This study was carried out to assess plasticity to drought of 30 adult fig cultivars,based on a screening of leaf structural and functional traits under sustained deficit irrigation,corresponding to 60%of crop evapotr...This study was carried out to assess plasticity to drought of 30 adult fig cultivars,based on a screening of leaf structural and functional traits under sustained deficit irrigation,corresponding to 60%of crop evapotranspiration.All trees,three per cultivar,are planted in an ex-situ collection in Sais plain,northern Morocco.The measurements concerned leaf area,blade thickness,trichomes density,trichome hair length,stomatal density,stomatal dimensions,stomatal area index,chlorophyll concentration index,relative water content,stomatal conductance,leaf temperature,water loss in detached leaves,cuticular wax content,proline content,total phenolic compounds,and total soluble sugars.The ranking of cultivars regarding drought tolerance was established based on a two-level clustering approach,primarily relying on chlorophyll concentration index and secondarily on water status traits.Results showed significant genotypic variations for all measured traits,except phenolic compounds content.Correlations between structural and functional traits have pinpointed blade thickness and trichome hair length as the key indicators of fig drought tolerance,owing to their involvement in maintaining chlorophyll content under water stress conditions.The extent of the variations shows that fig leaf is endowed with a wide structural and functional diversity,which can give to the species potential for resilience to various environmental stresses,including drought.Among the cultivars assessed,two exotic varieties,“Kadota”and“Royal Blanck”,as well as four local cultivars,namely,“Ferqouch Jmel”,“El Qoti Labied”,“Hamra”and“Fassi”showed the highest drought plasticity level.展开更多
Leaf disease identification is one of the most promising applications of convolutional neural networks(CNNs).This method represents a significant step towards revolutionizing agriculture by enabling the quick and accu...Leaf disease identification is one of the most promising applications of convolutional neural networks(CNNs).This method represents a significant step towards revolutionizing agriculture by enabling the quick and accurate assessment of plant health.In this study,a CNN model was specifically designed and tested to detect and categorize diseases on fig tree leaves.The researchers utilized a dataset of 3422 images,divided into four classes:healthy,fig rust,fig mosaic,and anthracnose.These diseases can significantly reduce the yield and quality of fig tree fruit.The objective of this research is to develop a CNN that can identify and categorize diseases in fig tree leaves.The data for this study was collected from gardens in the Amandi and Mamash Khail Bannu districts of the Khyber Pakhtunkhwa region in Pakistan.To minimize the risk of overfitting and enhance the model’s performance,early stopping techniques and data augmentation were employed.As a result,the model achieved a training accuracy of 91.53%and a validation accuracy of 90.12%,which are considered respectable.This comprehensive model assists farmers in the early identification and categorization of fig tree leaf diseases.Our experts believe that CNNs could serve as valuable tools for accurate disease classification and detection in precision agriculture.We recommend further research to explore additional data sources and more advanced neural networks to improve the model’s accuracy and applicability.Future research will focus on expanding the dataset by including new diseases and testing the model in real-world scenarios to enhance sustainable farming practices.展开更多
Figs (Moracea: Ficus) and fig wasps (Hymenoptera: Chlocloids: Agaonideae) depend on each other to complete their reproduction. Monoecious fig species and their pollinating wasps are in conflict over the use of fig ov...Figs (Moracea: Ficus) and fig wasps (Hymenoptera: Chlocloids: Agaonideae) depend on each other to complete their reproduction. Monoecious fig species and their pollinating wasps are in conflict over the use of fig ovaries which can either produce one seed or one wasp. From observation on Ficus virens Ait., we showed that female flowers with outer layer of ovaries (near to the wall of syconium) had no significant difference from that with inner and interval layer of ovaries (near to the syconium cavity), in which most seeds and wasps were produced. This meant that fig tree provided the same potential