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This study was carried out in Karaj, Iran in 2017 and 2018 to assess the efficacy of summer sowing (June 22) versus spring sowing (April 20) of six sugar beet genotypes at three harvest times (October 13, November 2, and November 23) via the measurement of catalase (CAT), malondialdehyde (MDA), and agronomic traits. Results showed that in both sowing dates, higher growth and temperature were related to higher CAT activity and MDA content, and the maximum MDA and CAT activity were observed in 1700−1900 growth degree days (GDD). Genotypes responded to the shortening of the growth period differently. The best genotypes for summer sowing were found to be ‘Paya’, ‘IR7’, and ‘Pars’ when a combination of the least response to delayed sowing and the highest root yield in the summer sowing conditions was considered. Compared to the spring sowing, the summer sowing decreased white sugar yield (WSY) of all cultivars by 28.3−50.5% in the first year and 5.3−32.4% in the second year. ‘Paya’ and ‘IR7’ were the most capable cultivars in preserving WSY so that they maintained 70% of their yields. In addition, the genotypes exhibited their highest WSY at the November 23 harvest date so that root, raw sugar and white sugar yields were 41.21, 6.35 and 5.02 t ha−1 higher at the November 23 harvest date than at the October 13 harvest date, respectively. Based on the results, if summer-sown sugar beets are considered as a cash crop in rotation with grains and there is no limitation on water supply, it can then be recommended to farmers as it can make good profits for them.

Sugar beet and sugarcane are two major crops for sugar extraction throughout the world. However, the sugar beet importance is not just about sugar production but it also plays an important role in crop rotation and increased productivity in various industries as well as livestock feed. In this study the long-term (2009-16) field trial effect of alfalfa (4 years)-winter wheat (1 year)–fallow (1year)-sugar beet rotation on yield and quality parameters of sugar beet were evaluated for two consecutive rotations. The field trials were carried out at single location in Karaj, Iran, using randomized complete block design with four replications. Analysis of variance showed that the seasonal factors influenced different traits. In the first and second rotations, the root yield ranged from about 56.5 to 83.2 and 61.4 to 77.8 t ha-1, respectively with significant difference among cultivars in the first rotation. However, no significant difference was observed among both rotations in terms of root yield. Same results were obtained for sugar yield in both rotations which illustrates the stability of the above-mentioned traits. Except for sugar content, significant difference was observed among other traits in both rotations. We show for the first time the effect of completing two rotation sequences on sugar beet performance and quality for decision making into a continual expansion/development of crop cultivation.

Background Sweet potato ( Ipomoea batatas L.) is a vital root crop valued for its nutritional quality, yield potential, and adaptability; however, the effects of early harvesting on yield, root size distribution, and marketable value are not well understood. This study evaluated nine genotypes to compare genotype performance at two harvest times, classify roots by economic value, and assess consumer-preferred traits. Methods The experiment was conducted at 90 and 120 days after transplanting (DAT). Morphological, yield, and nutritional traits were measured, including SPAD value, vine and leaf characteristics, shoot weight, root number and mass, economic root number and mass, soluble sugars, and total yield. Roots were classified into six size classes based on mass and number. Results More than 40% of root mass per plot consisted of roots weighing 30–100 g, with the remainder distributed among five other size classes. Genotypes G-89 and BARI Sweetpotato-15 produced 150% and 65% higher yields at 120 DAT compared with 90 DAT. At 120 DAT, BARI Sweetpotato-17, G-193, G-89, and BAU Sweetpotato-5 produced roots across all six size classes. Sensory evaluation at 90 DAT indicated that G-54 and G-193 were preferred for texture, boiling, and baking, while G-89 and BAU Sweetpotato-5 were favored for aroma, indicating potential traits associated with earlier maturity under the study conditions. Conclusions Genotypes G-89, G-184, BARI Sweetpotato-15, and G-138 exhibited comparatively higher yields and larger storage roots at 120 days after planting (DAT) under char land conditions, while several other genotypes including G-54 produced satisfactory yields and acceptable root quality at 90 DAT. This indicates their comparatively earlier performance within the evaluated harvest times under the specific char land agro-ecological conditions of the study. Broader applicability and definitive classification would require further validation across additional harvest stages and agro-ecological zones.

