image selection and processing. Unlike before, the adapted app uses a color ratio-based image-segmentation algorithm written in C++ to detect apples. This algorithm detects apples within apple tree images that farmers select for processing by using OpenCV functions and C++ code. The results of testing the algorithm on a dataset of images indicate an 8.52% Mean Absolute Percentage Error (MAPE) and a Pearson correlation coefficient of 0.6 between detected and actual apples on the trees. These findings were obtained by evaluating the images from both the east and west sides of the trees, which was the best method to reduce the error of this algorithm. The algorithm's processing time was tested for Android and iOS, yielding an average performance of 1.16 s on Android and 0.14 s on iOS. Although the Fruit Harvest Helper shows promise, there are many opportunities for improvement. These opportunities include exploring alternative machine-learning approaches for apple detection, conducting real-world testing without any human assistance, and expanding the app to detect various types of fruit. The Fruit Harvest Helper mobile application is among the many mobile applications contributing to precision agriculture. The app is nearing readiness for farmers to use for the purpose of yield monitoring and farm management within Pink Lady apple orchards. [ABSTRACT FROM AUTHOR]

Combining ability assessment helps select parents and hybrids with high performance, which can lead to increased yield and effective crop improvement. The present study aimed to evaluate 24 diverse crosses for ten different quantitative traits using line x tester mating in the kharif season. The experiment involved the assessment of crosses, which included 4 females, 6 males, and 1 commercial cultivar (Nishant). The evaluation employed a randomized block design (RBD) with three replications. Major discrepancies were observed in the genotypes of both parents and hybrids for all traits, indicating a significant amount of variation in fruit yield and other characteristics that contribute to yield. JBR-20-05 was found the best general combiner for days to 50% flowering, fruit length and plant height. JBR-20-04 was found to be the best general combiner for average fruit weight, fruit girth and total fruit yield per plant. The genotype identified in the JBR-20-07 study, resistant to fruit and shoot borer infestation, held significant potential for use in breeding and selection programs to enhance the resistance of brinjal varieties. Estimation of Specific combining ability effect revealed that among the hybrids, the hybrids JBR-20-04 x JBR-20-05 recorded highly significant specific combining ability (SCA) effects for total fruit yield per plant. The cross JBR-20-03 x JBR-20-05 showed high desirable significance to SCA for fruit and shoot borer infestation. Variance due to general combining ability was less than the variance due to SCA, and the ratio of GCA to SCA variance was less than unity. When choosing hybrids to enhance yield in brinjal (Solanum melongena L.) through breeding, it is crucial to prioritize specific traits that directly contribute to increased production. [ABSTRACT FROM AUTHOR]

Mandarin fruits are the most widely grown citrus fruits in the world, particularly in the eastern Himalayas of India, which is the primary center of citrus diversity. Diagnosing potential nutritional imbalances using leaf tissue analysis is a mandatory practice for a higher yield. Regarding the nutritional diagnosis of Khasi mandarin plants, particularly in the acidic soil of the hilly ecology of the Eastern Himalayas, India, there is currently no information available. Therefore, the present study was conducted to identify nutrient constraints, establish leaf-based diagnostic recommended and integrated system (DRIS) norms, and determine nutrients' relationship with fruit yields in 144 orchards. The result showed that the DRIS indices predicted a nutritional optimum value for Khasi mandarin: 2.26–2.83% N, 0.11–0.16% P, 1.86–2.07% K, 1.85–2.12% Ca, 0.33–0.48% Mg, 170.10–225.10 mg kg−1 Fe, 74.03–83.43 mg kg−1 Mn, 1.24–2.45 mg kg−1 Cu, and 19.84–21.28 mg kg−1 Zn. The DRIS norms identified the nutrients Zn, P, Ca, K, N, and Mg as deficient to low levels (14.15→2.14), while Fe, Mn, and Cu were at high to excessive levels (5.50→18.25). The nutritional balance index had a significantly negative relationship with the fruit yield. Leaf nutrient concentrations of N (0.909**), P (0.827**), K (0.867**), Zn (0.833**), Ca (0.827**), and Mg (0.592**) had a significant positive correlation with fruit yield. The finding will facilitate the correct interpretation of leaf nutrient analysis, and the norms developed will enable a precise intervention through nutrient management for higher yields in mandarin citrus. [ABSTRACT FROM AUTHOR]