resource for seed and wasps production. Observation indicated that there was usually only one foundress in syconium at female flower phase and no com- petition pollinators. Measurement of the style length of female flowers and the ovipositor of pollinators indicated that most ovaries could be reached by pollinator’s ovipositor. However, at the male flower phase, production of seeds was significantly more than that of wasps including non-pollinating wasps but there was no significant difference between seed and pollinating wasp production when without non-pollinating wasps produced. This result indicated that non-pollinating wasps competed ovaries not with seeds but with pollinating wasps for ovipositing. Bagged experiment showed that the sampling fig species was not self-sterile which was important for figs and wasps to survive bad season. Seed production in self-pollinated figs was not significantly different from total wasps in- cluding non-pollinating ones. This might be related with the weaker competition among wasps since bagged figs were not easy to reach by wasps from outside.展开更多
The theme of the Conception of the Virgin Mary fascinated 16th-century Mannerist painters, as manifested in Giorgio Vasari＇s many drawings and paintings and also the numerous replicas in drawings, paintings, and engr...The theme of the Conception of the Virgin Mary fascinated 16th-century Mannerist painters, as manifested in Giorgio Vasari＇s many drawings and paintings and also the numerous replicas in drawings, paintings, and engravings made after his paintings by his contemporary artists. This essay focuses on Vasari＇s complex iconography of The Conception of Our Lady of 1540 at SS. Apostoli in Florence, Italy. In his documentation of the painting, Vasari never referred to or entitled the painting as an Allegory of the Immaculate Conception or Immaculate Conception but coined it as The Conception of Our Lady （Concezione di Nostra Donna） as it will be referred in this essay. Vasari＇s complex iconography derived from the writings of the A retine canon Giovanni Pollastra. The Virgin Mary is depicted as a victorious symbol of grace and salvation, triumphing over evil. Rejoicing angels surround her with scrolls containing Latin inscriptions, QUOS EVE CULPA DAAVIT/MARIAE GRATIAE SOLVIT, ECCE AGNIU[S] and UNIUS ONNOSTAA. These joyful words allude to the restoration of the fate of Adam and Eve after eating the forbidden fruit from the Tree of Knowledge in Paradise. A sinuous serpent coils around the fig tree, while tied-up Old Testament and New Testaments wait for forgiveness and salvation. Three considerations are addressed in this essay： （1） discussion of Vasari＇s recorded commissions; （2） stylistic observations and influences; and （3） interpretation of the imagery, that is, some observations on the symbolism of the painting.展开更多
文摘This study was carried out to assess plasticity to drought of 30 adult fig cultivars,based on a screening of leaf structural and functional traits under sustained deficit irrigation,corresponding to 60%of crop evapotranspiration.All trees,three per cultivar,are planted in an ex-situ collection in Sais plain,northern Morocco.The measurements concerned leaf area,blade thickness,trichomes density,trichome hair length,stomatal density,stomatal dimensions,stomatal area index,chlorophyll concentration index,relative water content,stomatal conductance,leaf temperature,water loss in detached leaves,cuticular wax content,proline content,total phenolic compounds,and total soluble sugars.The ranking of cultivars regarding drought tolerance was established based on a two-level clustering approach,primarily relying on chlorophyll concentration index and secondarily on water status traits.Results showed significant genotypic variations for all measured traits,except phenolic compounds content.Correlations between structural and functional traits have pinpointed blade thickness and trichome hair length as the key indicators of fig drought tolerance,owing to their involvement in maintaining chlorophyll content under water stress conditions.The extent of the variations shows that fig leaf is endowed with a wide structural and functional diversity,which can give to the species potential for resilience to various environmental stresses,including drought.Among the cultivars assessed,two exotic varieties,“Kadota”and“Royal Blanck”,as well as four local cultivars,namely,“Ferqouch Jmel”,“El Qoti Labied”,“Hamra”and“Fassi”showed the highest drought plasticity level.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025).
