Agricultural Research最新文献

The vineyards present different phenological phases that comprise dormancy, bud break, and flowering buds going through different stages of development, such as inflorescence formation, flowering, fruit set, growth and fruit maturation. To control the quantity and quality of production, thinning is used in table grapes. The technique reduces berry number to improve fruit growth, but it is costly and in some cases impractical in the entire extension of an orchard. The right moment for execution and the intensity are complex issues that involve specific knowledge about the conditions of the vineyard. Therefore, phenological information that can help planning and decision-making about thinning is relevant and can improve the cost-effectiveness of the technique in viticulture. An electronic nose system was developed to collect and analyze compound volatile variations during the growing season, more specifically during the period of bud growth and ripening in three grape cultivars (BRS Vitória, Niagara Rosada, Bordô). The data were collected from October 2021 to February 2022. The research hypothesis is that the electronic nose can identify the general stage of plant development. To verify the hypothesis, a classification analysis was performed for each cultivar. The result showed that all models presented balanced accuracy above 85% for the cultivar BRS Vitória, above 92% for Niagara, and above 93% for Bordô, with better performance for models based on K-nearest neighbors (KNN), and random forest, than those based on extreme learning machine and support vector machine. In the total of 24 models, 9 for BRS Vitória, 9 for Niagara, and 11 for Bordô did not obtain error given the metrics used. It was observed that the normalization of the database is not necessary to improve the accuracy rates obtained, which obtained total rates using the KNN classifier. Regarding the research hypothesis, it is considered that the electronic nose is capable of distinguishing between the different stages proposed for each analyzed cultivar and between them. The results of this work indicate a potential use of the electronic nose to aid decision-making in vineyard activities.

Food crops contribute to food security in developing countries while being planted and harvested for profit in many industrialized countries. To improve food security and farmer income, the National Agricultural Research System of India developed and disseminated many crop varieties through technology transfer. Non-exclusive licensing allowed faster distribution due to multiple players having seed production rights and a market pricing control mechanism. Current literature shows technology transfer mechanism research on non-exclusive licensing is scarce. This study investigates the determinants of crop variety tech transfer in the case of non-exclusive licensing. It collects data from 100 seed licensees of India's largest agricultural research institute to examine the process from their perspective. Multivariate regression is applied to analyze the data under four domains, i.e., technology, technology transferor, tech transfer procedure, and policy. Technology readiness, availability, and an amicable tech transfer procedure boost technology commercialization, while stringent tech transfer policies negatively affect it. Results are used to create an effective technology transfer action framework to improve crop variety technology dissemination and enhance food security.

The greenhouse gas (GHG) emissions from agriculture, forestry, and other land use (AFOLU) account for more than 10% of the total GHG emissions in Iran. To reduce the environmental impact, assessments of Iran’s GHG emissions status are critical for identifying the national policies to achieve Sustainable Development Goals (SDGs) in the bio-based industry. However, there is no study exploring the dependency between AFOLU and GHG emissions in Iran by using the Vine Copula approach. Hence, the study aims to examine the causality direction and correlation structure among selected horticulture, farming crops, livestock, and poultry products and carbon dioxide (CO₂), nitrogen dioxide (N₂O), and methane emissions (CH₄) in the Iranian agriculture sector over the period 1961–2019, to determine which crops or products are more responsible to deteriorate the environment. The empirical strategy used a C-Vine Copula model to measure the correlations together with the Granger causality (GC) test to analyze the causality links. According to the empirical findings, several crops and products are the sources of emissions. Rice and vegetable cultivations, as well as meat and milk products (Kendall’s τ values of 0.37, 0.33, 0.31, and 0.31, respectively), are the leading sources of CH₄ emissions. Legumes, eggs, maize, rice, and milk enhance N₂O emissions, while CO₂ emissions are caused by apple, potato, and apricot crops (Kendall’s τ values of 0.22, 0.18, and 0.16, respectively). Finally, based on the findings, policy implications are offered.