Water scarcity is an extreme global concern due to changing climate and rapid population growth. Worldwide, freshwater sources are depleting and there is a need to implement water-conserving approaches in water-limited or arid areas for sustainable crop production. Therefore, this study aimed to investigate the impact of deficit irrigation on cucumber plant physiology, growth, and fruit yield traits grown under greenhouse conditions. The experiment was conducted in a complete randomized design with four water regimes, 100%, 80%, 60%, and 40% crop water requirement (ETc). Results showed that the highest plant leaf chlorophyll contents (43.2 µmol m-2), plant biomass (12.43 g), plant height (172.39 cm), number of leaves (19.85), fruit yield (2.49 kg), and total soluble solids (3.73 °Brix) were in plants irrigated at 100% level. In comparison, the lowest plant height (115.73 cm), number of leaves (15.77) and fruit yield (1.81 kg) were recorded at 40% irrigation. Results revealed that reduced irrigation regimes up to 80% or 60% have no significant inhibitory effects on cucumber agro-morphological traits. However, 40% of irrigation levels showed significantly reduced plant morphological and fruit yield traits. Overall, the result demonstrated that regulated deficit irrigation can significantly conserve water without negatively impacting cucumber yield.

Introduction Pepper is a rich source of essential vitamins and minerals. Like tomatoes, pepper plays an important role in preventing heart diseases due to its high amount of antioxidants. Fruit yield is a complex trait that is not only controlled by several genes, but also greatly influenced by the environment. On the other hand, fruit yield is affected by a large number of other traits and their interaction. Therefore, it is very important for plant breeders to know the relationships between these traits and their interaction effects. The path coefficient analysis is a method that clarifies the relationships between traits and their direct and indirect effects on fruit yield. In this method, the correlation coefficient between two attributes is divided into components that measure direct and indirect effects. Considering the limited studies regarding the evaluation of relationships between fruit yield and other traits affecting fruit yield in pepper, this research was conducted with the aim of identifying these important relationships and evaluating their direct and indirect effects in Iranian pepper populations. Materials and Methods In order to carry out this research, the seeds of 30 Iranian pepper accessions were collected directly from the farmers. The experiment was conducted in the form of pot cultivation in the research greenhouse of the Faculty of Agriculture of Urmia University in a completely randomized design with five replications during 2015-2016. After the flowering stage, the desired traits were estimated. Variance analysis was estimated, after examining the basic hypotheses of variance analysis by SAS9.4, as well as the genotypic and phenotypic correlation between traits based on the restricted maximum likelihood (REML) procedure in the SAS9.4 software. Step-by-step regression analysis was used to determine the traits with the most variation justified the fruit yield. The Durbin-Watson test was performed to investigate the independence of experimental errors. Analysis of path coefficients was performed based on the results of stepwise regression and genotypic correlation of traits in the R V.4.0.5. Results and Discussion In order to understand the relationships between traits and use them in breeding programs, the phenotypic correlation was estimated. In this study based on the results of phenotypic correlation, leaf width and leaf length (0.651), single fruit weight and fruit circumference (0.784), fruit circumference and fruit diameter (0.625) and pulp weight and fruit diameter (0.610), showed positive and significant correlation. The purpose of estimating genotypic correlation coefficient is to determine relationships in conditions which in environmental factors are not involved. In the investigation of genotypic correlation, a positive, strong and significant relationship between fruit yield and pulp weight (0.907), fruit circumference (0.891), fruit diameter (0.697), single fruit weight (0.646) and around the plant (0.381) were observed. Given that most of these traits are factors contributing to fruit yield, the presence of such positive and significant genotypic correlation coefficients is reasonable. It can be inferred that pepper accessions with higher fruit characteristics, encompassing factors such as plant density and branching, are likely to exhibit higher fruit yields as well. It's important to note that correlation coefficients are mathematical tools used to measure the linear relationship between two variables. Their significance lies in their mathematical interpretation, and as such, they alone do not provide sufficient proof of a cause-and-effect relationship. Utilizing the results of stepwise regression, less impactful traits or those with minimal effects were eliminated from the model. As a result, seven key traits were identified as the most influential factors affecting fruit yield: pulp weight, plant density, fruit diameter, fruit count, plant height, total seed weight, and branch count.The first characteristic was pulp weight, which was included in the model and explained 78.8% of the fruit yield changes between genotypes. The second characteristic (around the plant) along with pulp weight explained 80.9% of the fruit yield variations. Fruit diameter, together with the previous two characteristics, explained 81.5% of fruit yield variations. In total, the traits included in the model for fruit yield justified 84.6% of the total changes in fruit yield in 30 pepper accessions. In order to better understanding and more accurately interpret of the results, as well as to know the direct and indirect effects and the effect of the traits that were entered into the model through stepwise regression, the path coefficient analysis method was used in this research. Fruit diameter (0.709) and pulp weight (0.289) respectively showed the most positive and direct effect on fruit yield. Fruit pulp weight through fruit diameter had the most positive indirect effect (0.595) on fruit yield. Around the plant showed an indirect positive effect on fruit yield through pulp weight (0.157), fruit diameter (0.392) and number of branches (0.080). Conclusion In the present study, the trait of fruit diameter had a positive, strong and significant genotypic correlation (0.697) with fruit yield, and it also showed a positive direct effect (0.709) on fruit yield, these two coefficients can be considered equal, Approximately. Therefore, direct selection based on fruit diameter proves to be a valuable strategy for enhancing fruit yield. The magnitude of residual effects serves as an indicator of the model's accuracy in path analysis. When this value is substantial, it may be advisable to incorporate additional causal variables into the model. In the current study, the residual effects value (0.213) affirms the model's optimal accuracy.This research highlights the effectiveness of employing stepwise multivariate regression and path coefficient analysis to gain a deeper understanding of the fundamental relationships between traits. It underscores that relying solely on correlation relationships is insufficient for comprehensively justifying the associations between these traits.

