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Cold storage is expensive for smallholder farmers and seed processors in developing countries. Smallholder farmers continue to resort to traditional storage methods such as polypropylene (PP) bags for maize grain storage. They often dose the grains with chemicals to preserve them. However, hermetic bags have proven to provide superior protection to grains during storage without chemical treatment. With the advent of the COVID-19 virus which distorted many food systems across continents, stakeholders in the grain industry need to adopt better systems to reduce post-harvest food loss and improve food security. In this study, maize grain quality, nutritional content and viability were compared under three storage methods (PP bags with Phostoxin treatment, cold storage, and hermetic bag) over a storage period of four months. The results showed that the hermetic bag maintained the moisture content (MC) of the stored grains with 0.40% variations from the initial MC of 13% at the end of the storage period compared to 0.70% and 1.10% for grains stored under cold storage and in PP bags, respectively. Grain damage after the 4th month of storage in the hermetic bag had only increased by 0.40% from an initial 13.3% before storage compared to an increase of 6% for cold storage, which was attributed to unstable power during the storage period, and 4.30% for grains stored in the PP bag. Carbon dioxide concentration in the hermetic bag was maintained at about 11% throughout the storage period indicating low microbial activity. The hermetic bag technology was identified as the best option for quality preservation during storage of maize grain over the other methods, and its adoption by smallholder farmers in Ghana should be considered.
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This paper characterises South African sugarcane production for the 2021/22 milling season, from an agricultural perspective, to enable the industry to evaluate recent production strategies, and to identify priorities for improved efficiency. The industry's cane and sugar production during the 2021/22 season was 17.2 and 1.84 million tons, respectively. These figures show a marked drop of 5.6% for cane and 8.7% for sugar, when compared to the production figures for the 2020/21 season. The estimated industry average cane yield and quality also decreased slightly, compared to the previous season, but the main reason the drop in cane and sugar production was the limited milling capacity at several mills in KwaZulu-Natal. The civil unrest in July 2021 exacerbated the situation, causing disruptions to harvest and mill operations, as well as the subsequent closure of mills in parts of KwaZulu-Natal. The area harvested decreased considerably from an estimated 254 028 ha in 2020/21 to 241 030 ha in 2021/22 while estimated carry-over cane area increased from 24 029 ha to 32 476 ha over the same period. Rainfall was generally well above the long-term mean and well-distributed in most areas, while irrigation water supply also improved remarkably, compared to 2020 supply. Low temperatures and reduced sunshine duration caused yield reduction in the northern irrigated areas, but most rainfed areas experienced yield improvements when compared to 2020/21, because of the good rainfall. The Midlands region experienced severe frost damage during the winter of 2021, which had a negative impact on cane yield and quality. The Sugar Industry Value Chain Master Plan continued to help stabilise local sugar demand as well as reduce imports and exports at low world market prices, which all contributed to a 6% increase in the Recoverable Value (RV) price. This improved profitability for both largeand small-scale growers. COVID-19 had no noteworthy impact on sugarcane production.
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These proceedings contain over 100 articles discussing the latest developments and challenges facing the vine and wine industry, focusing on 4 major themes such as viticulture, oenology, economy and law, and safety and health. Specific topics discussed include the adaptation and optimization of viticultural resources, the characterization of different microclimate to improve grape quality, the validation of new oenological techniques, and the resilience of the wine sector after the COVID-19 pandemic. Other topics included the impact of climate change on viticulture, the market competitiveness of the wine sector, and public health aspects wine consumption.
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The market for biostimulants is rapidly growing and many companies are expanding their portfolio with the introduction of these products, which are increasingly used to improve the management of crop systems and increase their sustainability. In fact, biostimulants, if properly used, can increase crop yields and quality, reducing fertilizer inputs and increasing plant tolerance against abiotic stresses.
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Introduction: Most areas under spring sugar beet cultivation face severe water restrictions and increasing the area under cultivation of this crop in most of these areas is contrary to the principle of conservation of water and soil resources. The use of new areas for winter sugar beet cultivation should be the area under cultivation of this crop in hot and dry areas. Therefore, winter sowing (pending) of sugar beet with emphasis on the limitations of the country's water resources has been proposed as a solution. Materials and Methods: In this study, the quantitative and qualitative yield of 16 sugar beet genotypes in winter planting were studied as a randomized complete block design with four replications in the Torbat-e-Jam region in the two cropping years (2020-2021 and 2021-2022). The studied genotypes included F-20739, F-20837, F-21083, SBSI-5, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, FDIR 19 B 4028, F-20591, SBSI-6, SBSI-16, SBSI-7 and SBSI-17 are the breeding populations obtained from the gene bank of the Sugar Beet Seed Breeding Research Institute. In this research, traits such as root yield, sugar content, sugar yield, white sugar yield, Na, K, N, alkalinity, molasses sugar, white sugar content, and extraction coefficient of sugar were measured. Data were analyzed using SAS 9.1 software. The analysis of variance on test data and comparison to the middle of the Duncan test was performed at the 5% level. Factor analysis was calculated to identify the main factors using MINITAB software. Cluster analysis of the studied genotypes was obtained after standardizing the data by the Ward method and using Euclidean distance criterion with the help of SPSS software. Results and Discussion: The results of the combined analysis of variance showed that there was a significant difference between different genotypes of sugar beet at the level of 1% probability for all studied traits except for nitrogen content. The mean comparison showed that the SBSI-15 genotype had the highest root yield (60.66 ton.ha). It should be noted that this genotype in terms of yield index traits did not show significantly different from genotypes F-20739, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, and FDIR 19 B 4028. Also, the F-20739 genotype had the highest amounts of sugar content (19.5%), white sugar content (16.3%) and extraction coefficient of sugar (83.2%) and the lowest amount of potassium (4.24 meq .100 g-1 of root weight) and Molasses sugar (2.7%). In addition, the highest sugar yield (10.69 t/ha) and white sugar yield (8.68 t/ha) were in FDIR 19 B 3021 genotype. Investigating the correlation of traits showed the highest positive and significant correlation was between sugar yield and white sugar yield (0.99**) and the highest negative and significant correlation was between extraction coefficient of sugar and molasses sugar (-0.95**). Principal factor analysis based on the mean of the traits identified three factors that accounted for a total of 91% of the variability between the data. SBSI-15, SVZA 2019-JD0398, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, and FDIR 19 B 4028 genotypes are distinguished different from other genotypes and they were as superior genotypes in terms of yield index traits. The dendrogram generated from the cluster analysis for white sugar yield classified genotypes into three main groups.