Climate change stands as one of the most pressing challenges confronting global ecosystems and human livelihoods. The agriculture sector of Anuradhapura district, Sri Lanka, well renowned for its pivotal role in the nation’s food production, faces an increasing threat from the changing climate. This study aims to incorporate the indicator system method which uses a set of indicators to assess the agricultural vulnerability (AV) to climate change in Anuradhapura district. The AV assessment used in this study involves three principal components exposure, sensitivity, and adaptive capacity. The indicators are normalized to allow spatial analysis and smooth integration within a geographic information system (GIS) framework. The AV of Anuradhapura district ranged from 0.32 to 0.67 and was divided among five levels very low, low, moderate, high, and very high. The findings suggest that Anuradhapura’s agricultural sector was significantly impacted by climate change as the majority of the total area was found to have very high, high, and moderate levels of AV with 25, 28, and 24%, respectively. The results obtained from this study are essential for formulating plans to improve Anuradhapura’s agricultural sector resilience and adaptability to ensure food security and livelihood sustainability considering the ever-changing climate.

The Oriental fruit fly Bactrocera dorsalis (Hendel) is a highly significant, invasive pest of fruits which severely affect the global fruit trade. The advent of CRISPR/Cas9 has opened up new avenues for developing futurist management approaches as standalone or complementing other approaches. In this context, numerous earlier studies have documented the mutation of the white locus in B. dorsalis. Studies on Drosophila melanogaster and D. suzukii demonstrated that the white locus (wh) plays a crucial role in pigmentation and various other physiological functions like reproduction. Therefore, in the present study, we have generated a homozygous white eye mutants (wh^−/−) bearing a four base pair deletion and studied the possible effects on the biological attributes such as reproductive fitness and body size as compared to the wild flies. A single pair of adults produced significantly lesser offsprings (5.80 ± 3.67 pupae) in the cross involving wh^−/−♀ × wh^−/−♂ than in the WT♀ × WT♂ cross (21.80 ± 3.91 pupae). The morphometric analysis showed that wh^−/− individuals exhibited a reduced overall body size compared to wild-type males and females. Also, there was an overall increase in the life cycle of wh^−/− individuals (23.20 ± 0.47 days) as compared to WT individuals (19.20 ± 0.51 days). This study provides comprehensive insights into the effects of the white gene mutation and provide potential avenues for future research on devising novel management strategies against B. dorsalis.

Bemisia tabaci transmits begomoviruses that cause the most devastating disease of Capsicum chinense in tropical regions. Here we first evaluated the incidence and severity of Begomovirus symptoms on habanero pepper landraces H-224 and H-241 and commercial cultivar Jaguar that were naturally infested with B. tabaci in the field. Then we treated H-241 in the greenhouse with different botanical insecticides and assessed the Begomovirus symptoms. In the field, the mean area under the disease progress curve for incidence and severity did not differ significantly (P > 0.05) among the peppers tested; however, the final incidence of symptoms was significantly lower on Jaguar pepper than on the two landraces. Jaguar and H-241 had higher fruit yield than H-224. In the greenhouse experiment, the botanical insecticides protected H-241 against viral symptoms similarly to the treatment with only chemical insecticides. The fruit yield did not differ significantly between plants treated with the botanical insecticide combinations (2.1–2.5 kg plant⁻¹) and those treated with only chemical insecticides (2.3 kg plant⁻¹). The use of botanical insecticides holds promise as an environmental-friendly option to manage B. tabaci-transmitted begomoviruses in habanero pepper.

Multiple changes in centralized agricultural policies over the past 100 years have influenced crop production in Russia. The differential contributions of political and climatic factors in the performance of Russian agriculture have been widely examined in many historical and economic contexts. Besides traditional descriptive analysis statistical models proved their usefulness due to the quantitation of the role of both factors. We review the results of the statistical models of climate-driven dynamics of grain production in Russia in different historical periods. The modeling approach also proves its actuality today when Russia surprisingly emerges as a major net exporter of grain. Many experts attribute this success to a warmer climate, extending the growing season. Yet climate-yield modes are unable to fully explain this unprecedented yield increase with climate change alone. We propose that projecting climate change’s impact on yields under climate change in countries with transition economies needs to account more for the political factor in grain production.