Heat stress substantially reduces tomato (Solanum lycopersicum) growth and yield globally, thereby jeopardizing food security. DnaJ proteins, constituents of the heat shock protein system, protect cells from diverse environmental stresses as HSP‐70 molecular co‐chaperones. In this study, we demonstrated that AdDjSKI, a serine‐rich DnaJ III protein induced by pathogens, plays an important role in stabilizing photosystem II (PSII) in response to heat stress. Our results revealed that transplastomic tomato plants expressing the AdDjSKI gene exhibited increased levels of total soluble proteins, improved growth and chlorophyll content, reduced malondialdehyde (MDA) accumulation, and diminished PSII photoinhibition under elevated temperatures when compared with wild‐type (WT) plants. Intriguingly, these transplastomic plants maintained higher levels of D1 protein under elevated temperatures compared with the WT plants, suggesting that overexpression of AdDjSKI in plastids is crucial for PSII protection, likely due to its chaperone activity. Furthermore, the transplastomic plants displayed lower accumulation of superoxide radical (O2•─) and H2O2, in comparison with the WT plants, plausibly attributed to higher superoxide dismutase (SOD) and ascorbate peroxidase (APX) activities. This also coincides with an enhanced expression of corresponding genes, including SlCuZnSOD, SlFeSOD, SlAPX2, and SltAPX, under heat stress. Taken together, our findings reveal that chloroplastic expression of AdDjSKI in tomatoes plays a critical role in fruit yield, primarily through a combination of delayed senescence and stabilizing PSII under heat stress. [ABSTRACT FROM AUTHOR]