Nitrogen (N), phosphorus (P), and potassium (K) fertilization is widely used to enhance crop productivity. However, the synergistic effects of combined N, P, and K application on sweetpotato yield and nutrient use efficiency are not fully understood. To address this knowledge gap, a field experiment was conducted with five treatments: control (CK), no N (-N), no P (-P), no K (-K), and full NPK application (NPK). We systematically analyzed storage root yield, yield components, and nutrient accumulation characteristics. Additionally, fertilizer use efficiency and soil nutrient balance were evaluated. The NPK treatment significantly increased storage root yield by 34.8–53.1% compared with single nutrient deficiency treatments. The greatest yield reduction was observed under -P conditions, associated with low soil available P and a disordered N and K allocation ratio (5.10–14.40%). Phosphorus application resulted in high agronomic efficiency (187.79 kg kg −1 P 2 O 5 ) but low recovery efficiency (0.05–0.25 kg kg −1 P 2 O 5 ), whereas -N and -K treatments led to soil P surplus (50.25–63.06 kg ha −1 ). A logistic model revealed that NPK treatment increased the maximum and average nutrient accumulation rates compared with deficient treatments. Pearson correlation analysis showed significant positive relationships between yield and yield components, as well as nutrient accumulation in storage roots and whole plants. Random forest regression identified P accumulation in storage roots as the most important predictor of yield. In conclusion, combined NPK fertilization enhances both storage root yield and nutrient use efficiency, with targeted P management playing a critical role in achieving high-yield and high-efficiency sweetpotato production.

Background Rapid non-destructive measurements to predict cassava root yield over the full growing season through large numbers of germplasm and multiple environments is a huge challenge in Cassava breeding programs. As opposed to waiting until the harvest season, multispectral imagery using unmanned aerial vehicles (UAV) are capable of measuring the canopy metrics and vegetation indices (VIs) traits at different time points of the growth cycle. This resourceful time series aerial image processing with appropriate analytical framework is very important for the automatic extraction of phenotypic features from the image data. Many studies have demonstrated the usefulness of advanced remote sensing technologies coupled with machine learning (ML) approaches for accurate prediction of valuable crop traits. Until now, Cassava has received little to no attention in aerial image-based phenotyping and ML model testing. Results To accelerate image processing, an automated image-analysis framework called CIAT Pheno-i was developed to extract plot level vegetation indices/canopy metrics. Multiple linear regression models were constructed at different key growth stages of cassava, using ground-truth data and vegetation indices obtained from a multispectral sensor. Henceforth, the spectral indices/features were combined to develop models and predict cassava root yield using different Machine learning techniques. Our results showed that (1) Developed CIAT pheno-i image analysis framework was found to be easier and more rapid than manual methods. (2) The correlation analysis of four phenological stages of cassava revealed that elongation (EL) and late bulking (LBK) were the most useful stages to estimate above-ground biomass (AGB), below-ground biomass (BGB) and canopy height (CH). (3) The multi-temporal analysis revealed that cumulative image feature information of EL + early bulky (EBK) stages showed a higher significant correlation ( r  = 0.77) for Green Normalized Difference Vegetation indices (GNDVI) with BGB than individual time points. Canopy height measured on the ground correlated well with UAV (CHuav)-based measurements ( r  = 0.92) at late bulking (LBK) stage. Among different image features, normalized difference red edge index (NDRE) data were found to be consistently highly correlated ( r  = 0.65 to 0.84) with AGB at LBK stage. (4) Among the four ML algorithms used in this study, k-Nearest Neighbours (kNN), Random Forest (RF) and Support Vector Machine (SVM) showed the best performance for root yield prediction with the highest accuracy of R 2  = 0.67, 0.66 and 0.64, respectively. Conclusion UAV platforms, time series image acquisition, automated image analytical framework (CIAT Pheno-i), and key vegetation indices (VIs) to estimate phenotyping traits and root yield described in this work have great potential for use as a selection tool in the modern cassava breeding programs around the world to accelerate germplasm and varietal selection. The image analysis software (CIAT Pheno-i) developed from this study can be widely applicable to any other crop to extract phenotypic information rapidly.

Sugar beet fertilization is a very complex agrotechnical measure for farmers. The main reason is that technological quality is equally important as sugar beet yield, but the increment of the root yield does not follow the root quality. Technological quality implies the concentration of sucrose in the root and the possibility of its extraction in the production of white table sugar. The great variability of agroecological factors that directly affect root yield and quality are possible good agrotechnics, primarily by minimizing fertilization. It should be considered that for sugar beet, the status of a single plant available nutrient in the soil is more important than the total amounts of nutrients in the soil. Soil analysis will show us the amount of free nutrients, the degree of soil acidity and the status of individual elements in the soil so that farmers can make a compensation plan. An estimate of the mineralizing ability of the soil, the N min, is very important in determining the amount of mineral nitrogen that the plant can absorb for high root yield and good technological quality. The amount of N needed by the sugar beet crop to be grown is an important factor, and it will always will be in the focus for the producers, especially from the aspect of trying to reduce the N input in agricultural production to preserve soils and their biodiversity but also to establish high yields and quality.