Failure of pollination in date palms usually happens when temperature drops during the flowering season, causing a reduction in the fruit set and yield. Screening low temperature-tolerant date palm cultivars are needed in order to stabilize yield in such conditions. The present study was conducted to ascertain the impacts of varying temperatures, from 10 to 35 °C at 5 °C intervals, on the pollen germination and tube growth of eight date palm cultivars known as; Bouhlesse 1 (B1), Deglet-Baida 1 (DB1), Deglet-Nour 1 (DN1), Ghars 1 (GH1), Ghars 2 (GH2), Halwaya 1 (HL1), Moch-Deglet 1 (MD1) and Moch-Deglet2 (MD2). The studied cultivars belong to three flowering periods; precocious, medium and late period. Pollen germination and pollen tube growth were influenced by temperature across all cultivars. Nevertheless, the flowering periods did not have any significant impact on pollen germination and pollen tube length. In all cultivars, the optimal temperatures for pollen germination, above 90%, were found between 15 and 30 °C. The optimum temperature, according to the pollen tube growth, was recorded at 20 °C for DN1, H1, MD1 and MD2 and at 25 °C for B1, DB1, G1 and G2, respectively. The lowest rates of pollen germination and pollen tube growth were recorded at 10 °C, with the exception of MD2, G1, and H1, where the pollen germination rate approached 80%. Therefore, these cultivars could be used for pollination of date palm female during cold flowering seasons.

Seaweed extracts are proven to be potent biostimulants due to the presence of wide range of nutrients including mineral like potassium and other macro-micronutrients, plant growth hormones, amino acids, vitamins, glycine betaines and quaternary ammonium compounds in them. In the present study, potassium-rich powders were obtained from some commercially important tropical red seaweeds viz. Kappaphycus alvarezii, Gracilaria salicornia, G. edulis, G. firma and G. heteroclada and Eucheuma spinosum and checked for their biostimulant effect through green gram seedling bioassay study on in vitro using WinRhizo software, and we found that extracts of all species increased the root development at significant level (p < 0.05) as compared to standard nutrient medium. G. salicornia of Indian origin which is naturally available on a commercial level (>1000 t dry per year) was taken for further studies and manufactured 3 variants of potassium-rich biostimulants, viz. concentrated seaweed extract (CSE), potassium-rich water-soluble powder (PSP) and seaweed fortified granule (SFG), and tested their biostimulant activity on cassava root at farmer’s field and found to increase the tuber yield to 17.40%, 20.09% and 22.19%, respectively, with high starch content, less incidence of cassava brown streak virus disease (CBSD) and increased nutrient use efficiency over control plants. Based on the results of present study, potassium-rich biostimulant obtained from G. salicornia can be applied to cassava for yield and quality improvement.

This study investigated the effect of plant species, month of the year, time of the day, and weather variables on hen percentage outdoor and ranging distance of Lohmann LSL Classic (LW) and Lohmann Sandy (LS) strains. Mentha piperita (M. piperita), Petroselinum crispum (P. crispum), and Medicago sativa (M. sativa) were studied. From 14 to 42 weeks of age, the number of hens outside and the distance ranged: from 0 to 3.0 m, 3.1–6.0 m, and 6.1–9.0 m from the barn were live counted at 9:00 a.m., 12:00, and 3:00 p.m. daily. Also, within the same time, the weather conditions (live observed), and the indoor and outdoor temperatures were recorded accordingly. More LW than LS hens were observed outside and more LS than LW hens ranged further than 3.0 m from the barn (p < 0.01). More hens were found in the M. sativa than in other plant treatments (p < 0.01). The percentage of hens outside and ranging distance increased at 12:00 noon, at an indoor–outdoor temperature difference of ≥ 3 °C, and in October (p < 0.01). Hen percentage on the range and ranging distance increased and decreased in cloudy and foggy weather, respectively (p < 0.01). Additionally, the interaction between strain and the month of the year, and the interaction between strain and the weather conditions affected hen percentage outdoor (p < 0.01). It was concluded that the hen percentage outdoor and ranging distance can be modulated by plant species and laying hen strain. It is crucial to consider these two aspects in further studies so that the ranging behaviors of hens can be enhanced.