In recent years, an increase in the frequency of low-sunlight conditions due to climate change has resulted in a decline in the yield and quality of crops for greenhouse farmers, leading to significant challenges in maintaining optimal plant growth. The crop growth model can be used to predict changes in cucumber yield in response to variations in sunlight, which can help efficiently address sunlight shortages. The objective of this study was to improve and validate the model for predicting cucumber yield under different light environment conditions, including shading and supplemental lighting. The model comprises three steps: LAI prediction, daily assimilate yield prediction, and fruit yield prediction, each of which involves modifying the coefficients applied to suit the cucumber cultivar and environment condition. The improved model demonstrated a high degree of accuracy in predicting cucumber yields in the control and low-sunlight treatments (10, 20, and 30% shading), with a coefficient of determination (R2) > 0.98. When supplemental lighting was incorporated into the control and shading treatments, the accuracy of the improved model in predicting cucumber yield was also high, with a coefficient of determination (R2) > 0.99. The model also accurately predicted the decrease in cucumber fruit yield under low-sunlight conditions (shading treatments) and the increase in yield due to supplemental lighting. The findings of this study indicate that the improved cucumber yield prediction model can be applied to assess the efficacy of yield reduction in low-sunlight conditions and the potential for yield enhancement through supplemental lighting. [ABSTRACT FROM AUTHOR]

Tomato is one of the most widely grown vegetable crops in Europe. This study describes an approach for treating tomato plants with an extract of Ascophyllum nodosum (ANF) prior to a stress event, which prepares the plants at the molecular level to respond more effectively to stress conditions, through a process known as molecular priming. Solanum lycopersicum L. cv. Micro-Tom, a dwarf tomato variety, was pre-treated with ANF via foliar spray during the flowering phase and subsequently subjected to drought conditions. ANF-treated plants exhibited enhanced growth, fruit yield, and stress tolerance under both moderate and severe drought conditions compared to untreated plants. Transcriptomic studies in leaves revealed that the priming treatment preserved the photosynthetic machinery, inducing stress-protective genes involved in ascorbate, peroxidase, GABA, glutathione, and flavanol biosynthesis. Simultaneously, the treatment repressed key senescence-related genes associated with ethylene biosynthesis, as well as several WRKY and NAC transcription factors. Metabolome analysis demonstrated that ANF induces drought tolerance by promoting the accumulation of stress-protective primary and secondary metabolites, such as GABA, proline, maltose, ascorbic acid, quercetin, and biotin, which can act as osmoprotectants and free radical scavengers during drought. Combined transcriptome and metabolome analyses suggest that ANF treatment represses the senescence process, maintains photosynthetic activity, and induces the accumulation of protective metabolites and amino acids, promoting plant survival and growth under drought. Overall, this research provides new insights into the molecular mechanisms underlying biostimulant-based molecular priming and offers a knowledge-based approach for the accurate application of this ANF molecular priming agent to increase crop productivity and mitigate yield loss during drought, contributing to food security in the era of climate change.

Field trials were conducted at the Federal University of Agriculture, Abeokuta, Ogun State, Nigeria (700, 20' N, 300, 23' E) in the early and late wet seasons of 2012, to evaluate response of growth, chlorophyll content and fruit yield of cayenne pepper (Capsicum annuum L.) to seedling age and weed interference period. Split-plot arrangement in a randomized complete block design with three replicates was adopted in the trials. The main plot treatments were age of pepper seedlings at transplant, (four and six weeks after sowing (WAS)) while the subplot treatments consisted of ten periods of weed interference. Data were collected on stem girth, chlorophyll content, pepper fruit count, fruit yield and weed dry matter production. Data collected were subjected to analysis of variance and treatment means were separated using least significant difference at p=0.05. The results showed that six-week old pepper seedling had higher chlorophyll content and pepper fruit yield. Chlorophyll content and fruit yield of pepper increased with weed free period and decreased with weed infestation period. Uncontrolled weed infestation for whole season caused 98.6% and 91.6% reduction in pepper fruit yield in the early wet and late wet season respectively. In this study, six-week old pepper seedling kept weed free for at least 12 weeks after transplanting (WAT) resulted in significantly higher pepper fruit yield than four-week old pepper seedling irrespective of period of weed interference. Hence, six-week old pepper seedling should be planted and kept weed-free for the first 12 WAT for maximum fruit at harvest. [ABSTRACT FROM AUTHOR]