Drought stress (DS) is a major concern in the agricultural sector and, in particular, for sugar beet production and sugar content. As such several agricultural practices have been used to minimize yield losses from DS, and foliar application of proline is considered one such approach to improve drought tolerance in growing plants. Hence, the current study examined the proline-related improvements to induce drought tolerance in sugar beet plants. A field experiment was conducted at two locations (Shahrekord and Shalamzar) in Chaharmahal-Bakhtiari province, Iran. Experimental treatments comprised of three DS levels (well water: 100%; mild stress: 75%; severe stress: 50% water requirement of plant), and three proline applications (control: 0; low: 5 mM; high: 10 mM). DS caused a significant up-regulation in leaf proline content, malondialdehyde (MDA) content, hydrogen peroxide (H2O2) content, ascorbate peroxidase, catalase, and peroxidase enzymatic activities. This increase was more pronounced under proline application with concomitant down-regulation of MDA and H2O2 contents. DS also caused a decrease in leaf photosynthetic pigments, leaf relative water contents, membrane stability index and sugar beet root production; however, proline application mitigated these adverse DS effects. The study results suggest beneficial effects of proline applications, which is crucial to mitigation of the detrimental effects of DS in sugar beet by enhancing antioxidant enzymatic activities with concomitant reduction in MDA and H2O2 contents.

The cultivar BRS 420 has superior starch yields in early and late harvest, moderate resistance to the main diseases of the crop, adaptation to mechanized planting and to the no-till system, as well as rapid formation of soil cover (which assists in weed control). It represents an alternative for cassava growers in Paraná and Mato Grosso do Sul.

As in any other plant, the grapevine roots play a vital role in terms of anchorage, uptake of water and nutrients, as well as storage and production of chemicals. Their behaviour and development depend on various factors, namely rootstock genetics, soil physical and chemical features, and field agronomic practices. Canopy management, involving techniques such as defoliation and pruning, could greatly influence root growth. To date, most of the studies on grapevine winter pruning have focused on the effects on yield and quality of the grapes achievable through different pruning systems and techniques, while knowledge regarding root distribution, development, and growth in relation to winter pruning is still not completely understood. In this context, the purpose of our study was to investigate the effect of winter pruning on the root system of field-grown Vitis vinifera cv. Pinot Gris grafted onto rootstock SO4. We compared two pruning treatments (pruned-P and no pruned-NP) and analysed the effect on root distribution and density, the root index, and the root sugar reserve. Root data were analysed in relation to canopy growth and yield, to elucidate the effect of winter pruning on the root/yield ratio. Our data indicated that: (1) winter pruning stimulated the root growth and distribution; (2) canopy development was not negatively affected by this technique; (3) no pruned treatment produced less growth of the roots but a larger canopy. Information regarding both root growth and root canopy ratio is important as it gives us an understanding of the relationship between the aerial and subterranean parts of the plant, how they compete, and finally, offers us the possibility to ponder on the cultural practices.

is a common pest of carrots grown in hot climates. Existing control methods using synthetic nematicides are associated with contamination and intoxication of plants and the production environment. Recent research trends in pest control include investigations on the use of plant materials. In the present study, compost, powder, and essential oil were assessed in comparison with Furadan for mitigating the effects of on carrot plants. The essential oil was applied at 10, 20, and 30 mg·ml , while the compost and powder were applied at 1.0, 2.0, and 3.0 kg·m . The characteristic components of essential oil were trans-α-bergamotene (18.04%), caryophyllene epoxide (15.01%), eugenol (11.59%), carvacrol (11.02%), geraniol (10.13%), 1-octen-3-ol (7.03%), 1,8-cineole (7.02%), δ-elemene (7.01%), and α-copaene (6.20%). The reproduction of on carrot roots and the level of soil infestation were significantly reduced by compost and essential oil. The effect of compost was comparable to that of the standard nematicide – Furadan. Therefore, materials derived from may prove to be an interesting alternative in inhibiting populations.