文摘Leaf disease identification is one of the most promising applications of convolutional neural networks(CNNs).This method represents a significant step towards revolutionizing agriculture by enabling the quick and accurate assessment of plant health.In this study,a CNN model was specifically designed and tested to detect and categorize diseases on fig tree leaves.The researchers utilized a dataset of 3422 images,divided into four classes:healthy,fig rust,fig mosaic,and anthracnose.These diseases can significantly reduce the yield and quality of fig tree fruit.The objective of this research is to develop a CNN that can identify and categorize diseases in fig tree leaves.The data for this study was collected from gardens in the Amandi and Mamash Khail Bannu districts of the Khyber Pakhtunkhwa region in Pakistan.To minimize the risk of overfitting and enhance the model’s performance,early stopping techniques and data augmentation were employed.As a result,the model achieved a training accuracy of 91.53%and a validation accuracy of 90.12%,which are considered respectable.This comprehensive model assists farmers in the early identification and categorization of fig tree leaf diseases.Our experts believe that CNNs could serve as valuable tools for accurate disease classification and detection in precision agriculture.We recommend further research to explore additional data sources and more advanced neural networks to improve the model’s accuracy and applicability.Future research will focus on expanding the dataset by including new diseases and testing the model in real-world scenarios to enhance sustainable farming practices.
基金Supported by the Knowledge Innovation Research Program,Chinese Academy of Sciences (KSCX2-SW-105)
文摘Figs (Moracea: Ficus) and fig wasps (Hymenoptera: Chlocloids: Agaonideae) depend on each other to complete their reproduction. Monoecious fig species and their pollinating wasps are in conflict over the use of fig ovaries which can either produce one seed or one wasp. From observation on Ficus virens Ait., we showed that female flowers with outer layer of ovaries (near to the wall of syconium) had no significant difference from that with inner and interval layer of ovaries (near to the syconium cavity), in which most seeds and wasps were produced. This meant that fig tree provided the same potential resource for seed and wasps production. Observation indicated that there was usually only one foundress in syconium at female flower phase and no com- petition pollinators. Measurement of the style length of female flowers and the ovipositor of pollinators indicated that most ovaries could be reached by pollinator’s ovipositor. However, at the male flower phase, production of seeds was significantly more than that of wasps including non-pollinating wasps but there was no significant difference between seed and pollinating wasp production when without non-pollinating wasps produced. This result indicated that non-pollinating wasps competed ovaries not with seeds but with pollinating wasps for ovipositing. Bagged experiment showed that the sampling fig species was not self-sterile which was important for figs and wasps to survive bad season. Seed production in self-pollinated figs was not significantly different from total wasps in- cluding non-pollinating ones. This might be related with the weaker competition among wasps since bagged figs were not easy to reach by wasps from outside.
文摘The theme of the Conception of the Virgin Mary fascinated 16th-century Mannerist painters, as manifested in Giorgio Vasari＇s many drawings and paintings and also the numerous replicas in drawings, paintings, and engravings made after his paintings by his contemporary artists. This essay focuses on Vasari＇s complex iconography of The Conception of Our Lady of 1540 at SS. Apostoli in Florence, Italy. In his documentation of the painting, Vasari never referred to or entitled the painting as an Allegory of the Immaculate Conception or Immaculate Conception but coined it as The Conception of Our Lady （Concezione di Nostra Donna） as it will be referred in this essay. Vasari＇s complex iconography derived from the writings of the A retine canon Giovanni Pollastra. The Virgin Mary is depicted as a victorious symbol of grace and salvation, triumphing over evil. Rejoicing angels surround her with scrolls containing Latin inscriptions, QUOS EVE CULPA DAAVIT/MARIAE GRATIAE SOLVIT, ECCE AGNIU[S] and UNIUS ONNOSTAA. These joyful words allude to the restoration of the fate of Adam and Eve after eating the forbidden fruit from the Tree of Knowledge in Paradise. A sinuous serpent coils around the fig tree, while tied-up Old Testament and New Testaments wait for forgiveness and salvation. Three considerations are addressed in this essay： （1） discussion of Vasari＇s recorded commissions; （2） stylistic observations and influences; and （3） interpretation of the imagery, that is, some observations on the symbolism of the painting.