The degree of association between yield and its components can be identified using correlation and Principal Component Analyses (PCA). PCA also reveals key characteristics that explain most of the differences between genotypes. A study was formulated to evaluate the relationship between yield and its contributing traits in cucumber. The experiment was conducted with 16 cucumber genotypes in a Randomized Complete Block Design, with three replications. The correlation analysis revealed a strong and statistically significant relationship in number of pistillate flowers (r = 0.58**), number of branches (r = 0.43**), vine length (r = 0.69**), number of leaves (r = 0.73**), leaf area (r = 0.70**), number of fruits (r = 0.91**), fruit length (r = 0.40**), fruit girth (r = 0.39**), and fruit weight (r = 0.74**) with fruit yield. PCA revealed that PC1 accounted for 51.53% of the total variation, while PC2 explained 13.91% of the total variability. This study demonstrated that choosing traits such as number of pistillate flowers, number of branches, vine length, number of leaves, leaf area, number of fruits, fruit length, fruit girth, and fruit weight that have a strong positive correlation with fruit yield could be given priority in selection for yield improvement.

The Fruit Harvest Helper, a mobile application developed by Northwest Nazarene University’s (NNU) Robotics Vision Lab, aims to assist farmers in estimating fruit yield for apple orchards. Currently, farmers manually estimate the fruit yield for an orchard, which is a laborious task. The Fruit Harvest Helper seeks to simplify their process by detecting apples on images of apple trees. Once the number of apples is detected, a correlation can then be applied to this value to obtain a usable yield estimate for an apple tree. While prior research efforts at NNU concentrated on developing an iOS app for blossom detection, this current research aims to adapt that smart farming application for apple detection across multiple platforms, iOS and Android. Borrowing ideas from the former iOS app, the new application was designed with an intuitive user interface that is easy for farmers to use, allowing for quick image selection and processing. Unlike before, the adapted app uses a color ratio-based image-segmentation algorithm written in C++ to detect apples. This algorithm detects apples within apple tree images that farmers select for processing by using OpenCV functions and C++ code. The results of testing the algorithm on a dataset of images indicate an 8.52% Mean Absolute Percentage Error (MAPE) and a Pearson correlation coefficient of 0.6 between detected and actual apples on the trees. These findings were obtained by evaluating the images from both the east and west sides of the trees, which was the best method to reduce the error of this algorithm. The algorithm’s processing time was tested for Android and iOS, yielding an average performance of 1.16 s on Android and 0.14 s on iOS. Although the Fruit Harvest Helper shows promise, there are many opportunities for improvement. These opportunities include exploring alternative machine-learning approaches for apple detection, conducting real-world testing without any human assistance, and expanding the app to detect various types of fruit. The Fruit Harvest Helper mobile application is among the many mobile applications contributing to precision agriculture. The app is nearing readiness for farmers to use for the purpose of yield monitoring and farm management within Pink Lady apple orchards.

Background: Sowing density optimal is rated a less expensive solution for enhancing the output of tomato yield in the background of extending food requirements worldwide. Methods: The main objective of this study is to investigate the sowing density effect on the growth and tomato yield planted in Don Duong district of Lam Dong province, Vietnam. The study was conducted during the spring tomato crop (January to June 2020) with five different sowing densities varying from 33000 to 50000 plants/ha based on drip irrigation system supply approximately 100% of actual evapotranspiration. Result: Results pointed out that among investigated sowing densities, sowing density 45830 plants/ha obtained the optimal fruit yield (OFY) up to 87.8 tons/ha compared with different sowing densities while other observed variations as the number of bunches, fruit weight per plant and diameter were no significant difference. Based on the findings, tomato growers can sow with a density 45830 plants/ha to obtain the OFY thereby contributing to increase profits. [ABSTRACT FROM AUTHOR]