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Cape gooseberry fruits have positioned in the world market due to their excellent nutritional characteristics, because they are an ideal food that contributes to raising the defenses of the human body and helps it to face diseases such as COVID-19, they are also a natural source of antioxidants and anticancer agents. In order to avoid the physiopathy of cracking in cape gooseberry fruits, these were characterized at harvest time, coming from greenhouse plants irrigated with different applications of water levels and irrigation frequencies, as well as different calcium doses, in a design of randomized complete blocks with 12 treatments. The blocks were the irrigation frequencies (4, 9 and 14 days), while the treatments were the combination of four irrigation coefficients (0.7, 0.9, 1.1 and 1.3 of the evaporation of the tank class A) and three doses of calcium (0, 50 and 100 kg ha-1). The plants were sown in 20 L pots with peat moss substrate. Fruits were harvested at the color stage 5 and 6 of the calyx, from 19 weeks after transplanting. The different water levels and irrigation frequencies did not significantly affect the firmness of the cape gooseberry fruits, but there was a strong tendency that cracked gooseberry fruits are less firm than healthy fruits. As the irrigation coefficient increased, the total soluble solids (TSS) increased while the total titratable acids (TTA) decreased. Irrigation frequency of 14 days generated fruits with higher TSS and pH values. The calcium doses did not affect the calcium concentration in the fruits or the TSS, TTA and pH values. Therefore, it can be concluded that incremented irrigation coefficients (up to 1.3) increase the quality of cape gooseberry fruits.
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Surface ozone is damaging to human health and crop yields. When evaluating global air pollution risk, gridded datasets with high accuracy are desired to reflect the local variations in air pollution concentrations. Here, a cluster‐enhanced ensemble machine learning method was used to develop a new 0.5‐degree monthly surface ozone data set during 2003–2019 by combining numerous informative variables. The overall accuracy of our data set is 91.5% (90.8% for space and 92.3% for time). Historically, populations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest ozone concentrations. Globally, the population weighted ozone concentration in the peak season is 47.07 ppbv. Our results highlight that ozone pollution is intensifying in some regions, and implicate air quality management is crucial to secure human health from air pollution. Plain Language Summary: Surface ozone is one of the most hazardous air pollutants to human health and plants. However, estimation of global surface ozone is still limited. Here, by using state‐of‐the‐art machine learning techniques, we fuse satellite, chemical transport model outputs, atmospheric reanalyses, and emission data with surface observations to construct a full coverage and long‐time period surface ozone data set. We demonstrate that surface population weighted ozone concentration in North America and Europe has decreased from 2003 to 2019, while ozone pollution in East Asia has intensified during 2016–2019. We also show at least 37% of the world's population is exposed to ozone greater than the World Health Organization's interim target one of 50 ppbv (MDA8) in the peak season. Our results could help identify the key regions for improving global air quality and offers an insightful data set for human health assessments and air quality management. Key Points: A cluster‐enhanced ensemble machine learning method can predict global surface ozone with high accuracyPopulations in South Asia, North Africa and Middle‐East, and High‐income North America are exposed to the highest MDA8 during 2003–2019At least 37% of world's population is exposed to greater than 50 ppbv MDA8 in peak seasons [ FROM AUTHOR] Copyright of Geophysical Research Letters is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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The audience of consumers of watermelon and melon is the widest, the reason for this is the light and at the same time rich composition of sweet fruits. Given the increase in complications among the country's population associated with the postponed coronavirus pandemic, the consumption of highly vitaminized and environmentally friendly products is especially important. Unfortunately, in recent years there has been an acute issue of unfair production of melons and gourds. In pursuit of an early harvest, producers completely forget about quality. Melon products contaminated with nitrates can lead to the most serious consequences. The way out of this situation is to use biological stimulants of the vital activity of soil microorganisms, which accelerates the maturation processes, while reducing the introduction of agrochemicals by almost twice. According to the results of our research, it was found that the treatment of plants with biological stimulants increased the yield of watermelon by 33.88%, melon -27.30%. Plants treated with bio stimulants were larger, had a greater number of ovaries to control, respectively. Biochemical analysis showed an increase in dry matter, total sugar and ascorbic acid in the fruits of watermelon and melon.