Satellite data is increasingly being used as a basis for operational crop monitoring. However, satellite technologies for monitoring perennial crops remain underdeveloped. The aim of this study was to assess the relationship between apple yield and NDVI calculated using all available Sentinel-2 data for the growing seasons (March-November) from 2017 to 2024. Totally 81 cloud-free images were analyzed. The seasonal absolute maximum and area-weighted average NDVI were calculated based on analysis of all images for each growing season for each plot. Intensively irrigated, mixed-age apple orchards located in northern Azerbaijan served as the research site. Totally 30 plots with 6 apple tree varieties (Arian, Gala, Golden, Golden Parsi, Granny Smith, and Fuji) planted from 2007 to 2017 were analyzed. Apple yield for each plot for 2018–2024 were collected. The linear regression models between NDVI (the seasonal absolute maximum and area-weighted average) and apple yield was used as the relationship criterion. An analysis of the relationship was conducted for individual apple varieties, for orchard plots, and for plots of different ages. It was found that reliable relationships between apple yield and NDVI are only observed for specific plots with a single variety of the same age (R2cv higher than 0,8 with RPIQ more than 2,1). Grouping plots of the same variety or age does not demonstrate a reliable relationship between NDVI and yield. Only for groups of middle-aged orchards does such a relationship become stronger. These results should be considered when developing methods for satellite monitoring of apple orchards.
Optimizing harvest maturity and postharvest handling is important for maintaining pineapple quality and reducing losses under tropical storage conditions. However, limited information is available on how ripening stage at harvest interacts with postharvest storage duration to influence physical and quality characteristics of Smooth Cayenne pineapple under ambient conditions in Fiji. This study evaluated the effects of four ripening stages and postharvest storage duration on fruit weight, crown weight, fruit dimensions, and °Brix of Ananas comosus (Smooth Cayenne) pineapple stored under ambient conditions at 27 ± 2 °C and 85 ± 5% RH. Forty fruits were assigned to four ripening stages: S1 (25%), S2 (50%), S3 (75%), and S4 (100%), with 10 fruits per stage. The same fruits were repeatedly evaluated from Day 0 to Day 14. Although the estimated shelf life of some treatments ended by Day 5, observations were continued to document the progression of quality deterioration during extended ambient storage. At S1, total fruit weight and fruit weight reached their highest recorded means on Day 6 (2.42 and 2.10 kg, respectively), while °Brix varied across storage days, with relatively higher values observed on Days 5 and 9. At S2, the highest fruit weights occurred early in storage, whereas °Brix increased during the later observation period and reached 17.00°Brix on Day 12. At S3, fruit weight and dimensions were greatest around Day 3 and subsequently declined, while °Brix remained relatively stable. At S4, fruit weight, dimensions, crown weight, and °Brix showed comparatively minor fluctuations during storage. Postharvest shelf life decreased with advancing ripening stage, with S1 fruits showing the longest storability and S2, S3, and S4 fruits exhibiting shorter storage periods under ambient conditions. Earlier-harvested fruits provided greater storage flexibility, whereas more advanced ripening stages were associated with higher initial soluble-solids concentrations but reduced postharvest storability. These findings demonstrate the importance of matching harvest maturity with intended marketing and storage conditions to maintain pineapple quality and minimize postharvest losses. Future research should evaluate larger fruit populations across multiple seasons and locations and incorporate additional quality indicators, including titratable acidity, firmness, weight loss, microbial deterioration, and physiological disorders, together with improved storage technologies for extending the postharvest life of pineapple under tropical conditions.
Soft rot, caused by the phytopathogenic bacteria Pectobacterium and Dickeya, is a serious and destructive disease of potato worldwide. Symptoms caused by the two genera are indistinguishable. An effective diagnostic strategy is essential for controlling the disease and reducing losses in potato production. In this study, we examined genomes from multiple Pectobacterium and Dickeya species and selected the distinctive p4h gene to design specific primers and develop a loop-mediated isothermal amplification (LAMP) assay for the rapid and specific detection of Pectobacterium among other genera causing soft rot. The assay was designed for use with a field-portable thermal flask at 65 °C. The specificity of the developed LAMP assay was evaluated using 15 bacterial strains comprising inclusivity and exclusivity panels. The assay detected as little as 5 fg (~9000 genomic copies) of genomic DNA. It also detected Pectobacterium in infected potato tuber samples. Results were consistent between laboratory and field conditions, with no false-positive or false-negative results. The developed LAMP assay may be applied to diagnostics, agricultural quarantine, and disease management.
Under traditional open-field cultivation, turmeric (Curcuma longa L.) yield and quality are strongly influenced by genotype and environmental conditions, resulting in variability in productivity and phytochemical composition. Controlled greenhouse production offers an opportunity to minimize environmental fluctuations and enhance yield and quality predictability. In this study, 21 turmeric genotypes, representing diverse agro-ecological regions of India, were evaluated under greenhouse conditions over two consecutive years (2021–2023) to identify superior and stable genotypes for yield and quality traits. Significant genotypic variation was observed for fresh rhizome yield (378–1,014 g clump −1), dry recovery (15%–28%), oleoresin (3%–12%), essential oil (2%–9.5%), and curcuminoid content (0.7%–4.0%). IISR Pragati and NDH 8 were identified as high-yielding and stable genotypes, while Chhattisgarh Haldi 2 showed superior dry recovery. Waigon Turmeric exhibited consistently higher oleoresin and essential oil contents, and IISR Pragati demonstrated superior and stable curcuminoid content. GGE biplot analysis indicated that genotype and genotype × environment interaction contributed more to trait variation than the environment itself, reflecting the reduced environmental influence under greenhouse cultivation. Genotypes Roma, IISR Pratibha, and CO 3 emerged as consistent, balanced multi-trait ideotypes, while IISR Pragati and Waigon Turmeric exhibited superior performance for yield and quality traits, respectively, using MGIDI and FAI-BLUP models. These findings highlight that greenhouse cultivation combined with appropriate genotype selection can improve yield stability and quality consistency in turmeric, supporting informed selection of genotypes for commercial and industrial use. This study is the first to evaluate turmeric genotypes for yield and quality under controlled greenhouse conditions.
This study investigated how preharvest supplemental far-red (FR) and UVA light under white LED light influences growth, photochemical performance, phenolic content, and antioxidant activity in leaf lettuce grown in a vertical plant factory. Lettuce plants were cultivated under a white LED background light with a photosynthetic photon flux density (PPFD) of 100 µmol m −2 s −1. During the final two weeks before harvest, plants received supplemental FR at 10 µmol m −2 s −1 or UVA at 5 µmol m −2 s −1, while white-light plants served as the control. Throughout the cultivation period, plants were maintained under a 16-h light/8-h dark photoperiod, 35–40% relative humidity, and a CO 2 concentration of 350–380 ppm in the plant factory. Research revealed that preharvest FR significantly enhanced plant height, leaf area, fresh weight, and dry weight by 19.4%, 22.7%, 13.1%, and 39.5%, respectively, compared with white light alone. FR improved photochemical performance, resulting in higher F v / F m, performance index (PI), and stomatal conductance. Furthermore, FR increased the contents of chlorophyll a, chlorophyll b, carotenoids, by 39.3%, 50.0%, 50.0%, respectively, and UVA light increased anthocyanin by 84.6%, compared to white light. In contrast, UVA treatment was more effective at enhancing nutritional quality, increasing anthocyanin content by 146.2%, total phenolic content by 34.5%, total flavonoids by 25.4%, amino acid content by 106.2%, DPPH radical-scavenging activity by 7.7%, and FRAP antioxidant capacity by 16.7% compared with white light. However, UVA also enhanced antinutrient nitrate content by 64.0% compared to white. This study shows that short-term preharvest spectral supplementation can be strategically applied to improve either biomass production via FR or nutritional quality via UVA, without increasing baseline light intensity; however, further investigation is needed to reduce nitrate levels.
